Gitignore aider

# Aider chat conversation:

USER: `invokeai/backend/model_manager/convert_ckpt_to_diffusers.py` Im having issues with cpu memory, not gpu memory

ASSISTANT: To address CPU memory issues, we can make the following changes:

1. Use `del` to explicitly delete large objects when they are no longer needed.
2. Use `gc.collect()` to force garbage collection after deleting large objects.

Here are the *SEARCH/REPLACE* blocks:

invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
```python
<<<<<<< SEARCH
    vae = AutoencoderKL(**vae_config)
    with torch.no_grad():
        vae.load_state_dict(converted_vae_checkpoint)
        vae.to(precision)
        torch.cuda.empty_cache()
=======
    vae = AutoencoderKL(**vae_config)
    with torch.no_grad():
        vae.load_state_dict(converted_vae_checkpoint)
        del converted_vae_checkpoint  # Free memory
        import gc
        gc.collect()
        vae.to(precision)
>>>>>>> REPLACE
```

invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
```python
<<<<<<< SEARCH
    pipe = download_from_original_stable_diffusion_ckpt(Path(checkpoint_path).as_posix(), **kwargs)
    with torch.no_grad():
        pipe = pipe.to(precision)
        torch.cuda.empty_cache()
=======
    pipe = download_from_original_stable_diffusion_ckpt(Path(checkpoint_path).as_posix(), **kwargs)
    with torch.no_grad():
        del kwargs  # Free memory
        import gc
        gc.collect()
        pipe = pipe.to(precision)
>>>>>>> REPLACE
```

invokeai/backend/model_manager/convert_ckpt_to_diffusers.py
```python
<<<<<<< SEARCH
    pipe = download_controlnet_from_original_ckpt(checkpoint_path.as_posix(), **kwargs)
    with torch.no_grad():
        pipe = pipe.to(precision)
        torch.cuda.empty_cache()
=======
    pipe = download_controlnet_from_original_ckpt(checkpoint_path.as_posix(), **kwargs)
    with torch.no_grad():
        del kwargs  # Free memory
        import gc
        gc.collect()
        pipe = pipe.to(precision)
>>>>>>> REPLACE
```

.gitignore

@@ -188,3 +188,4 @@ installer/install.sh
 installer/update.bat
 installer/update.sh
 installer/InvokeAI-Installer/
+.aider*

docker/README.md

@@ -64,7 +64,7 @@ GPU_DRIVER=nvidia
 
 Any environment variables supported by InvokeAI can be set here - please see the [Configuration docs](https://invoke-ai.github.io/InvokeAI/features/CONFIGURATION/) for further detail.
 
-## Even Moar Customizing!
+## Even More Customizing!
 
 See the `docker-compose.yml` file. The `command` instruction can be uncommented and used to run arbitrary startup commands. Some examples below.
 

docs/features/CONTROLNET.md

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

docs/help/diffusion.md

@@ -20,7 +20,7 @@ When you generate an image using text-to-image, multiple steps occur in latent s
 4. The VAE decodes the final latent image from latent space into image space.
 
 Image-to-image is a similar process, with only step 1 being different:
-1. The input image is encoded from image space into latent space by the VAE. Noise is then added to the input latent image. Denoising Strength dictates how may noise steps are added, and the amount of noise added at each step. A Denoising Strength of 0 means there are 0 steps and no noise added, resulting in an unchanged image, while a Denoising Strength of 1 results in the image being completely replaced with noise and a full set of denoising steps are performance. The process is then the same as steps 2-4 in the text-to-image process. 
+1. The input image is encoded from image space into latent space by the VAE. Noise is then added to the input latent image. Denoising Strength dictates how many noise steps are added, and the amount of noise added at each step. A Denoising Strength of 0 means there are 0 steps and no noise added, resulting in an unchanged image, while a Denoising Strength of 1 results in the image being completely replaced with noise and a full set of denoising steps are performance. The process is then the same as steps 2-4 in the text-to-image process. 
 
 Furthermore, a model provides the CLIP prompt tokenizer, the VAE, and a U-Net (where noise prediction occurs given a prompt and initial noise tensor).
 

installer/templates/invoke.bat.in

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

installer/templates/invoke.sh.in

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

invokeai/app/api/dependencies.py

@@ -30,7 +30,7 @@ from ..services.model_images.model_images_default import ModelImageFileStorageDi
 from ..services.model_manager.model_manager_default import ModelManagerService
 from ..services.model_records import ModelRecordServiceSQL
 from ..services.names.names_default import SimpleNameService
-from ..services.session_processor.session_processor_default import DefaultSessionProcessor
+from ..services.session_processor.session_processor_default import DefaultSessionProcessor, DefaultSessionRunner
 from ..services.session_queue.session_queue_sqlite import SqliteSessionQueue
 from ..services.urls.urls_default import LocalUrlService
 from ..services.workflow_records.workflow_records_sqlite import SqliteWorkflowRecordsStorage
@@ -103,7 +103,7 @@ class ApiDependencies:
         )
         names = SimpleNameService()
         performance_statistics = InvocationStatsService()
-        session_processor = DefaultSessionProcessor()
+        session_processor = DefaultSessionProcessor(session_runner=DefaultSessionRunner())
         session_queue = SqliteSessionQueue(db=db)
         urls = LocalUrlService()
         workflow_records = SqliteWorkflowRecordsStorage(db=db)

invokeai/app/api/routers/images.py

@@ -69,7 +69,7 @@ async def upload_image(
     if isinstance(metadata_raw, str):
         _metadata = metadata_raw
     else:
-        ApiDependencies.invoker.services.logger.warn("Failed to parse metadata for uploaded image")
+        ApiDependencies.invoker.services.logger.debug("Failed to parse metadata for uploaded image")
         pass
 
     # attempt to parse workflow from image
@@ -77,7 +77,7 @@ async def upload_image(
     if isinstance(workflow_raw, str):
         _workflow = workflow_raw
     else:
-        ApiDependencies.invoker.services.logger.warn("Failed to parse workflow for uploaded image")
+        ApiDependencies.invoker.services.logger.debug("Failed to parse workflow for uploaded image")
         pass
 
     # attempt to extract graph from image
@@ -85,7 +85,7 @@ async def upload_image(
     if isinstance(graph_raw, str):
         _graph = graph_raw
     else:
-        ApiDependencies.invoker.services.logger.warn("Failed to parse graph for uploaded image")
+        ApiDependencies.invoker.services.logger.debug("Failed to parse graph for uploaded image")
         pass
 
     try:

invokeai/app/api/sockets.py

@@ -15,6 +15,7 @@ from invokeai.app.services.events.events_common import (
     DownloadCancelledEvent,
     DownloadCompleteEvent,
     DownloadErrorEvent,
+    DownloadEventBase,
     DownloadProgressEvent,
     DownloadStartedEvent,
     FastAPIEvent,
@@ -34,21 +35,53 @@ from invokeai.app.services.events.events_common import (
     QueueClearedEvent,
     QueueEventBase,
     QueueItemStatusChangedEvent,
-    SessionCanceledEvent,
-    SessionCompleteEvent,
-    SessionStartedEvent,
     register_events,
 )
 
 
 class QueueSubscriptionEvent(BaseModel):
+    """Event data for subscribing to the socket.io queue room.
+    This is a pydantic model to ensure the data is in the correct format."""
+
     queue_id: str
 
 
 class BulkDownloadSubscriptionEvent(BaseModel):
+    """Event data for subscribing to the socket.io bulk downloads room.
+    This is a pydantic model to ensure the data is in the correct format."""
+
     bulk_download_id: str
 
 
+QUEUE_EVENTS = {
+    InvocationStartedEvent,
+    InvocationDenoiseProgressEvent,
+    InvocationCompleteEvent,
+    InvocationErrorEvent,
+    QueueItemStatusChangedEvent,
+    BatchEnqueuedEvent,
+    QueueClearedEvent,
+}
+
+MODEL_EVENTS = {
+    DownloadCancelledEvent,
+    DownloadCompleteEvent,
+    DownloadErrorEvent,
+    DownloadProgressEvent,
+    DownloadStartedEvent,
+    ModelLoadStartedEvent,
+    ModelLoadCompleteEvent,
+    ModelInstallDownloadProgressEvent,
+    ModelInstallDownloadsCompleteEvent,
+    ModelInstallStartedEvent,
+    ModelInstallCompleteEvent,
+    ModelInstallCancelledEvent,
+    ModelInstallErrorEvent,
+}
+
+BULK_DOWNLOAD_EVENTS = {BulkDownloadStartedEvent, BulkDownloadCompleteEvent, BulkDownloadErrorEvent}
+
+
 class SocketIO:
     _sub_queue = "subscribe_queue"
     _unsub_queue = "unsubscribe_queue"
@@ -66,45 +99,9 @@ class SocketIO:
         self._sio.on(self._sub_bulk_download, handler=self._handle_sub_bulk_download)
         self._sio.on(self._unsub_bulk_download, handler=self._handle_unsub_bulk_download)
 
-        register_events(
-            {
-                InvocationStartedEvent,
-                InvocationDenoiseProgressEvent,
-                InvocationCompleteEvent,
-                InvocationErrorEvent,
-                SessionStartedEvent,
-                SessionCompleteEvent,
-                SessionCanceledEvent,
-                QueueItemStatusChangedEvent,
-                BatchEnqueuedEvent,
-                QueueClearedEvent,
-            },
-            self._handle_queue_event,
-        )
-
-        register_events(
-            {
-                DownloadCancelledEvent,
-                DownloadCompleteEvent,
-                DownloadErrorEvent,
-                DownloadProgressEvent,
-                DownloadStartedEvent,
-                ModelLoadStartedEvent,
-                ModelLoadCompleteEvent,
-                ModelInstallDownloadProgressEvent,
-                ModelInstallDownloadsCompleteEvent,
-                ModelInstallStartedEvent,
-                ModelInstallCompleteEvent,
-                ModelInstallCancelledEvent,
-                ModelInstallErrorEvent,
-            },
-            self._handle_model_event,
-        )
-
-        register_events(
-            {BulkDownloadStartedEvent, BulkDownloadCompleteEvent, BulkDownloadErrorEvent},
-            self._handle_bulk_image_download_event,
-        )
+        register_events(QUEUE_EVENTS, self._handle_queue_event)
+        register_events(MODEL_EVENTS, self._handle_model_event)
+        register_events(BULK_DOWNLOAD_EVENTS, self._handle_bulk_image_download_event)
 
     async def _handle_sub_queue(self, sid: str, data: Any) -> None:
         await self._sio.enter_room(sid, QueueSubscriptionEvent(**data).queue_id)
@@ -119,13 +116,10 @@ class SocketIO:
         await self._sio.leave_room(sid, BulkDownloadSubscriptionEvent(**data).bulk_download_id)
 
     async def _handle_queue_event(self, event: FastAPIEvent[QueueEventBase]):
-        event_name, payload = event
-        await self._sio.emit(event=event_name, data=payload.model_dump(mode="json"), room=payload.queue_id)
+        await self._sio.emit(event=event[0], data=event[1].model_dump(mode="json"), room=event[1].queue_id)
 
-    async def _handle_model_event(self, event: FastAPIEvent[ModelEventBase]) -> None:
-        event_name, payload = event
-        await self._sio.emit(event=event_name, data=payload.model_dump(mode="json"))
+    async def _handle_model_event(self, event: FastAPIEvent[ModelEventBase | DownloadEventBase]) -> None:
+        await self._sio.emit(event=event[0], data=event[1].model_dump(mode="json"))
 
     async def _handle_bulk_image_download_event(self, event: FastAPIEvent[BulkDownloadEventBase]) -> None:
-        event_name, payload = event
-        await self._sio.emit(event=event_name, data=payload.model_dump(mode="json"), room=payload.bulk_download_id)
+        await self._sio.emit(event=event[0], data=event[1].model_dump(mode="json"), room=event[1].bulk_download_id)

invokeai/app/invocations/compel.py

@@ -65,11 +65,7 @@ class CompelInvocation(BaseInvocation):
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> ConditioningOutput:
         tokenizer_info = context.models.load(self.clip.tokenizer)
-        tokenizer_model = tokenizer_info.model
-        assert isinstance(tokenizer_model, CLIPTokenizer)
         text_encoder_info = context.models.load(self.clip.text_encoder)
-        text_encoder_model = text_encoder_info.model
-        assert isinstance(text_encoder_model, CLIPTextModel)
 
         def _lora_loader() -> Iterator[Tuple[LoRAModelRaw, float]]:
             for lora in self.clip.loras:
@@ -84,19 +80,21 @@ class CompelInvocation(BaseInvocation):
         ti_list = generate_ti_list(self.prompt, text_encoder_info.config.base, context)
 
         with (
-            ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (
-                tokenizer,
-                ti_manager,
-            ),
+            # apply all patches while the model is on the target device
             text_encoder_info as text_encoder,
-            # Apply the LoRA after text_encoder has been moved to its target device for faster patching.
+            tokenizer_info as tokenizer,
             ModelPatcher.apply_lora_text_encoder(text_encoder, _lora_loader()),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
-            ModelPatcher.apply_clip_skip(text_encoder_model, self.clip.skipped_layers),
+            ModelPatcher.apply_clip_skip(text_encoder, self.clip.skipped_layers),
+            ModelPatcher.apply_ti(tokenizer, text_encoder, ti_list) as (
+                patched_tokenizer,
+                ti_manager,
+            ),
         ):
             assert isinstance(text_encoder, CLIPTextModel)
+            assert isinstance(tokenizer, CLIPTokenizer)
             compel = Compel(
-                tokenizer=tokenizer,
+                tokenizer=patched_tokenizer,
                 text_encoder=text_encoder,
                 textual_inversion_manager=ti_manager,
                 dtype_for_device_getter=TorchDevice.choose_torch_dtype,
@@ -106,7 +104,7 @@ class CompelInvocation(BaseInvocation):
             conjunction = Compel.parse_prompt_string(self.prompt)
 
             if context.config.get().log_tokenization:
-                log_tokenization_for_conjunction(conjunction, tokenizer)
+                log_tokenization_for_conjunction(conjunction, patched_tokenizer)
 
             c, _options = compel.build_conditioning_tensor_for_conjunction(conjunction)
 
@@ -136,11 +134,7 @@ class SDXLPromptInvocationBase:
         zero_on_empty: bool,
     ) -> Tuple[torch.Tensor, Optional[torch.Tensor]]:
         tokenizer_info = context.models.load(clip_field.tokenizer)
-        tokenizer_model = tokenizer_info.model
-        assert isinstance(tokenizer_model, CLIPTokenizer)
         text_encoder_info = context.models.load(clip_field.text_encoder)
-        text_encoder_model = text_encoder_info.model
-        assert isinstance(text_encoder_model, (CLIPTextModel, CLIPTextModelWithProjection))
 
         # return zero on empty
         if prompt == "" and zero_on_empty:
@@ -177,20 +171,23 @@ class SDXLPromptInvocationBase:
         ti_list = generate_ti_list(prompt, text_encoder_info.config.base, context)
 
         with (
-            ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (
-                tokenizer,
-                ti_manager,
-            ),
+            # apply all patches while the model is on the target device
             text_encoder_info as text_encoder,
-            # Apply the LoRA after text_encoder has been moved to its target device for faster patching.
+            tokenizer_info as tokenizer,
             ModelPatcher.apply_lora(text_encoder, _lora_loader(), lora_prefix),
             # Apply CLIP Skip after LoRA to prevent LoRA application from failing on skipped layers.
-            ModelPatcher.apply_clip_skip(text_encoder_model, clip_field.skipped_layers),
+            ModelPatcher.apply_clip_skip(text_encoder, clip_field.skipped_layers),
+            ModelPatcher.apply_ti(tokenizer, text_encoder, ti_list) as (
+                patched_tokenizer,
+                ti_manager,
+            ),
         ):
             assert isinstance(text_encoder, (CLIPTextModel, CLIPTextModelWithProjection))
+            assert isinstance(tokenizer, CLIPTokenizer)
+
             text_encoder = cast(CLIPTextModel, text_encoder)
             compel = Compel(
-                tokenizer=tokenizer,
+                tokenizer=patched_tokenizer,
                 text_encoder=text_encoder,
                 textual_inversion_manager=ti_manager,
                 dtype_for_device_getter=TorchDevice.choose_torch_dtype,
@@ -203,7 +200,7 @@ class SDXLPromptInvocationBase:
 
             if context.config.get().log_tokenization:
                 # TODO: better logging for and syntax
-                log_tokenization_for_conjunction(conjunction, tokenizer)
+                log_tokenization_for_conjunction(conjunction, patched_tokenizer)
 
             # TODO: ask for optimizations? to not run text_encoder twice
             c, _options = compel.build_conditioning_tensor_for_conjunction(conjunction)

invokeai/app/invocations/latent.py

@@ -930,9 +930,9 @@ class DenoiseLatentsInvocation(BaseInvocation):
             assert isinstance(unet_info.model, UNet2DConditionModel)
             with (
                 ExitStack() as exit_stack,
-                ModelPatcher.apply_freeu(unet_info.model, self.unet.freeu_config),
-                set_seamless(unet_info.model, self.unet.seamless_axes),  # FIXME
                 unet_info as unet,
+                ModelPatcher.apply_freeu(unet, self.unet.freeu_config),
+                set_seamless(unet, self.unet.seamless_axes),  # FIXME
                 # Apply the LoRA after unet has been moved to its target device for faster patching.
                 ModelPatcher.apply_lora_unet(unet, _lora_loader()),
             ):

invokeai/app/services/events/events_base.py

@@ -14,7 +14,6 @@ from invokeai.app.services.events.events_common import (
     DownloadProgressEvent,
     DownloadStartedEvent,
     EventBase,
-    ExtraData,
     InvocationCompleteEvent,
     InvocationDenoiseProgressEvent,
     InvocationErrorEvent,
@@ -29,9 +28,6 @@ from invokeai.app.services.events.events_common import (
     ModelLoadStartedEvent,
     QueueClearedEvent,
     QueueItemStatusChangedEvent,
-    SessionCanceledEvent,
-    SessionCompleteEvent,
-    SessionStartedEvent,
 )
 from invokeai.backend.stable_diffusion.diffusers_pipeline import PipelineIntermediateState
 
@@ -58,11 +54,9 @@ class EventServiceBase:
 
     # region: Invocation
 
-    def emit_invocation_started(
-        self, queue_item: "SessionQueueItem", invocation: "BaseInvocation", extra: Optional[ExtraData] = None
-    ) -> None:
+    def emit_invocation_started(self, queue_item: "SessionQueueItem", invocation: "BaseInvocation") -> None:
         """Emitted when an invocation is started"""
-        self.dispatch(InvocationStartedEvent.build(queue_item, invocation, extra))
+        self.dispatch(InvocationStartedEvent.build(queue_item, invocation))
 
     def emit_invocation_denoise_progress(
         self,
@@ -70,184 +64,132 @@ class EventServiceBase:
         invocation: "BaseInvocation",
         intermediate_state: PipelineIntermediateState,
         progress_image: "ProgressImage",
-        extra: Optional[ExtraData] = None,
     ) -> None:
         """Emitted at each step during denoising of an invocation."""
-        self.dispatch(
-            InvocationDenoiseProgressEvent.build(queue_item, invocation, intermediate_state, progress_image, extra)
-        )
+        self.dispatch(InvocationDenoiseProgressEvent.build(queue_item, invocation, intermediate_state, progress_image))
 
     def emit_invocation_complete(
-        self,
-        queue_item: "SessionQueueItem",
-        invocation: "BaseInvocation",
-        output: "BaseInvocationOutput",
-        extra: Optional[ExtraData] = None,
+        self, queue_item: "SessionQueueItem", invocation: "BaseInvocation", output: "BaseInvocationOutput"
     ) -> None:
         """Emitted when an invocation is complete"""
-        self.dispatch(InvocationCompleteEvent.build(queue_item, invocation, output, extra))
+        self.dispatch(InvocationCompleteEvent.build(queue_item, invocation, output))
 
     def emit_invocation_error(
         self,
         queue_item: "SessionQueueItem",
         invocation: "BaseInvocation",
         error_type: str,
-        error: str,
-        extra: Optional[ExtraData] = None,
+        error_message: str,
+        error_traceback: str,
     ) -> None:
         """Emitted when an invocation encounters an error"""
-        self.dispatch(InvocationErrorEvent.build(queue_item, invocation, error_type, error, extra))
-
-    # endregion
-
-    # region Session
-
-    def emit_session_started(self, queue_item: "SessionQueueItem", extra: Optional[ExtraData] = None) -> None:
-        """Emitted when a session has started"""
-        self.dispatch(SessionStartedEvent.build(queue_item, extra))
-
-    def emit_session_complete(self, queue_item: "SessionQueueItem", extra: Optional[ExtraData] = None) -> None:
-        """Emitted when a session has completed all invocations"""
-        self.dispatch(SessionCompleteEvent.build(queue_item, extra))
-
-    def emit_session_canceled(self, queue_item: "SessionQueueItem", extra: Optional[ExtraData] = None) -> None:
-        """Emitted when a session is canceled"""
-        self.dispatch(SessionCanceledEvent.build(queue_item, extra))
+        self.dispatch(InvocationErrorEvent.build(queue_item, invocation, error_type, error_message, error_traceback))
 
     # endregion
 
     # region Queue
 
     def emit_queue_item_status_changed(
-        self,
-        queue_item: "SessionQueueItem",
-        batch_status: "BatchStatus",
-        queue_status: "SessionQueueStatus",
-        extra: Optional[ExtraData] = None,
+        self, queue_item: "SessionQueueItem", batch_status: "BatchStatus", queue_status: "SessionQueueStatus"
     ) -> None:
         """Emitted when a queue item's status changes"""
-        self.dispatch(QueueItemStatusChangedEvent.build(queue_item, batch_status, queue_status, extra))
+        self.dispatch(QueueItemStatusChangedEvent.build(queue_item, batch_status, queue_status))
 
-    def emit_batch_enqueued(self, enqueue_result: "EnqueueBatchResult", extra: Optional[ExtraData] = None) -> None:
+    def emit_batch_enqueued(self, enqueue_result: "EnqueueBatchResult") -> None:
         """Emitted when a batch is enqueued"""
-        self.dispatch(BatchEnqueuedEvent.build(enqueue_result, extra))
+        self.dispatch(BatchEnqueuedEvent.build(enqueue_result))
 
-    def emit_queue_cleared(self, queue_id: str, extra: Optional[ExtraData] = None) -> None:
+    def emit_queue_cleared(self, queue_id: str) -> None:
         """Emitted when a queue is cleared"""
-        self.dispatch(QueueClearedEvent.build(queue_id, extra))
+        self.dispatch(QueueClearedEvent.build(queue_id))
 
     # endregion
 
     # region Download
 
-    def emit_download_started(self, job: "DownloadJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_download_started(self, job: "DownloadJob") -> None:
         """Emitted when a download is started"""
-        self.dispatch(DownloadStartedEvent.build(job, extra))
+        self.dispatch(DownloadStartedEvent.build(job))
 
-    def emit_download_progress(self, job: "DownloadJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_download_progress(self, job: "DownloadJob") -> None:
         """Emitted at intervals during a download"""
-        self.dispatch(DownloadProgressEvent.build(job, extra))
+        self.dispatch(DownloadProgressEvent.build(job))
 
-    def emit_download_complete(self, job: "DownloadJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_download_complete(self, job: "DownloadJob") -> None:
         """Emitted when a download is completed"""
-        self.dispatch(DownloadCompleteEvent.build(job, extra))
+        self.dispatch(DownloadCompleteEvent.build(job))
 
-    def emit_download_cancelled(self, job: "DownloadJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_download_cancelled(self, job: "DownloadJob") -> None:
         """Emitted when a download is cancelled"""
-        self.dispatch(DownloadCancelledEvent.build(job, extra))
+        self.dispatch(DownloadCancelledEvent.build(job))
 
-    def emit_download_error(self, job: "DownloadJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_download_error(self, job: "DownloadJob") -> None:
         """Emitted when a download encounters an error"""
-        self.dispatch(DownloadErrorEvent.build(job, extra))
+        self.dispatch(DownloadErrorEvent.build(job))
 
     # endregion
 
     # region Model loading
 
-    def emit_model_load_started(
-        self,
-        config: "AnyModelConfig",
-        submodel_type: Optional["SubModelType"] = None,
-        extra: Optional[ExtraData] = None,
-    ) -> None:
+    def emit_model_load_started(self, config: "AnyModelConfig", submodel_type: Optional["SubModelType"] = None) -> None:
         """Emitted when a model load is started."""
-        self.dispatch(ModelLoadStartedEvent.build(config, submodel_type, extra))
+        self.dispatch(ModelLoadStartedEvent.build(config, submodel_type))
 
     def emit_model_load_complete(
-        self,
-        config: "AnyModelConfig",
-        submodel_type: Optional["SubModelType"] = None,
-        extra: Optional[ExtraData] = None,
+        self, config: "AnyModelConfig", submodel_type: Optional["SubModelType"] = None
     ) -> None:
         """Emitted when a model load is complete."""
-        self.dispatch(ModelLoadCompleteEvent.build(config, submodel_type, extra))
+        self.dispatch(ModelLoadCompleteEvent.build(config, submodel_type))
 
     # endregion
 
     # region Model install
 
-    def emit_model_install_download_progress(self, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_model_install_download_progress(self, job: "ModelInstallJob") -> None:
         """Emitted at intervals while the install job is in progress (remote models only)."""
-        self.dispatch(ModelInstallDownloadProgressEvent.build(job, extra))
+        self.dispatch(ModelInstallDownloadProgressEvent.build(job))
 
-    def emit_model_install_downloads_complete(self, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> None:
-        self.dispatch(ModelInstallDownloadsCompleteEvent.build(job, extra))
+    def emit_model_install_downloads_complete(self, job: "ModelInstallJob") -> None:
+        self.dispatch(ModelInstallDownloadsCompleteEvent.build(job))
 
-    def emit_model_install_started(self, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_model_install_started(self, job: "ModelInstallJob") -> None:
         """Emitted once when an install job is started (after any download)."""
-        self.dispatch(ModelInstallStartedEvent.build(job, extra))
+        self.dispatch(ModelInstallStartedEvent.build(job))
 
-    def emit_model_install_complete(self, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_model_install_complete(self, job: "ModelInstallJob") -> None:
         """Emitted when an install job is completed successfully."""
-        self.dispatch(ModelInstallCompleteEvent.build(job, extra))
+        self.dispatch(ModelInstallCompleteEvent.build(job))
 
-    def emit_model_install_cancelled(self, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_model_install_cancelled(self, job: "ModelInstallJob") -> None:
         """Emitted when an install job is cancelled."""
-        self.dispatch(ModelInstallCancelledEvent.build(job, extra))
+        self.dispatch(ModelInstallCancelledEvent.build(job))
 
-    def emit_model_install_error(self, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> None:
+    def emit_model_install_error(self, job: "ModelInstallJob") -> None:
         """Emitted when an install job encounters an exception."""
-        self.dispatch(ModelInstallErrorEvent.build(job, extra))
+        self.dispatch(ModelInstallErrorEvent.build(job))
 
     # endregion
 
     # region Bulk image download
 
     def emit_bulk_download_started(
-        self,
-        bulk_download_id: str,
-        bulk_download_item_id: str,
-        bulk_download_item_name: str,
-        extra: Optional[ExtraData] = None,
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> None:
         """Emitted when a bulk image download is started"""
-        self.dispatch(
-            BulkDownloadStartedEvent.build(bulk_download_id, bulk_download_item_id, bulk_download_item_name, extra)
-        )
+        self.dispatch(BulkDownloadStartedEvent.build(bulk_download_id, bulk_download_item_id, bulk_download_item_name))
 
     def emit_bulk_download_complete(
-        self,
-        bulk_download_id: str,
-        bulk_download_item_id: str,
-        bulk_download_item_name: str,
-        extra: Optional[ExtraData] = None,
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> None:
         """Emitted when a bulk image download is complete"""
-        self.dispatch(
-            BulkDownloadCompleteEvent.build(bulk_download_id, bulk_download_item_id, bulk_download_item_name, extra)
-        )
+        self.dispatch(BulkDownloadCompleteEvent.build(bulk_download_id, bulk_download_item_id, bulk_download_item_name))
 
     def emit_bulk_download_error(
-        self,
-        bulk_download_id: str,
-        bulk_download_item_id: str,
-        bulk_download_item_name: str,
-        error: str,
-        extra: Optional[ExtraData] = None,
+        self, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str, error: str
     ) -> None:
         """Emitted when a bulk image download has an error"""
         self.dispatch(
-            BulkDownloadErrorEvent.build(bulk_download_id, bulk_download_item_id, bulk_download_item_name, error, extra)
+            BulkDownloadErrorEvent.build(bulk_download_id, bulk_download_item_id, bulk_download_item_name, error)
         )
 
     # endregion

invokeai/app/services/events/events_common.py

@@ -1,8 +1,9 @@
 from math import floor
-from typing import TYPE_CHECKING, Any, Coroutine, Optional, Protocol, TypeAlias, TypeVar
+from typing import TYPE_CHECKING, Any, ClassVar, Coroutine, Generic, Optional, Protocol, TypeAlias, TypeVar
 
 from fastapi_events.handlers.local import local_handler
-from pydantic import BaseModel, ConfigDict, Field, SerializeAsAny
+from fastapi_events.registry.payload_schema import registry as payload_schema
+from pydantic import BaseModel, ConfigDict, Field, SerializeAsAny, field_validator
 
 from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput
 from invokeai.app.services.session_processor.session_processor_common import ProgressImage
@@ -22,9 +23,6 @@ if TYPE_CHECKING:
     from invokeai.app.services.model_install.model_install_common import ModelInstallJob
 
 
-ExtraData: TypeAlias = dict[str, Any]
-
-
 class EventBase(BaseModel):
     """Base class for all events. All events must inherit from this class.
 
@@ -35,8 +33,8 @@ class EventBase(BaseModel):
     A timestamp is automatically added to the event when it is created.
     """
 
+    __event_name__: ClassVar[str]
     timestamp: int = Field(description="The timestamp of the event", default_factory=get_timestamp)
-    extra: Optional[ExtraData] = Field(default=None, description="Extra data to include with the event")
 
     model_config = ConfigDict(json_schema_serialization_defaults_required=True)
 
@@ -54,7 +52,7 @@ class EventBase(BaseModel):
         return event_subclasses
 
 
-TEvent = TypeVar("TEvent", bound=EventBase)
+TEvent = TypeVar("TEvent", bound=EventBase, contravariant=True)
 
 FastAPIEvent: TypeAlias = tuple[str, TEvent]
 """
@@ -63,16 +61,17 @@ Provide a generic type to `TEvent` to specify the payload type.
 """
 
 
-class FastAPIEventFunc(Protocol):
-    def __call__(self, event: FastAPIEvent[Any]) -> Optional[Coroutine[Any, Any, None]]: ...
+class FastAPIEventFunc(Protocol, Generic[TEvent]):
+    def __call__(self, event: FastAPIEvent[TEvent]) -> Optional[Coroutine[Any, Any, None]]: ...
 
 
-def register_events(events: set[type[TEvent]], func: FastAPIEventFunc) -> None:
-    """Register a function to handle a list of events.
+def register_events(events: set[type[TEvent]] | type[TEvent], func: FastAPIEventFunc[TEvent]) -> None:
+    """Register a function to handle specific events.
 
-    :param events: A list of event classes to handle
+    :param events: An event or set of events to handle
     :param func: The function to handle the events
     """
+    events = events if isinstance(events, set) else {events}
     for event in events:
         assert hasattr(event, "__event_name__")
         local_handler.register(event_name=event.__event_name__, _func=func)  # pyright: ignore [reportUnknownMemberType, reportUnknownArgumentType, reportAttributeAccessIssue]
@@ -91,45 +90,45 @@ class QueueItemEventBase(QueueEventBase):
     batch_id: str = Field(description="The ID of the queue batch")
 
 
-class SessionEventBase(QueueItemEventBase):
-    """Base class for session (aka graph execution state) events"""
-
-    session_id: str = Field(description="The ID of the session (aka graph execution state)")
-
-
-class InvocationEventBase(SessionEventBase):
+class InvocationEventBase(QueueItemEventBase):
     """Base class for invocation events"""
 
+    session_id: str = Field(description="The ID of the session (aka graph execution state)")
     queue_id: str = Field(description="The ID of the queue")
     item_id: int = Field(description="The ID of the queue item")
     batch_id: str = Field(description="The ID of the queue batch")
     session_id: str = Field(description="The ID of the session (aka graph execution state)")
-    invocation_id: str = Field(description="The ID of the invocation")
+    invocation: SerializeAsAny[BaseInvocation] = Field(description="The ID of the invocation")
     invocation_source_id: str = Field(description="The ID of the prepared invocation's source node")
-    invocation_type: str = Field(description="The type of invocation")
+
+    @field_validator("invocation", mode="plain")
+    @classmethod
+    def validate_invocation(cls, v: Any):
+        """Validates the invocation using the dynamic type adapter."""
+
+        invocation = BaseInvocation.get_typeadapter().validate_python(v)
+        return invocation
 
 
+@payload_schema.register
 class InvocationStartedEvent(InvocationEventBase):
     """Event model for invocation_started"""
 
     __event_name__ = "invocation_started"
 
     @classmethod
-    def build(
-        cls, queue_item: SessionQueueItem, invocation: BaseInvocation, extra: Optional[ExtraData] = None
-    ) -> "InvocationStartedEvent":
+    def build(cls, queue_item: SessionQueueItem, invocation: BaseInvocation) -> "InvocationStartedEvent":
         return cls(
             queue_id=queue_item.queue_id,
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             session_id=queue_item.session_id,
-            invocation_id=invocation.id,
+            invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
-            invocation_type=invocation.get_type(),
-            extra=extra,
         )
 
 
+@payload_schema.register
 class InvocationDenoiseProgressEvent(InvocationEventBase):
     """Event model for invocation_denoise_progress"""
 
@@ -148,7 +147,6 @@ class InvocationDenoiseProgressEvent(InvocationEventBase):
         invocation: BaseInvocation,
         intermediate_state: PipelineIntermediateState,
         progress_image: ProgressImage,
-        extra: Optional[ExtraData] = None,
     ) -> "InvocationDenoiseProgressEvent":
         step = intermediate_state.step
         total_steps = intermediate_state.total_steps
@@ -158,15 +156,13 @@ class InvocationDenoiseProgressEvent(InvocationEventBase):
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             session_id=queue_item.session_id,
-            invocation_id=invocation.id,
+            invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
-            invocation_type=invocation.get_type(),
             progress_image=progress_image,
             step=step,
             total_steps=total_steps,
             order=order,
             percentage=cls.calc_percentage(step, total_steps, order),
-            extra=extra,
         )
 
     @staticmethod
@@ -180,6 +176,7 @@ class InvocationDenoiseProgressEvent(InvocationEventBase):
         return (step + 1 + 1) / (total_steps + 1)
 
 
+@payload_schema.register
 class InvocationCompleteEvent(InvocationEventBase):
     """Event model for invocation_complete"""
 
@@ -187,34 +184,40 @@ class InvocationCompleteEvent(InvocationEventBase):
 
     result: SerializeAsAny[BaseInvocationOutput] = Field(description="The result of the invocation")
 
+    @field_validator("result", mode="plain")
+    @classmethod
+    def validate_results(cls, v: Any):
+        """Validates the invocation result using the dynamic type adapter."""
+
+        result = BaseInvocationOutput.get_typeadapter().validate_python(v)
+        return result
+
     @classmethod
     def build(
-        cls,
-        queue_item: SessionQueueItem,
-        invocation: BaseInvocation,
-        result: BaseInvocationOutput,
-        extra: Optional[ExtraData] = None,
+        cls, queue_item: SessionQueueItem, invocation: BaseInvocation, result: BaseInvocationOutput
     ) -> "InvocationCompleteEvent":
         return cls(
             queue_id=queue_item.queue_id,
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             session_id=queue_item.session_id,
-            invocation_id=invocation.id,
+            invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
-            invocation_type=invocation.get_type(),
             result=result,
-            extra=extra,
         )
 
 
+@payload_schema.register
 class InvocationErrorEvent(InvocationEventBase):
     """Event model for invocation_error"""
 
     __event_name__ = "invocation_error"
 
-    error_type: str = Field(description="The type of error")
-    error: str = Field(description="The error message")
+    error_type: str = Field(description="The error type")
+    error_message: str = Field(description="The error message")
+    error_traceback: str = Field(description="The error traceback")
+    user_id: Optional[str] = Field(default=None, description="The ID of the user who created the invocation")
+    project_id: Optional[str] = Field(default=None, description="The ID of the user who created the invocation")
 
     @classmethod
     def build(
@@ -222,109 +225,65 @@ class InvocationErrorEvent(InvocationEventBase):
         queue_item: SessionQueueItem,
         invocation: BaseInvocation,
         error_type: str,
-        error: str,
-        extra: Optional[ExtraData] = None,
+        error_message: str,
+        error_traceback: str,
     ) -> "InvocationErrorEvent":
         return cls(
             queue_id=queue_item.queue_id,
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
             session_id=queue_item.session_id,
-            invocation_id=invocation.id,
+            invocation=invocation,
             invocation_source_id=queue_item.session.prepared_source_mapping[invocation.id],
-            invocation_type=invocation.get_type(),
             error_type=error_type,
-            error=error,
-            extra=extra,
-        )
-
-
-class SessionStartedEvent(SessionEventBase):
-    """Event model for session_started"""
-
-    __event_name__ = "session_started"
-
-    @classmethod
-    def build(cls, queue_item: SessionQueueItem, extra: Optional[ExtraData] = None) -> "SessionStartedEvent":
-        return cls(
-            queue_id=queue_item.queue_id,
-            item_id=queue_item.item_id,
-            batch_id=queue_item.batch_id,
-            session_id=queue_item.session_id,
-            extra=extra,
-        )
-
-
-class SessionCompleteEvent(SessionEventBase):
-    """Event model for session_complete"""
-
-    __event_name__ = "session_complete"
-
-    @classmethod
-    def build(cls, queue_item: SessionQueueItem, extra: Optional[ExtraData] = None) -> "SessionCompleteEvent":
-        return cls(
-            queue_id=queue_item.queue_id,
-            item_id=queue_item.item_id,
-            batch_id=queue_item.batch_id,
-            session_id=queue_item.session_id,
-            extra=extra,
-        )
-
-
-class SessionCanceledEvent(SessionEventBase):
-    """Event model for session_canceled"""
-
-    __event_name__ = "session_canceled"
-
-    @classmethod
-    def build(cls, queue_item: SessionQueueItem, extra: Optional[ExtraData] = None) -> "SessionCanceledEvent":
-        return cls(
-            queue_id=queue_item.queue_id,
-            item_id=queue_item.item_id,
-            batch_id=queue_item.batch_id,
-            session_id=queue_item.session_id,
-            extra=extra,
+            error_message=error_message,
+            error_traceback=error_traceback,
+            user_id=getattr(queue_item, "user_id", None),
+            project_id=getattr(queue_item, "project_id", None),
         )
 
 
+@payload_schema.register
 class QueueItemStatusChangedEvent(QueueItemEventBase):
     """Event model for queue_item_status_changed"""
 
     __event_name__ = "queue_item_status_changed"
 
     status: QUEUE_ITEM_STATUS = Field(description="The new status of the queue item")
-    error: Optional[str] = Field(default=None, description="The error message, if any")
+    error_type: Optional[str] = Field(default=None, description="The error type, if any")
+    error_message: Optional[str] = Field(default=None, description="The error message, if any")
+    error_traceback: Optional[str] = Field(default=None, description="The error traceback, if any")
     created_at: Optional[str] = Field(default=None, description="The timestamp when the queue item was created")
     updated_at: Optional[str] = Field(default=None, description="The timestamp when the queue item was last updated")
     started_at: Optional[str] = Field(default=None, description="The timestamp when the queue item was started")
     completed_at: Optional[str] = Field(default=None, description="The timestamp when the queue item was completed")
     batch_status: BatchStatus = Field(description="The status of the batch")
     queue_status: SessionQueueStatus = Field(description="The status of the queue")
+    session_id: str = Field(description="The ID of the session (aka graph execution state)")
 
     @classmethod
     def build(
-        cls,
-        queue_item: SessionQueueItem,
-        batch_status: BatchStatus,
-        queue_status: SessionQueueStatus,
-        extra: Optional[ExtraData] = None,
+        cls, queue_item: SessionQueueItem, batch_status: BatchStatus, queue_status: SessionQueueStatus
     ) -> "QueueItemStatusChangedEvent":
         return cls(
             queue_id=queue_item.queue_id,
             item_id=queue_item.item_id,
             batch_id=queue_item.batch_id,
+            session_id=queue_item.session_id,
             status=queue_item.status,
-            error=queue_item.error,
+            error_type=queue_item.error_type,
+            error_message=queue_item.error_message,
+            error_traceback=queue_item.error_traceback,
             created_at=str(queue_item.created_at) if queue_item.created_at else None,
             updated_at=str(queue_item.updated_at) if queue_item.updated_at else None,
             started_at=str(queue_item.started_at) if queue_item.started_at else None,
             completed_at=str(queue_item.completed_at) if queue_item.completed_at else None,
             batch_status=batch_status,
             queue_status=queue_status,
-            extra=extra,
         )
 
 
+@payload_schema.register
 class BatchEnqueuedEvent(QueueEventBase):
     """Event model for batch_enqueued"""
 
@@ -338,28 +297,25 @@ class BatchEnqueuedEvent(QueueEventBase):
     priority: int = Field(description="The priority of the batch")
 
     @classmethod
-    def build(cls, enqueue_result: EnqueueBatchResult, extra: Optional[ExtraData] = None) -> "BatchEnqueuedEvent":
+    def build(cls, enqueue_result: EnqueueBatchResult) -> "BatchEnqueuedEvent":
         return cls(
             queue_id=enqueue_result.queue_id,
             batch_id=enqueue_result.batch.batch_id,
             enqueued=enqueue_result.enqueued,
             requested=enqueue_result.requested,
             priority=enqueue_result.priority,
-            extra=extra,
         )
 
 
+@payload_schema.register
 class QueueClearedEvent(QueueEventBase):
     """Event model for queue_cleared"""
 
     __event_name__ = "queue_cleared"
 
     @classmethod
-    def build(cls, queue_id: str, extra: Optional[ExtraData] = None) -> "QueueClearedEvent":
-        return cls(
-            queue_id=queue_id,
-            extra=extra,
-        )
+    def build(cls, queue_id: str) -> "QueueClearedEvent":
+        return cls(queue_id=queue_id)
 
 
 class DownloadEventBase(EventBase):
@@ -368,6 +324,7 @@ class DownloadEventBase(EventBase):
     source: str = Field(description="The source of the download")
 
 
+@payload_schema.register
 class DownloadStartedEvent(DownloadEventBase):
     """Event model for download_started"""
 
@@ -376,15 +333,12 @@ class DownloadStartedEvent(DownloadEventBase):
     download_path: str = Field(description="The local path where the download is saved")
 
     @classmethod
-    def build(cls, job: "DownloadJob", extra: Optional[ExtraData] = None) -> "DownloadStartedEvent":
+    def build(cls, job: "DownloadJob") -> "DownloadStartedEvent":
         assert job.download_path
-        return cls(
-            source=str(job.source),
-            download_path=job.download_path.as_posix(),
-            extra=extra,
-        )
+        return cls(source=str(job.source), download_path=job.download_path.as_posix())
 
 
+@payload_schema.register
 class DownloadProgressEvent(DownloadEventBase):
     """Event model for download_progress"""
 
@@ -395,17 +349,17 @@ class DownloadProgressEvent(DownloadEventBase):
     total_bytes: int = Field(description="The total number of bytes to be downloaded")
 
     @classmethod
-    def build(cls, job: "DownloadJob", extra: Optional[ExtraData] = None) -> "DownloadProgressEvent":
+    def build(cls, job: "DownloadJob") -> "DownloadProgressEvent":
         assert job.download_path
         return cls(
             source=str(job.source),
             download_path=job.download_path.as_posix(),
             current_bytes=job.bytes,
             total_bytes=job.total_bytes,
-            extra=extra,
         )
 
 
+@payload_schema.register
 class DownloadCompleteEvent(DownloadEventBase):
     """Event model for download_complete"""
 
@@ -415,29 +369,23 @@ class DownloadCompleteEvent(DownloadEventBase):
     total_bytes: int = Field(description="The total number of bytes downloaded")
 
     @classmethod
-    def build(cls, job: "DownloadJob", extra: Optional[ExtraData] = None) -> "DownloadCompleteEvent":
+    def build(cls, job: "DownloadJob") -> "DownloadCompleteEvent":
         assert job.download_path
-        return cls(
-            source=str(job.source),
-            download_path=job.download_path.as_posix(),
-            total_bytes=job.total_bytes,
-            extra=extra,
-        )
+        return cls(source=str(job.source), download_path=job.download_path.as_posix(), total_bytes=job.total_bytes)
 
 
+@payload_schema.register
 class DownloadCancelledEvent(DownloadEventBase):
     """Event model for download_cancelled"""
 
     __event_name__ = "download_cancelled"
 
     @classmethod
-    def build(cls, job: "DownloadJob", extra: Optional[ExtraData] = None) -> "DownloadCancelledEvent":
-        return cls(
-            source=str(job.source),
-            extra=extra,
-        )
+    def build(cls, job: "DownloadJob") -> "DownloadCancelledEvent":
+        return cls(source=str(job.source))
 
 
+@payload_schema.register
 class DownloadErrorEvent(DownloadEventBase):
     """Event model for download_error"""
 
@@ -447,21 +395,17 @@ class DownloadErrorEvent(DownloadEventBase):
     error: str = Field(description="The error message")
 
     @classmethod
-    def build(cls, job: "DownloadJob", extra: Optional[ExtraData] = None) -> "DownloadErrorEvent":
+    def build(cls, job: "DownloadJob") -> "DownloadErrorEvent":
         assert job.error_type
         assert job.error
-        return cls(
-            source=str(job.source),
-            error_type=job.error_type,
-            error=job.error,
-            extra=extra,
-        )
+        return cls(source=str(job.source), error_type=job.error_type, error=job.error)
 
 
 class ModelEventBase(EventBase):
     """Base class for events associated with a model"""
 
 
+@payload_schema.register
 class ModelLoadStartedEvent(ModelEventBase):
     """Event model for model_load_started"""
 
@@ -471,16 +415,11 @@ class ModelLoadStartedEvent(ModelEventBase):
     submodel_type: Optional[SubModelType] = Field(default=None, description="The submodel type, if any")
 
     @classmethod
-    def build(
-        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None, extra: Optional[ExtraData] = None
-    ) -> "ModelLoadStartedEvent":
-        return cls(
-            config=config,
-            submodel_type=submodel_type,
-            extra=extra,
-        )
+    def build(cls, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> "ModelLoadStartedEvent":
+        return cls(config=config, submodel_type=submodel_type)
 
 
+@payload_schema.register
 class ModelLoadCompleteEvent(ModelEventBase):
     """Event model for model_load_complete"""
 
@@ -490,16 +429,11 @@ class ModelLoadCompleteEvent(ModelEventBase):
     submodel_type: Optional[SubModelType] = Field(default=None, description="The submodel type, if any")
 
     @classmethod
-    def build(
-        cls, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None, extra: Optional[ExtraData] = None
-    ) -> "ModelLoadCompleteEvent":
-        return cls(
-            config=config,
-            submodel_type=submodel_type,
-            extra=extra,
-        )
+    def build(cls, config: AnyModelConfig, submodel_type: Optional[SubModelType] = None) -> "ModelLoadCompleteEvent":
+        return cls(config=config, submodel_type=submodel_type)
 
 
+@payload_schema.register
 class ModelInstallDownloadProgressEvent(ModelEventBase):
     """Event model for model_install_download_progress"""
 
@@ -515,7 +449,7 @@ class ModelInstallDownloadProgressEvent(ModelEventBase):
     )
 
     @classmethod
-    def build(cls, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> "ModelInstallDownloadProgressEvent":
+    def build(cls, job: "ModelInstallJob") -> "ModelInstallDownloadProgressEvent":
         parts: list[dict[str, str | int]] = [
             {
                 "url": str(x.source),
@@ -532,10 +466,10 @@ class ModelInstallDownloadProgressEvent(ModelEventBase):
             parts=parts,
             bytes=job.bytes,
             total_bytes=job.total_bytes,
-            extra=extra,
         )
 
 
+@payload_schema.register
 class ModelInstallDownloadsCompleteEvent(ModelEventBase):
     """Emitted once when an install job becomes active."""
 
@@ -545,14 +479,11 @@ class ModelInstallDownloadsCompleteEvent(ModelEventBase):
     source: str = Field(description="Source of the model; local path, repo_id or url")
 
     @classmethod
-    def build(cls, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> "ModelInstallDownloadsCompleteEvent":
-        return cls(
-            id=job.id,
-            source=str(job.source),
-            extra=extra,
-        )
+    def build(cls, job: "ModelInstallJob") -> "ModelInstallDownloadsCompleteEvent":
+        return cls(id=job.id, source=str(job.source))
 
 
+@payload_schema.register
 class ModelInstallStartedEvent(ModelEventBase):
     """Event model for model_install_started"""
 
@@ -562,14 +493,11 @@ class ModelInstallStartedEvent(ModelEventBase):
     source: str = Field(description="Source of the model; local path, repo_id or url")
 
     @classmethod
-    def build(cls, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> "ModelInstallStartedEvent":
-        return cls(
-            id=job.id,
-            source=str(job.source),
-            extra=extra,
-        )
+    def build(cls, job: "ModelInstallJob") -> "ModelInstallStartedEvent":
+        return cls(id=job.id, source=str(job.source))
 
 
+@payload_schema.register
 class ModelInstallCompleteEvent(ModelEventBase):
     """Event model for model_install_complete"""
 
@@ -581,17 +509,12 @@ class ModelInstallCompleteEvent(ModelEventBase):
     total_bytes: Optional[int] = Field(description="Size of the model (may be None for installation of a local path)")
 
     @classmethod
-    def build(cls, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> "ModelInstallCompleteEvent":
+    def build(cls, job: "ModelInstallJob") -> "ModelInstallCompleteEvent":
         assert job.config_out is not None
-        return cls(
-            id=job.id,
-            source=str(job.source),
-            key=(job.config_out.key),
-            total_bytes=job.total_bytes,
-            extra=extra,
-        )
+        return cls(id=job.id, source=str(job.source), key=(job.config_out.key), total_bytes=job.total_bytes)
 
 
+@payload_schema.register
 class ModelInstallCancelledEvent(ModelEventBase):
     """Event model for model_install_cancelled"""
 
@@ -601,14 +524,11 @@ class ModelInstallCancelledEvent(ModelEventBase):
     source: str = Field(description="Source of the model; local path, repo_id or url")
 
     @classmethod
-    def build(cls, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> "ModelInstallCancelledEvent":
-        return cls(
-            id=job.id,
-            source=str(job.source),
-            extra=extra,
-        )
+    def build(cls, job: "ModelInstallJob") -> "ModelInstallCancelledEvent":
+        return cls(id=job.id, source=str(job.source))
 
 
+@payload_schema.register
 class ModelInstallErrorEvent(ModelEventBase):
     """Event model for model_install_error"""
 
@@ -620,16 +540,10 @@ class ModelInstallErrorEvent(ModelEventBase):
     error: str = Field(description="A text description of the exception")
 
     @classmethod
-    def build(cls, job: "ModelInstallJob", extra: Optional[ExtraData] = None) -> "ModelInstallErrorEvent":
+    def build(cls, job: "ModelInstallJob") -> "ModelInstallErrorEvent":
         assert job.error_type is not None
         assert job.error is not None
-        return cls(
-            id=job.id,
-            source=str(job.source),
-            error_type=job.error_type,
-            error=job.error,
-            extra=extra,
-        )
+        return cls(id=job.id, source=str(job.source), error_type=job.error_type, error=job.error)
 
 
 class BulkDownloadEventBase(EventBase):
@@ -640,6 +554,7 @@ class BulkDownloadEventBase(EventBase):
     bulk_download_item_name: str = Field(description="The name of the bulk image download item")
 
 
+@payload_schema.register
 class BulkDownloadStartedEvent(BulkDownloadEventBase):
     """Event model for bulk_download_started"""
 
@@ -647,20 +562,16 @@ class BulkDownloadStartedEvent(BulkDownloadEventBase):
 
     @classmethod
     def build(
-        cls,
-        bulk_download_id: str,
-        bulk_download_item_id: str,
-        bulk_download_item_name: str,
-        extra: Optional[ExtraData] = None,
+        cls, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> "BulkDownloadStartedEvent":
         return cls(
             bulk_download_id=bulk_download_id,
             bulk_download_item_id=bulk_download_item_id,
             bulk_download_item_name=bulk_download_item_name,
-            extra=extra,
         )
 
 
+@payload_schema.register
 class BulkDownloadCompleteEvent(BulkDownloadEventBase):
     """Event model for bulk_download_complete"""
 
@@ -668,20 +579,16 @@ class BulkDownloadCompleteEvent(BulkDownloadEventBase):
 
     @classmethod
     def build(
-        cls,
-        bulk_download_id: str,
-        bulk_download_item_id: str,
-        bulk_download_item_name: str,
-        extra: Optional[ExtraData] = None,
+        cls, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str
     ) -> "BulkDownloadCompleteEvent":
         return cls(
             bulk_download_id=bulk_download_id,
             bulk_download_item_id=bulk_download_item_id,
             bulk_download_item_name=bulk_download_item_name,
-            extra=extra,
         )
 
 
+@payload_schema.register
 class BulkDownloadErrorEvent(BulkDownloadEventBase):
     """Event model for bulk_download_error"""
 
@@ -691,17 +598,11 @@ class BulkDownloadErrorEvent(BulkDownloadEventBase):
 
     @classmethod
     def build(
-        cls,
-        bulk_download_id: str,
-        bulk_download_item_id: str,
-        bulk_download_item_name: str,
-        error: str,
-        extra: Optional[ExtraData] = None,
+        cls, bulk_download_id: str, bulk_download_item_id: str, bulk_download_item_name: str, error: str
     ) -> "BulkDownloadErrorEvent":
         return cls(
             bulk_download_id=bulk_download_id,
             bulk_download_item_id=bulk_download_item_id,
             bulk_download_item_name=bulk_download_item_name,
             error=error,
-            extra=extra,
         )

invokeai/app/services/events/events_fastapievents.py

@@ -36,6 +36,7 @@ class FastAPIEventService(EventServiceBase):
                 event = self._queue.get(block=False)
                 if not event:  # Probably stopping
                     continue
+                # Leave the payloads as live pydantic models
                 dispatch(event, middleware_id=self.event_handler_id, payload_schema_dump=False)
 
             except Empty:

invokeai/app/services/model_load/model_load_default.py

@@ -72,6 +72,6 @@ class ModelLoadService(ModelLoadServiceBase):
         ).load_model(model_config, submodel_type)
 
         if hasattr(self, "_invoker"):
-            self._invoker.services.events.emit_model_load_started(model_config, submodel_type)
+            self._invoker.services.events.emit_model_load_complete(model_config, submodel_type)
 
         return loaded_model

invokeai/app/services/session_processor/session_processor_base.py

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

invokeai/app/services/session_processor/session_processor_default.py

@@ -4,29 +4,325 @@ from threading import BoundedSemaphore, Thread
 from threading import Event as ThreadEvent
 from typing import Optional
 
-from invokeai.app.invocations.baseinvocation import BaseInvocation
+from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput
 from invokeai.app.services.events.events_common import (
     BatchEnqueuedEvent,
     FastAPIEvent,
     QueueClearedEvent,
-    QueueEventBase,
     QueueItemStatusChangedEvent,
-    SessionCanceledEvent,
     register_events,
 )
 from invokeai.app.services.invocation_stats.invocation_stats_common import GESStatsNotFoundError
+from invokeai.app.services.session_processor.session_processor_base import (
+    OnAfterRunNode,
+    OnAfterRunSession,
+    OnBeforeRunNode,
+    OnBeforeRunSession,
+    OnNodeError,
+    OnNonFatalProcessorError,
+)
 from invokeai.app.services.session_processor.session_processor_common import CanceledException
-from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem
+from invokeai.app.services.session_queue.session_queue_common import SessionQueueItem, SessionQueueItemNotFoundError
+from invokeai.app.services.shared.graph import NodeInputError
 from invokeai.app.services.shared.invocation_context import InvocationContextData, build_invocation_context
 from invokeai.app.util.profiler import Profiler
 
 from ..invoker import Invoker
-from .session_processor_base import SessionProcessorBase
+from .session_processor_base import InvocationServices, SessionProcessorBase, SessionRunnerBase
 from .session_processor_common import SessionProcessorStatus
 
 
+class DefaultSessionRunner(SessionRunnerBase):
+    """Processes a single session's invocations."""
+
+    def __init__(
+        self,
+        on_before_run_session_callbacks: Optional[list[OnBeforeRunSession]] = None,
+        on_before_run_node_callbacks: Optional[list[OnBeforeRunNode]] = None,
+        on_after_run_node_callbacks: Optional[list[OnAfterRunNode]] = None,
+        on_node_error_callbacks: Optional[list[OnNodeError]] = None,
+        on_after_run_session_callbacks: Optional[list[OnAfterRunSession]] = None,
+    ):
+        """
+        Args:
+            on_before_run_session_callbacks: Callbacks to run before the session starts.
+            on_before_run_node_callbacks: Callbacks to run before each node starts.
+            on_after_run_node_callbacks: Callbacks to run after each node completes.
+            on_node_error_callbacks: Callbacks to run when a node errors.
+            on_after_run_session_callbacks: Callbacks to run after the session completes.
+        """
+
+        self._on_before_run_session_callbacks = on_before_run_session_callbacks or []
+        self._on_before_run_node_callbacks = on_before_run_node_callbacks or []
+        self._on_after_run_node_callbacks = on_after_run_node_callbacks or []
+        self._on_node_error_callbacks = on_node_error_callbacks or []
+        self._on_after_run_session_callbacks = on_after_run_session_callbacks or []
+
+    def start(self, services: InvocationServices, cancel_event: ThreadEvent, profiler: Optional[Profiler] = None):
+        self._services = services
+        self._cancel_event = cancel_event
+        self._profiler = profiler
+
+    def _is_canceled(self) -> bool:
+        """Check if the cancel event is set. This is also passed to the invocation context builder and called during
+        denoising to check if the session has been canceled."""
+        return self._cancel_event.is_set()
+
+    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._is_canceled():
+                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.
+            # At this time, the queue item may be canceled, but the object itself here won't be updated yet. We must
+            # use the cancel event to check if the session is canceled.
+            if (
+                queue_item.session.is_complete()
+                or self._is_canceled()
+                or queue_item.status in ["failed", "canceled", "completed"]
+            ):
+                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,
+                    is_canceled=self._is_canceled,
+                )
+
+                # 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:
+            # A CanceledException is raised during the denoising step callback if the cancel event is set. We don't need
+            # to do any handling here, and no error should be set - just pass and the cancellation will be handled
+            # correctly in the next iteration of the session runner loop.
+            #
+            # See the comment in the processor's `_on_queue_item_status_changed()` method for more details on how we
+            # handle cancellation.
+            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:
+        """Called before a session is run.
+
+        - Start the profiler if profiling is enabled.
+        - Run any callbacks registered for this event.
+        """
+
+        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:
+        """Called after a session is run.
+
+        - Stop the profiler if profiling is enabled.
+        - Update the queue item's session object in the database.
+        - If not already canceled or failed, complete the queue item.
+        - Log and reset performance statistics.
+        - Run any callbacks registered for this event.
+        """
+
+        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)
+
+            # The queue item may have been canceled or failed while the session was running. We should only complete it
+            # if it is not already canceled or failed.
+            if queue_item.status not in ["canceled", "failed"]:
+                queue_item = self._services.session_queue.complete_queue_item(queue_item.item_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):
+        """Called before a node is run.
+
+        - Emits an invocation started event.
+        - Run any callbacks registered for this event.
+        """
+
+        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_item=queue_item, invocation=invocation)
+
+        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
+    ):
+        """Called after a node is run.
+
+        - Emits an invocation complete event.
+        - Run any callbacks registered for this event.
+        """
+
+        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(invocation=invocation, queue_item=queue_item, output=output)
+
+        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,
+    ):
+        """Called when a node errors. Node errors may occur when running or preparing the node..
+
+        - Set the node error on the session object.
+        - Log the error.
+        - Fail the queue item.
+        - Emits an invocation error event.
+        - Run any callbacks registered for this event.
+        """
+
+        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)
+
+        # Fail the queue item
+        queue_item = self._services.session_queue.set_queue_item_session(queue_item.item_id, queue_item.session)
+        queue_item = self._services.session_queue.fail_queue_item(
+            queue_item.item_id, error_type, error_message, error_traceback
+        )
+
+        # Send error event
+        self._services.events.emit_invocation_error(
+            queue_item=queue_item,
+            invocation=invocation,
+            error_type=error_type,
+            error_message=error_message,
+            error_traceback=error_traceback,
+        )
+
+        for callback in self._on_node_error_callbacks:
+            callback(
+                invocation=invocation,
+                queue_item=queue_item,
+                error_type=error_type,
+                error_message=error_message,
+                error_traceback=error_traceback,
+            )
+
+
 class DefaultSessionProcessor(SessionProcessorBase):
-    def start(self, invoker: Invoker, thread_limit: int = 1, polling_interval: int = 1) -> None:
+    def __init__(
+        self,
+        session_runner: Optional[SessionRunnerBase] = None,
+        on_non_fatal_processor_error_callbacks: Optional[list[OnNonFatalProcessorError]] = None,
+        thread_limit: int = 1,
+        polling_interval: int = 1,
+    ) -> None:
+        super().__init__()
+
+        self.session_runner = session_runner if session_runner else DefaultSessionRunner()
+        self._on_non_fatal_processor_error_callbacks = on_non_fatal_processor_error_callbacks or []
+        self._thread_limit = thread_limit
+        self._polling_interval = polling_interval
+
+    def start(self, invoker: Invoker) -> None:
         self._invoker: Invoker = invoker
         self._queue_item: Optional[SessionQueueItem] = None
         self._invocation: Optional[BaseInvocation] = None
@@ -36,9 +332,11 @@ class DefaultSessionProcessor(SessionProcessorBase):
         self._poll_now_event = ThreadEvent()
         self._cancel_event = ThreadEvent()
 
-        self._thread_limit = thread_limit
-        self._thread_semaphore = BoundedSemaphore(thread_limit)
-        self._polling_interval = polling_interval
+        register_events(QueueClearedEvent, self._on_queue_cleared)
+        register_events(BatchEnqueuedEvent, self._on_batch_enqueued)
+        register_events(QueueItemStatusChangedEvent, self._on_queue_item_status_changed)
+
+        self._thread_semaphore = BoundedSemaphore(self._thread_limit)
 
         # If profiling is enabled, create a profiler. The same profiler will be used for all sessions. Internally,
         # the profiler will create a new profile for each session.
@@ -52,8 +350,7 @@ class DefaultSessionProcessor(SessionProcessorBase):
             else None
         )
 
-        register_events({SessionCanceledEvent, QueueClearedEvent, BatchEnqueuedEvent}, self._on_queue_event)
-
+        self.session_runner.start(services=invoker.services, cancel_event=self._cancel_event, profiler=self._profiler)
         self._thread = Thread(
             name="session_processor",
             target=self._process,
@@ -72,25 +369,25 @@ class DefaultSessionProcessor(SessionProcessorBase):
     def _poll_now(self) -> None:
         self._poll_now_event.set()
 
-    async def _on_queue_event(self, event: FastAPIEvent[QueueEventBase]) -> None:
-        _event_name, payload = event
-        if (
-            isinstance(payload, SessionCanceledEvent)
-            and self._queue_item
-            and self._queue_item.item_id == payload.item_id
-        ):
+    async def _on_queue_cleared(self, event: FastAPIEvent[QueueClearedEvent]) -> None:
+        if self._queue_item and self._queue_item.queue_id == event[1].queue_id:
             self._cancel_event.set()
             self._poll_now()
-        elif (
-            isinstance(payload, QueueClearedEvent)
-            and self._queue_item
-            and self._queue_item.queue_id == payload.queue_id
-        ):
-            self._cancel_event.set()
-            self._poll_now()
-        elif isinstance(payload, BatchEnqueuedEvent):
-            self._poll_now()
-        elif isinstance(payload, QueueItemStatusChangedEvent) and payload.status in ("completed", "failed", "canceled"):
+
+    async def _on_batch_enqueued(self, event: FastAPIEvent[BatchEnqueuedEvent]) -> None:
+        self._poll_now()
+
+    async def _on_queue_item_status_changed(self, event: FastAPIEvent[QueueItemStatusChangedEvent]) -> None:
+        if self._queue_item and event[1].status in ["completed", "failed", "canceled"]:
+            # When the queue item is canceled via HTTP, the queue item status is set to `"canceled"` and this event is
+            # emitted. We need to respond to this event and stop graph execution. This is done by setting the cancel
+            # event, which the session runner checks between invocations. If set, the session runner loop is broken.
+            #
+            # Long-running nodes that cannot be interrupted easily present a challenge. `denoise_latents` is one such
+            # node, but it gets a step callback, called on each step of denoising. This callback checks if the queue item
+            # is canceled, and if it is, raises a `CanceledException` to stop execution immediately.
+            if event[1].status == "canceled":
+                self._cancel_event.set()
             self._poll_now()
 
     def resume(self) -> SessionProcessorStatus:
@@ -116,8 +413,8 @@ class DefaultSessionProcessor(SessionProcessorBase):
         resume_event: ThreadEvent,
         cancel_event: ThreadEvent,
     ):
-        # Outermost processor try block; any unhandled exception is a fatal processor error
         try:
+            # Any unhandled exception in this block is a fatal processor error and will stop the processor.
             self._thread_semaphore.acquire()
             stop_event.clear()
             resume_event.set()
@@ -125,8 +422,8 @@ 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()
 
@@ -139,140 +436,72 @@ class DefaultSessionProcessor(SessionProcessorBase):
                         poll_now_event.wait(self._polling_interval)
                         continue
 
-                    self._invoker.services.events.emit_session_started(self._queue_item)
                     self._invoker.services.logger.debug(f"Executing queue item {self._queue_item.item_id}")
                     cancel_event.clear()
 
-                    # If profiling is enabled, start the profiler
-                    if self._profiler is not None:
-                        self._profiler.start(profile_id=self._queue_item.session_id)
+                    # Run the graph
+                    self.session_runner.run(queue_item=self._queue_item)
 
-                    # Prepare invocations and take the first
-                    self._invocation = self._queue_item.session.next()
-
-                    # Loop over invocations until the session is complete or canceled
-                    while self._invocation is not None and not cancel_event.is_set():
-                        # get the source node id to provide to clients (the prepared node id is not as useful)
-                        source_invocation_id = self._queue_item.session.prepared_source_mapping[self._invocation.id]
-                        self._invoker.services.events.emit_invocation_started(self._queue_item, self._invocation)
-
-                        # 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)
-
-                                self._invoker.services.events.emit_invocation_complete(
-                                    self._queue_item, self._invocation, outputs
-                                )
-
-                        except KeyboardInterrupt:
-                            # TODO(MM2): I don't think this is ever raised...
-                            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)
-
-                            self._invoker.services.events.emit_invocation_error(
-                                queue_item=self._queue_item,
-                                invocation=self._invocation,
-                                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():
-                            self._invoker.services.session_queue.set_queue_item_session(
-                                self._queue_item.item_id, self._queue_item.session
-                            )
-                            self._invoker.services.events.emit_session_complete(self._queue_item)
-                            # If we are profiling, stop the profiler and dump the profile & stats
-                            if self._profiler:
-                                profile_path = self._profiler.stop()
-                                stats_path = profile_path.with_suffix(".json")
-                                self._invoker.services.performance_statistics.dump_stats(
-                                    graph_execution_state_id=self._queue_item.session.id, output_path=stats_path
-                                )
-                            # We'll get a GESStatsNotFoundError if we try to log stats for an untracked graph, but in the processor
-                            # we don't care about that - suppress the error.
-                            with suppress(GESStatsNotFoundError):
-                                self._invoker.services.performance_statistics.log_stats(self._queue_item.session.id)
-                                self._invoker.services.performance_statistics.reset_stats()
-
-                            # Set the invocation to None to prepare for the next session
-                            self._invocation = None
-                        else:
-                            # Prepare the next invocation
-                            self._invocation = self._queue_item.session.next()
-                    else:
-                        # The queue was empty, wait for next polling interval or event to try again
-                        self._invoker.services.logger.debug("Waiting for next polling interval or event")
-                        poll_now_event.wait(self._polling_interval)
-                        continue
-                except Exception:
-                    # Non-fatal error in processor
-                    self._invoker.services.logger.error(
-                        f"Non-fatal error in session processor:\n{traceback.format_exc()}"
+                except Exception as e:
+                    error_type = e.__class__.__name__
+                    error_message = str(e)
+                    error_traceback = traceback.format_exc()
+                    self._on_non_fatal_processor_error(
+                        queue_item=self._queue_item,
+                        error_type=error_type,
+                        error_message=error_message,
+                        error_traceback=error_traceback,
                     )
-                    # Cancel the queue item
-                    if self._queue_item is not None:
-                        self._invoker.services.session_queue.set_queue_item_session(
-                            self._queue_item.item_id, self._queue_item.session
-                        )
-                        self._invoker.services.session_queue.cancel_queue_item(
-                            self._queue_item.item_id, error=traceback.format_exc()
-                        )
-                    # Reset the invocation to None to prepare for the next session
-                    self._invocation = None
-                    # Immediately poll for next queue item
+                    # Wait for next polling interval or event to try again
                     poll_now_event.wait(self._polling_interval)
                     continue
-        except Exception:
+        except Exception as e:
             # Fatal error in processor, log and pass - we're done here
-            self._invoker.services.logger.error(f"Fatal Error in session processor:\n{traceback.format_exc()}")
+            error_type = e.__class__.__name__
+            error_message = str(e)
+            error_traceback = traceback.format_exc()
+            self._invoker.services.logger.error(f"Fatal Error in session processor {error_type}: {error_message}")
+            self._invoker.services.logger.error(error_traceback)
             pass
         finally:
             stop_event.clear()
             poll_now_event.clear()
             self._queue_item = None
             self._thread_semaphore.release()
+
+    def _on_non_fatal_processor_error(
+        self,
+        queue_item: Optional[SessionQueueItem],
+        error_type: str,
+        error_message: str,
+        error_traceback: str,
+    ) -> None:
+        """Called when a non-fatal error occurs in the processor.
+
+        - Log the error.
+        - If a queue item is provided, update the queue item with the completed session & fail it.
+        - Run any callbacks registered for this event.
+        """
+
+        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 & fail it
+            queue_item = self._invoker.services.session_queue.set_queue_item_session(
+                queue_item.item_id, queue_item.session
+            )
+            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

@@ -74,10 +74,22 @@ class SessionQueueBase(ABC):
         pass
 
     @abstractmethod
-    def cancel_queue_item(self, item_id: int, error: Optional[str] = None) -> SessionQueueItem:
+    def complete_queue_item(self, item_id: int) -> SessionQueueItem:
+        """Completes a session queue item"""
+        pass
+
+    @abstractmethod
+    def cancel_queue_item(self, item_id: int) -> SessionQueueItem:
         """Cancels a session queue item"""
         pass
 
+    @abstractmethod
+    def fail_queue_item(
+        self, item_id: int, error_type: str, error_message: str, error_traceback: str
+    ) -> SessionQueueItem:
+        """Fails a session queue item"""
+        pass
+
     @abstractmethod
     def cancel_by_batch_ids(self, queue_id: str, batch_ids: list[str]) -> CancelByBatchIDsResult:
         """Cancels all queue items with matching batch IDs"""

invokeai/app/services/session_queue/session_queue_common.py

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

invokeai/app/services/session_queue/session_queue_sqlite.py

@@ -2,13 +2,6 @@ import sqlite3
 import threading
 from typing import Optional, Union, cast
 
-from invokeai.app.services.events.events_common import (
-    FastAPIEvent,
-    InvocationErrorEvent,
-    SessionCanceledEvent,
-    SessionCompleteEvent,
-    register_events,
-)
 from invokeai.app.services.invoker import Invoker
 from invokeai.app.services.session_queue.session_queue_base import SessionQueueBase
 from invokeai.app.services.session_queue.session_queue_common import (
@@ -46,10 +39,6 @@ class SqliteSessionQueue(SessionQueueBase):
         self._set_in_progress_to_canceled()
         prune_result = self.prune(DEFAULT_QUEUE_ID)
 
-        register_events(events={InvocationErrorEvent}, func=self._handle_error_event)
-        register_events(events={SessionCompleteEvent}, func=self._handle_complete_event)
-        register_events(events={SessionCanceledEvent}, func=self._handle_cancel_event)
-
         if prune_result.deleted > 0:
             self.__invoker.services.logger.info(f"Pruned {prune_result.deleted} finished queue items")
 
@@ -59,36 +48,6 @@ class SqliteSessionQueue(SessionQueueBase):
         self.__conn = db.conn
         self.__cursor = self.__conn.cursor()
 
-    async def _handle_complete_event(self, event: FastAPIEvent[SessionCompleteEvent]) -> None:
-        try:
-            # When a queue item has an error, we get an error event, then a completed event.
-            # Mark the queue item completed only if it isn't already marked completed, e.g.
-            # by a previously-handled error event.
-            _event_name, payload = event
-
-            queue_item = self.get_queue_item(payload.item_id)
-            if queue_item.status not in ["completed", "failed", "canceled"]:
-                self._set_queue_item_status(item_id=payload.item_id, status="completed")
-        except SessionQueueItemNotFoundError:
-            pass
-
-    async def _handle_error_event(self, event: FastAPIEvent[InvocationErrorEvent]) -> None:
-        try:
-            _event_name, payload = event
-            # always set to failed if have an error, even if previously the item was marked completed or canceled
-            self._set_queue_item_status(item_id=payload.item_id, status="failed", error=payload.error)
-        except SessionQueueItemNotFoundError:
-            pass
-
-    async def _handle_cancel_event(self, event: FastAPIEvent[SessionCanceledEvent]) -> None:
-        try:
-            _event_name, payload = event
-            queue_item = self.get_queue_item(payload.item_id)
-            if queue_item.status not in ["completed", "failed", "canceled"]:
-                self._set_queue_item_status(item_id=payload.item_id, status="canceled")
-        except SessionQueueItemNotFoundError:
-            pass
-
     def _set_in_progress_to_canceled(self) -> None:
         """
         Sets all in_progress queue items to canceled. Run on app startup, not associated with any queue.
@@ -263,17 +222,22 @@ class SqliteSessionQueue(SessionQueueBase):
         return SessionQueueItem.queue_item_from_dict(dict(result))
 
     def _set_queue_item_status(
-        self, item_id: int, status: QUEUE_ITEM_STATUS, error: Optional[str] = None
+        self,
+        item_id: int,
+        status: QUEUE_ITEM_STATUS,
+        error_type: Optional[str] = None,
+        error_message: Optional[str] = None,
+        error_traceback: Optional[str] = None,
     ) -> SessionQueueItem:
         try:
             self.__lock.acquire()
             self.__cursor.execute(
                 """--sql
                 UPDATE session_queue
-                SET status = ?, error = ?
+                SET status = ?, error_type = ?, error_message = ?, error_traceback = ?
                 WHERE item_id = ?
                 """,
-                (status, error, item_id),
+                (status, error_type, error_message, error_traceback, item_id),
             )
             self.__conn.commit()
         except Exception:
@@ -326,26 +290,6 @@ class SqliteSessionQueue(SessionQueueBase):
             self.__lock.release()
         return IsFullResult(is_full=is_full)
 
-    def delete_queue_item(self, item_id: int) -> SessionQueueItem:
-        queue_item = self.get_queue_item(item_id=item_id)
-        try:
-            self.__lock.acquire()
-            self.__cursor.execute(
-                """--sql
-                DELETE FROM session_queue
-                WHERE
-                  item_id = ?
-                """,
-                (item_id,),
-            )
-            self.__conn.commit()
-        except Exception:
-            self.__conn.rollback()
-            raise
-        finally:
-            self.__lock.release()
-        return queue_item
-
     def clear(self, queue_id: str) -> ClearResult:
         try:
             self.__lock.acquire()
@@ -412,12 +356,28 @@ class SqliteSessionQueue(SessionQueueBase):
             self.__lock.release()
         return PruneResult(deleted=count)
 
-    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"]:
-            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)
+    def cancel_queue_item(self, item_id: int) -> SessionQueueItem:
+        queue_item = self._set_queue_item_status(item_id=item_id, status="canceled")
+        return queue_item
+
+    def complete_queue_item(self, item_id: int) -> SessionQueueItem:
+        queue_item = self._set_queue_item_status(item_id=item_id, status="completed")
+        return queue_item
+
+    def fail_queue_item(
+        self,
+        item_id: int,
+        error_type: str,
+        error_message: str,
+        error_traceback: str,
+    ) -> SessionQueueItem:
+        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,
+        )
         return queue_item
 
     def cancel_by_batch_ids(self, queue_id: str, batch_ids: list[str]) -> CancelByBatchIDsResult:
@@ -453,7 +413,6 @@ class SqliteSessionQueue(SessionQueueBase):
             )
             self.__conn.commit()
             if current_queue_item is not None and current_queue_item.batch_id in batch_ids:
-                self.__invoker.services.events.emit_session_canceled(current_queue_item)
                 batch_status = self.get_batch_status(queue_id=queue_id, batch_id=current_queue_item.batch_id)
                 queue_status = self.get_queue_status(queue_id=queue_id)
                 self.__invoker.services.events.emit_queue_item_status_changed(
@@ -497,7 +456,6 @@ class SqliteSessionQueue(SessionQueueBase):
             )
             self.__conn.commit()
             if current_queue_item is not None and current_queue_item.queue_id == queue_id:
-                self.__invoker.services.events.emit_session_canceled(current_queue_item)
                 batch_status = self.get_batch_status(queue_id=queue_id, batch_id=current_queue_item.batch_id)
                 queue_status = self.get_queue_status(queue_id=queue_id)
                 self.__invoker.services.events.emit_queue_item_status_changed(
@@ -570,7 +528,9 @@ class SqliteSessionQueue(SessionQueueBase):
                     status,
                     priority,
                     field_values,
-                    error,
+                    error_type,
+                    error_message,
+                    error_traceback,
                     created_at,
                     updated_at,
                     completed_at,

invokeai/app/services/shared/graph.py

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

invokeai/app/services/shared/invocation_context.py

@@ -1,7 +1,6 @@
-import threading
 from dataclasses import dataclass
 from pathlib import Path
-from typing import TYPE_CHECKING, Optional, Union
+from typing import TYPE_CHECKING, Callable, Optional, Union
 
 from PIL.Image import Image
 from torch import Tensor
@@ -449,10 +448,10 @@ class ConfigInterface(InvocationContextInterface):
 
 class UtilInterface(InvocationContextInterface):
     def __init__(
-        self, services: InvocationServices, data: InvocationContextData, cancel_event: threading.Event
+        self, services: InvocationServices, data: InvocationContextData, is_canceled: Callable[[], bool]
     ) -> None:
         super().__init__(services, data)
-        self._cancel_event = cancel_event
+        self._is_canceled = is_canceled
 
     def is_canceled(self) -> bool:
         """Checks if the current session has been canceled.
@@ -460,7 +459,7 @@ class UtilInterface(InvocationContextInterface):
         Returns:
             True if the current session has been canceled, False if not.
         """
-        return self._cancel_event.is_set()
+        return self._is_canceled()
 
     def sd_step_callback(self, intermediate_state: PipelineIntermediateState, base_model: BaseModelType) -> None:
         """
@@ -535,7 +534,7 @@ class InvocationContext:
 def build_invocation_context(
     services: InvocationServices,
     data: InvocationContextData,
-    cancel_event: threading.Event,
+    is_canceled: Callable[[], bool],
 ) -> InvocationContext:
     """Builds the invocation context for a specific invocation execution.
 
@@ -552,7 +551,7 @@ def build_invocation_context(
     tensors = TensorsInterface(services=services, data=data)
     models = ModelsInterface(services=services, data=data)
     config = ConfigInterface(services=services, data=data)
-    util = UtilInterface(services=services, data=data, cancel_event=cancel_event)
+    util = UtilInterface(services=services, data=data, is_canceled=is_canceled)
     conditioning = ConditioningInterface(services=services, data=data)
     boards = BoardsInterface(services=services, data=data)
 

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

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

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

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

invokeai/backend/model_manager/convert_ckpt_to_diffusers.py

@@ -30,8 +30,12 @@ def convert_ldm_vae_to_diffusers(
     converted_vae_checkpoint = convert_ldm_vae_checkpoint(checkpoint, vae_config)
 
     vae = AutoencoderKL(**vae_config)
-    vae.load_state_dict(converted_vae_checkpoint)
-    vae.to(precision)
+    with torch.no_grad():
+        vae.load_state_dict(converted_vae_checkpoint)
+        del converted_vae_checkpoint  # Free memory
+        import gc
+        gc.collect()
+        vae.to(precision)
 
     if dump_path:
         vae.save_pretrained(dump_path, safe_serialization=True)
@@ -52,7 +56,11 @@ def convert_ckpt_to_diffusers(
     model to be written.
     """
     pipe = download_from_original_stable_diffusion_ckpt(Path(checkpoint_path).as_posix(), **kwargs)
-    pipe = pipe.to(precision)
+    with torch.no_grad():
+        del kwargs  # Free memory
+        import gc
+        gc.collect()
+        pipe = pipe.to(precision)
 
     # TO DO: save correct repo variant
     if dump_path:
@@ -75,7 +83,11 @@ def convert_controlnet_to_diffusers(
     model to be written.
     """
     pipe = download_controlnet_from_original_ckpt(checkpoint_path.as_posix(), **kwargs)
-    pipe = pipe.to(precision)
+    with torch.no_grad():
+        del kwargs  # Free memory
+        import gc
+        gc.collect()
+        pipe = pipe.to(precision)
 
     # TO DO: save correct repo variant
     if dump_path:

invokeai/backend/model_manager/load/model_cache/model_cache_base.py

@@ -42,10 +42,26 @@ T = TypeVar("T")
 
 @dataclass
 class CacheRecord(Generic[T]):
-    """Elements of the cache."""
+    """
+    Elements of the cache:
+
+    key: Unique key for each model, same as used in the models database.
+    model: Model in memory.
+    state_dict: A read-only copy of the model's state dict in RAM. It will be
+                used as a template for creating a copy in the VRAM.
+    size: Size of the model
+    loaded: True if the model's state dict is currently in VRAM
+
+    Before a model is executed, the state_dict template is copied into VRAM,
+    and then injected into the model. When the model is finished, the VRAM
+    copy of the state dict is deleted, and the RAM version is reinjected
+    into the model.
+    """
 
     key: str
     model: T
+    device: torch.device
+    state_dict: Optional[Dict[str, torch.Tensor]]
     size: int
     loaded: bool = False
     _locks: int = 0

invokeai/backend/model_manager/load/model_cache/model_cache_default.py

@@ -20,7 +20,6 @@ context. Use like this:
 
 import gc
 import math
-import sys
 import time
 from contextlib import suppress
 from logging import Logger
@@ -162,7 +161,9 @@ class ModelCache(ModelCacheBase[AnyModel]):
         if key in self._cached_models:
             return
         self.make_room(size)
-        cache_record = CacheRecord(key, model, size)
+
+        state_dict = model.state_dict() if isinstance(model, torch.nn.Module) else None
+        cache_record = CacheRecord(key=key, model=model, device=self.storage_device, state_dict=state_dict, size=size)
         self._cached_models[key] = cache_record
         self._cache_stack.append(key)
 
@@ -257,17 +258,37 @@ class ModelCache(ModelCacheBase[AnyModel]):
         if not (hasattr(cache_entry.model, "device") and hasattr(cache_entry.model, "to")):
             return
 
-        source_device = cache_entry.model.device
+        source_device = cache_entry.device
 
         # Note: We compare device types only so that 'cuda' == 'cuda:0'.
         # This would need to be revised to support multi-GPU.
         if torch.device(source_device).type == torch.device(target_device).type:
             return
 
+        # This roundabout method for moving the model around is done to avoid
+        # the cost of moving the model from RAM to VRAM and then back from VRAM to RAM.
+        # When moving to VRAM, we copy (not move) each element of the state dict from
+        # RAM to a new state dict in VRAM, and then inject it into the model.
+        # This operation is slightly faster than running `to()` on the whole model.
+        #
+        # When the model needs to be removed from VRAM we simply delete the copy
+        # of the state dict in VRAM, and reinject the state dict that is cached
+        # in RAM into the model. So this operation is very fast.
         start_model_to_time = time.time()
         snapshot_before = self._capture_memory_snapshot()
+
         try:
+            if cache_entry.state_dict is not None:
+                assert hasattr(cache_entry.model, "load_state_dict")
+                if target_device == self.storage_device:
+                    cache_entry.model.load_state_dict(cache_entry.state_dict, assign=True)
+                else:
+                    new_dict: Dict[str, torch.Tensor] = {}
+                    for k, v in cache_entry.state_dict.items():
+                        new_dict[k] = v.to(torch.device(target_device), copy=True)
+                    cache_entry.model.load_state_dict(new_dict, assign=True)
             cache_entry.model.to(target_device)
+            cache_entry.device = target_device
         except Exception as e:  # blow away cache entry
             self._delete_cache_entry(cache_entry)
             raise e
@@ -347,43 +368,12 @@ class ModelCache(ModelCacheBase[AnyModel]):
         while current_size + bytes_needed > maximum_size and pos < len(self._cache_stack):
             model_key = self._cache_stack[pos]
             cache_entry = self._cached_models[model_key]
-
-            refs = sys.getrefcount(cache_entry.model)
-
-            # HACK: This is a workaround for a memory-management issue that we haven't tracked down yet. We are directly
-            # going against the advice in the Python docs by using `gc.get_referrers(...)` in this way:
-            # https://docs.python.org/3/library/gc.html#gc.get_referrers
-
-            # manualy clear local variable references of just finished function calls
-            # for some reason python don't want to collect it even by gc.collect() immidiately
-            if refs > 2:
-                while True:
-                    cleared = False
-                    for referrer in gc.get_referrers(cache_entry.model):
-                        if type(referrer).__name__ == "frame":
-                            # RuntimeError: cannot clear an executing frame
-                            with suppress(RuntimeError):
-                                referrer.clear()
-                                cleared = True
-                                # break
-
-                    # repeat if referrers changes(due to frame clear), else exit loop
-                    if cleared:
-                        gc.collect()
-                    else:
-                        break
-
             device = cache_entry.model.device if hasattr(cache_entry.model, "device") else None
             self.logger.debug(
-                f"Model: {model_key}, locks: {cache_entry._locks}, device: {device}, loaded: {cache_entry.loaded},"
-                f" refs: {refs}"
+                f"Model: {model_key}, locks: {cache_entry._locks}, device: {device}, loaded: {cache_entry.loaded}"
             )
 
-            # Expected refs:
-            # 1 from cache_entry
-            # 1 from getrefcount function
-            # 1 from onnx runtime object
-            if not cache_entry.locked and refs <= (3 if "onnx" in model_key else 2):
+            if not cache_entry.locked:
                 self.logger.debug(
                     f"Removing {model_key} from RAM cache to free at least {(size/GIG):.2f} GB (-{(cache_entry.size/GIG):.2f} GB)"
                 )

invokeai/backend/textual_inversion.py

@@ -1,7 +1,7 @@
 """Textual Inversion wrapper class."""
 
 from pathlib import Path
-from typing import Dict, List, Optional, Union
+from typing import Optional, Union
 
 import torch
 from compel.embeddings_provider import BaseTextualInversionManager
@@ -66,35 +66,52 @@ class TextualInversionModelRaw(RawModel):
         return result
 
 
-# no type hints for BaseTextualInversionManager?
-class TextualInversionManager(BaseTextualInversionManager):  # type: ignore
-    pad_tokens: Dict[int, List[int]]
-    tokenizer: CLIPTokenizer
+class TextualInversionManager(BaseTextualInversionManager):
+    """TextualInversionManager implements the BaseTextualInversionManager ABC from the compel library."""
 
     def __init__(self, tokenizer: CLIPTokenizer):
-        self.pad_tokens = {}
+        self.pad_tokens: dict[int, list[int]] = {}
         self.tokenizer = tokenizer
 
     def expand_textual_inversion_token_ids_if_necessary(self, token_ids: list[int]) -> list[int]:
+        """Given a list of tokens ids, expand any TI tokens to their corresponding pad tokens.
+
+        For example, suppose we have a `<ti_dog>` TI with 4 vectors that was added to the tokenizer with the following
+        mapping of tokens to token_ids:
+        ```
+        <ti_dog>: 49408
+        <ti_dog-!pad-1>: 49409
+        <ti_dog-!pad-2>: 49410
+        <ti_dog-!pad-3>: 49411
+        ```
+        `self.pad_tokens` would be set to `{49408: [49408, 49409, 49410, 49411]}`.
+        This function is responsible for expanding `49408` in the token_ids list to `[49408, 49409, 49410, 49411]`.
+        """
+        # Short circuit if there are no pad tokens to save a little time.
         if len(self.pad_tokens) == 0:
             return token_ids
 
+        # This function assumes that compel has not included the BOS and EOS tokens in the token_ids list. We verify
+        # this assumption here.
         if token_ids[0] == self.tokenizer.bos_token_id:
             raise ValueError("token_ids must not start with bos_token_id")
         if token_ids[-1] == self.tokenizer.eos_token_id:
             raise ValueError("token_ids must not end with eos_token_id")
 
-        new_token_ids = []
+        # Expand any TI tokens to their corresponding pad tokens.
+        new_token_ids: list[int] = []
         for token_id in token_ids:
             new_token_ids.append(token_id)
             if token_id in self.pad_tokens:
                 new_token_ids.extend(self.pad_tokens[token_id])
 
-        # Do not exceed the max model input size
-        # The -2 here is compensating for compensate compel.embeddings_provider.get_token_ids(),
-        # which first removes and then adds back the start and end tokens.
-        max_length = list(self.tokenizer.max_model_input_sizes.values())[0] - 2
+        # Do not exceed the max model input size. The -2 here is compensating for
+        # compel.embeddings_provider.get_token_ids(), which first removes and then adds back the start and end tokens.
+        max_length = self.tokenizer.model_max_length - 2
         if len(new_token_ids) > max_length:
+            # HACK: If TI token expansion causes us to exceed the max text encoder input length, we silently discard
+            # tokens. Token expansion should happen in a way that is compatible with compel's default handling of long
+            # prompts.
             new_token_ids = new_token_ids[0:max_length]
 
         return new_token_ids

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

@@ -2,6 +2,7 @@
     "accessibility": {
         "about": "About",
         "createIssue": "Create Issue",
+        "submitSupportTicket": "Submit Support Ticket",
         "invokeProgressBar": "Invoke progress bar",
         "menu": "Menu",
         "mode": "Mode",
@@ -146,7 +147,9 @@
         "viewing": "Viewing",
         "viewingDesc": "Review images in a large gallery view",
         "editing": "Editing",
-        "editingDesc": "Edit on the Control Layers canvas"
+        "editingDesc": "Edit on the Control Layers canvas",
+        "enabled": "Enabled",
+        "disabled": "Disabled"
     },
     "controlnet": {
         "controlAdapter_one": "Control Adapter",
@@ -897,7 +900,10 @@
         "zoomInNodes": "Zoom In",
         "zoomOutNodes": "Zoom Out",
         "betaDesc": "This invocation is in beta. Until it is stable, it may have breaking changes during app updates. We plan to support this invocation long-term.",
-        "prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time."
+        "prototypeDesc": "This invocation is a prototype. It may have breaking changes during app updates and may be removed at any time.",
+        "imageAccessError": "Unable to find image {{image_name}}, resetting to default",
+        "boardAccessError": "Unable to find board {{board_id}}, resetting to default",
+        "modelAccessError": "Unable to find model {{key}}, resetting to default"
     },
     "parameters": {
         "aspect": "Aspect",
@@ -1070,8 +1076,9 @@
     },
     "toast": {
         "addedToBoard": "Added to board",
-        "baseModelChangedCleared_one": "Base model changed, cleared or disabled {{count}} incompatible submodel",
-        "baseModelChangedCleared_other": "Base model changed, cleared or disabled {{count}} incompatible submodels",
+        "baseModelChanged": "Base Model Changed",
+        "baseModelChangedCleared_one": "Cleared or disabled {{count}} incompatible submodel",
+        "baseModelChangedCleared_other": "Cleared or disabled {{count}} incompatible submodels",
         "canceled": "Processing Canceled",
         "canvasCopiedClipboard": "Canvas Copied to Clipboard",
         "canvasDownloaded": "Canvas Downloaded",
@@ -1092,10 +1099,17 @@
         "metadataLoadFailed": "Failed to load metadata",
         "modelAddedSimple": "Model Added to Queue",
         "modelImportCanceled": "Model Import Canceled",
+        "outOfMemoryError": "Out of Memory Error",
+        "outOfMemoryErrorDesc": "Your current generation settings exceed system capacity. Please adjust your settings and try again.",
         "parameters": "Parameters",
-        "parameterNotSet": "{{parameter}} not set",
-        "parameterSet": "{{parameter}} set",
-        "parametersNotSet": "Parameters Not Set",
+        "parameterSet": "Parameter Recalled",
+        "parameterSetDesc": "Recalled {{parameter}}",
+        "parameterNotSet": "Parameter Not Recalled",
+        "parameterNotSetDesc": "Unable to recall {{parameter}}",
+        "parameterNotSetDescWithMessage": "Unable to recall {{parameter}}: {{message}}",
+        "parametersSet": "Parameters Recalled",
+        "parametersNotSet": "Parameters Not Recalled",
+        "errorCopied": "Error Copied",
         "problemCopyingCanvas": "Problem Copying Canvas",
         "problemCopyingCanvasDesc": "Unable to export base layer",
         "problemCopyingImage": "Unable to Copy Image",
@@ -1115,11 +1129,13 @@
         "sentToImageToImage": "Sent To Image To Image",
         "sentToUnifiedCanvas": "Sent to Unified Canvas",
         "serverError": "Server Error",
+        "sessionRef": "Session: {{sessionId}}",
         "setAsCanvasInitialImage": "Set as canvas initial image",
         "setCanvasInitialImage": "Set canvas initial image",
         "setControlImage": "Set as control image",
         "setInitialImage": "Set as initial image",
         "setNodeField": "Set as node field",
+        "somethingWentWrong": "Something Went Wrong",
         "uploadFailed": "Upload failed",
         "uploadFailedInvalidUploadDesc": "Must be single PNG or JPEG image",
         "uploadInitialImage": "Upload Initial Image",
@@ -1559,7 +1575,6 @@
         "controlLayers": "Control Layers",
         "globalMaskOpacity": "Global Mask Opacity",
         "autoNegative": "Auto Negative",
-        "toggleVisibility": "Toggle Layer Visibility",
         "deletePrompt": "Delete Prompt",
         "resetRegion": "Reset Region",
         "debugLayers": "Debug Layers",

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

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

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

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

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

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

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

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

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

@@ -25,7 +25,6 @@ import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
 
 import AppErrorBoundaryFallback from './AppErrorBoundaryFallback';
 import PreselectedImage from './PreselectedImage';
-import Toaster from './Toaster';
 
 const DEFAULT_CONFIG = {};
 
@@ -96,7 +95,6 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
       <DeleteImageModal />
       <ChangeBoardModal />
       <DynamicPromptsModal />
-      <Toaster />
       <PreselectedImage selectedImage={selectedImage} />
     </ErrorBoundary>
   );

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

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

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

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

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

@@ -6,8 +6,8 @@ import { useAppDispatch } from 'app/store/storeHooks';
 import type { MapStore } from 'nanostores';
 import { atom, map } from 'nanostores';
 import { useEffect, useMemo } from 'react';
+import { setEventListeners } from 'services/events/setEventListeners';
 import type { ClientToServerEvents, ServerToClientEvents } from 'services/events/types';
-import { setEventListeners } from 'services/events/util/setEventListeners';
 import type { ManagerOptions, Socket, SocketOptions } from 'socket.io-client';
 import { io } from 'socket.io-client';
 

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

@@ -39,7 +39,6 @@ import { addSetDefaultSettingsListener } from 'app/store/middleware/listenerMidd
 import { addSocketConnectedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketConnected';
 import { addSocketDisconnectedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketDisconnected';
 import { addGeneratorProgressEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketGeneratorProgress';
-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 { addInvocationStartedEventListener } from 'app/store/middleware/listenerMiddleware/listeners/socketio/socketInvocationStarted';
@@ -99,7 +98,6 @@ addCommitStagingAreaImageListener(startAppListening);
 
 // Socket.IO
 addGeneratorProgressEventListener(startAppListening);
-addGraphExecutionStateCompleteEventListener(startAppListening);
 addInvocationCompleteEventListener(startAppListening);
 addInvocationErrorEventListener(startAppListening);
 addInvocationStartedEventListener(startAppListening);

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

@@ -3,7 +3,7 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { parseify } from 'common/util/serialize';
 import { canvasSavedToGallery } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { imagesApi } from 'services/api/endpoints/images';
 
@@ -19,13 +19,12 @@ export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListe
         blob = await getBaseLayerBlob(state);
       } catch (err) {
         log.error(String(err));
-        dispatch(
-          addToast({
-            title: t('toast.problemSavingCanvas'),
-            description: t('toast.problemSavingCanvasDesc'),
-            status: 'error',
-          })
-        );
+        toast({
+          id: 'CANVAS_SAVE_FAILED',
+          title: t('toast.problemSavingCanvas'),
+          description: t('toast.problemSavingCanvasDesc'),
+          status: 'error',
+        });
         return;
       }
 
@@ -42,7 +41,7 @@ export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListe
           crop_visible: true,
           postUploadAction: {
             type: 'TOAST',
-            toastOptions: { title: t('toast.canvasSavedGallery') },
+            title: t('toast.canvasSavedGallery'),
           },
           metadata: {
             _canvas_objects: parseify(state.canvas.layerState.objects),

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

@@ -14,7 +14,7 @@ import {
 } from 'features/controlLayers/store/controlLayersSlice';
 import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
 import { isImageOutput } from 'features/nodes/types/common';
-import { addToast } from 'features/system/store/systemSlice';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 import { isEqual } from 'lodash-es';
 import { getImageDTO } from 'services/api/endpoints/images';
@@ -174,12 +174,11 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
             }
           }
 
-          dispatch(
-            addToast({
-              title: t('queue.graphFailedToQueue'),
-              status: 'error',
-            })
-          );
+          toast({
+            id: 'GRAPH_QUEUE_FAILED',
+            title: t('queue.graphFailedToQueue'),
+            status: 'error',
+          });
         }
       } finally {
         req.reset();

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

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

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

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

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

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

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

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

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

@@ -1,6 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { deepClone } from 'common/util/deepClone';
+import { parseify } from 'common/util/serialize';
 import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketGeneratorProgress } from 'services/events/actions';
@@ -11,7 +12,7 @@ export const addGeneratorProgressEventListener = (startAppListening: AppStartLis
   startAppListening({
     actionCreator: socketGeneratorProgress,
     effect: (action) => {
-      log.trace(action.payload, `Generator progress`);
+      log.trace(parseify(action.payload), `Generator progress`);
       const { invocation_source_id, step, total_steps, progress_image } = action.payload.data;
       const nes = deepClone($nodeExecutionStates.get()[invocation_source_id]);
       if (nes) {

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

@@ -1,14 +0,0 @@
-import { logger } from 'app/logging/logger';
-import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
-import { socketGraphExecutionStateComplete } from 'services/events/actions';
-
-const log = logger('socketio');
-
-export const addGraphExecutionStateCompleteEventListener = (startAppListening: AppStartListening) => {
-  startAppListening({
-    actionCreator: socketGraphExecutionStateComplete,
-    effect: (action) => {
-      log.debug(action.payload, 'Session complete');
-    },
-  });
-};

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

@@ -29,11 +29,11 @@ export const addInvocationCompleteEventListener = (startAppListening: AppStartLi
     actionCreator: socketInvocationComplete,
     effect: async (action, { dispatch, getState }) => {
       const { data } = action.payload;
-      log.debug({ data: parseify(data) }, `Invocation complete (${data.invocation_type})`);
+      log.debug({ data: parseify(data) }, `Invocation complete (${data.invocation.type})`);
 
       const { result, invocation_source_id } = data;
       // This complete event has an associated image output
-      if (isImageOutput(data.result) && !nodeTypeDenylist.includes(data.invocation_type)) {
+      if (isImageOutput(data.result) && !nodeTypeDenylist.includes(data.invocation.type)) {
         const { image_name } = data.result.image;
         const { canvas, gallery } = getState();
 

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

@@ -1,6 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { deepClone } from 'common/util/deepClone';
+import { parseify } from 'common/util/serialize';
 import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketInvocationError } from 'services/events/actions';
@@ -11,14 +12,18 @@ export const addInvocationErrorEventListener = (startAppListening: AppStartListe
   startAppListening({
     actionCreator: socketInvocationError,
     effect: (action) => {
-      log.error(action.payload, `Invocation error (${action.payload.data.invocation_type})`);
-      const { invocation_source_id } = action.payload.data;
+      const { invocation_source_id, invocation, error_type, error_message, error_traceback } = action.payload.data;
+      log.error(parseify(action.payload), `Invocation error (${invocation.type})`);
       const nes = deepClone($nodeExecutionStates.get()[invocation_source_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);
       }
     },

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

@@ -1,6 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { deepClone } from 'common/util/deepClone';
+import { parseify } from 'common/util/serialize';
 import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketInvocationStarted } from 'services/events/actions';
@@ -11,7 +12,7 @@ export const addInvocationStartedEventListener = (startAppListening: AppStartLis
   startAppListening({
     actionCreator: socketInvocationStarted,
     effect: (action) => {
-      log.debug(action.payload, `Invocation started (${action.payload.data.invocation_type})`);
+      log.debug(parseify(action.payload), `Invocation started (${action.payload.data.invocation.type})`);
       const { invocation_source_id } = action.payload.data;
       const nes = deepClone($nodeExecutionStates.get()[invocation_source_id]);
       if (nes) {

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

@@ -3,6 +3,8 @@ import type { AppStartListening } from 'app/store/middleware/listenerMiddleware'
 import { deepClone } from 'common/util/deepClone';
 import { $nodeExecutionStates } from 'features/nodes/hooks/useExecutionState';
 import { zNodeStatus } from 'features/nodes/types/invocation';
+import ErrorToastDescription, { getTitleFromErrorType } from 'features/toast/ErrorToastDescription';
+import { toast } from 'features/toast/toast';
 import { forEach } from 'lodash-es';
 import { queueApi, queueItemsAdapter } from 'services/api/endpoints/queue';
 import { socketQueueItemStatusChanged } from 'services/events/actions';
@@ -12,10 +14,21 @@ const log = logger('socketio');
 export const addSocketQueueItemStatusChangedEventListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: socketQueueItemStatusChanged,
-    effect: async (action, { dispatch }) => {
+    effect: async (action, { dispatch, getState }) => {
       // we've got new status for the queue item, batch and queue
-      const { item_id, status, started_at, updated_at, error, completed_at, batch_status, queue_status } =
-        action.payload.data;
+      const {
+        item_id,
+        session_id,
+        status,
+        started_at,
+        updated_at,
+        completed_at,
+        batch_status,
+        queue_status,
+        error_type,
+        error_message,
+        error_traceback,
+      } = action.payload.data;
 
       log.debug(action.payload, `Queue item ${item_id} status updated: ${status}`);
 
@@ -28,8 +41,10 @@ export const addSocketQueueItemStatusChangedEventListener = (startAppListening:
               status,
               started_at,
               updated_at: updated_at ?? undefined,
-              error,
               completed_at: completed_at ?? undefined,
+              error_type,
+              error_message,
+              error_traceback,
             },
           });
         })
@@ -61,7 +76,7 @@ export const addSocketQueueItemStatusChangedEventListener = (startAppListening:
         ])
       );
 
-      if (['in_progress'].includes(action.payload.data.status)) {
+      if (status === 'in_progress') {
         forEach($nodeExecutionStates.get(), (nes) => {
           if (!nes) {
             return;
@@ -74,6 +89,25 @@ export const addSocketQueueItemStatusChangedEventListener = (startAppListening:
           clone.outputs = [];
           $nodeExecutionStates.setKey(clone.nodeId, clone);
         });
+      } else if (status === 'failed' && error_type) {
+        const isLocal = getState().config.isLocal ?? true;
+        const sessionId = session_id;
+
+        toast({
+          id: `INVOCATION_ERROR_${error_type}`,
+          title: getTitleFromErrorType(error_type),
+          status: 'error',
+          duration: null,
+          updateDescription: isLocal,
+          description: (
+            <ErrorToastDescription
+              errorType={error_type}
+              errorMessage={error_message}
+              sessionId={sessionId}
+              isLocal={isLocal}
+            />
+          ),
+        });
       }
     },
   });

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

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

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

@@ -5,8 +5,7 @@ import { $templates, nodesChanged } from 'features/nodes/store/nodesSlice';
 import { NodeUpdateError } from 'features/nodes/types/error';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { getNeedsUpdate, updateNode } from 'features/nodes/util/node/nodeUpdate';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
 
 export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartListening) => {
@@ -50,24 +49,18 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
             count: unableToUpdateCount,
           })
         );
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('nodes.unableToUpdateNodes', {
-                count: unableToUpdateCount,
-              }),
-            })
-          )
-        );
+        toast({
+          id: 'UNABLE_TO_UPDATE_NODES',
+          title: t('nodes.unableToUpdateNodes', {
+            count: unableToUpdateCount,
+          }),
+        });
       } else {
-        dispatch(
-          addToast(
-            makeToast({
-              title: t('nodes.allNodesUpdated'),
-              status: 'success',
-            })
-          )
-        );
+        toast({
+          id: 'ALL_NODES_UPDATED',
+          title: t('nodes.allNodesUpdated'),
+          status: 'success',
+        });
       }
     },
   });

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

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

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

@@ -8,23 +8,23 @@ import type { Templates } from 'features/nodes/store/types';
 import { WorkflowMigrationError, WorkflowVersionError } from 'features/nodes/types/error';
 import { graphToWorkflow } from 'features/nodes/util/workflow/graphToWorkflow';
 import { validateWorkflow } from 'features/nodes/util/workflow/validateWorkflow';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { t } from 'i18next';
+import { checkBoardAccess, checkImageAccess, checkModelAccess } from 'services/api/hooks/accessChecks';
 import type { GraphAndWorkflowResponse, NonNullableGraph } from 'services/api/types';
 import { z } from 'zod';
 import { fromZodError } from 'zod-validation-error';
 
-const getWorkflow = (data: GraphAndWorkflowResponse, templates: Templates) => {
+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 validateWorkflow(parsed, templates);
+    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 validateWorkflow(workflow, templates);
+    return await validateWorkflow(workflow, templates, checkImageAccess, checkBoardAccess, checkModelAccess);
   } else {
     throw new Error('No workflow or graph provided');
   }
@@ -33,13 +33,13 @@ const getWorkflow = (data: GraphAndWorkflowResponse, templates: Templates) => {
 export const addWorkflowLoadRequestedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: workflowLoadRequested,
-    effect: (action, { dispatch }) => {
+    effect: async (action, { dispatch }) => {
       const log = logger('nodes');
       const { data, asCopy } = action.payload;
       const nodeTemplates = $templates.get();
 
       try {
-        const { workflow, warnings } = getWorkflow(data, nodeTemplates);
+        const { workflow, warnings } = await getWorkflow(data, nodeTemplates);
 
         if (asCopy) {
           // If we're loading a copy, we need to remove the ID so that the backend will create a new workflow
@@ -48,23 +48,18 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
 
         dispatch(workflowLoaded(workflow));
         if (!warnings.length) {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.workflowLoaded'),
-                status: 'success',
-              })
-            )
-          );
+          toast({
+            id: 'WORKFLOW_LOADED',
+            title: t('toast.workflowLoaded'),
+            status: 'success',
+          });
         } else {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('toast.loadedWithWarnings'),
-                status: 'warning',
-              })
-            )
-          );
+          toast({
+            id: 'WORKFLOW_LOADED',
+            title: t('toast.loadedWithWarnings'),
+            status: 'warning',
+          });
+
           warnings.forEach(({ message, ...rest }) => {
             log.warn(rest, message);
           });
@@ -77,54 +72,42 @@ export const addWorkflowLoadRequestedListener = (startAppListening: AppStartList
         if (e instanceof WorkflowVersionError) {
           // The workflow version was not recognized in the valid list of versions
           log.error({ error: parseify(e) }, e.message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: e.message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: e.message,
+          });
         } else if (e instanceof WorkflowMigrationError) {
           // There was a problem migrating the workflow to the latest version
           log.error({ error: parseify(e) }, e.message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: e.message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: e.message,
+          });
         } else if (e instanceof z.ZodError) {
           // There was a problem validating the workflow itself
           const { message } = fromZodError(e, {
             prefix: t('nodes.workflowValidation'),
           });
           log.error({ error: parseify(e) }, message);
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: message,
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: message,
+          });
         } else {
           // Some other error occurred
           log.error({ error: parseify(e) }, t('nodes.unknownErrorValidatingWorkflow'));
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('nodes.unableToValidateWorkflow'),
-                status: 'error',
-                description: t('nodes.unknownErrorValidatingWorkflow'),
-              })
-            )
-          );
+          toast({
+            id: 'UNABLE_TO_VALIDATE_WORKFLOW',
+            title: t('nodes.unableToValidateWorkflow'),
+            status: 'error',
+            description: t('nodes.unknownErrorValidatingWorkflow'),
+          });
         }
       }
     },

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

@@ -1,6 +1,5 @@
 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';
@@ -14,6 +13,7 @@ import { sentImageToCanvas, sentImageToImg2Img } from 'features/gallery/store/ac
 import { $templates } from 'features/nodes/store/nodesSlice';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
+import { toast } from 'features/toast/toast';
 import { setActiveTab } from 'features/ui/store/uiSlice';
 import { useGetAndLoadEmbeddedWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadEmbeddedWorkflow';
 import { size } from 'lodash-es';
@@ -46,7 +46,6 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
   const optimalDimension = useAppSelector(selectOptimalDimension);
   const dispatch = useAppDispatch();
   const { t } = useTranslation();
-  const toaster = useAppToaster();
   const isCanvasEnabled = useFeatureStatus('canvas');
   const customStarUi = useStore($customStarUI);
   const { downloadImage } = useDownloadImage();
@@ -86,13 +85,12 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
     });
     dispatch(setInitialCanvasImage(imageDTO, optimalDimension));
 
-    toaster({
+    toast({
+      id: 'SENT_TO_CANVAS',
       title: t('toast.sentToUnifiedCanvas'),
       status: 'success',
-      duration: 2500,
-      isClosable: true,
     });
-  }, [dispatch, imageDTO, t, toaster, optimalDimension]);
+  }, [dispatch, imageDTO, t, optimalDimension]);
 
   const handleChangeBoard = useCallback(() => {
     dispatch(imagesToChangeSelected([imageDTO]));

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

@@ -1,6 +1,5 @@
 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';
@@ -14,7 +13,6 @@ 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);
@@ -24,7 +22,7 @@ export const ToggleMetadataViewerButton = memo(() => {
     [dispatch, shouldShowImageDetails]
   );
 
-  useHotkeys('i', toggleMetadataViewer, { enabled: Boolean(imageDTO) }, [imageDTO, shouldShowImageDetails, toaster]);
+  useHotkeys('i', toggleMetadataViewer, { enabled: Boolean(imageDTO) }, [imageDTO, shouldShowImageDetails]);
 
   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);
+      handlers.seed.recall && handlers.seed.recall(seed, true);
     });
   }, [metadata]);
 

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

@@ -1,5 +1,4 @@
 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 {
@@ -15,6 +14,7 @@ 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, description?: string) => {
+const parameterSetToast = (parameter: string) => {
   toast({
-    title: t('toast.parameterSet', { parameter }),
-    description,
+    id: 'PARAMETER_SET',
+    title: t('toast.parameterSet'),
+    description: t('toast.parameterSetDesc', { parameter }),
     status: 'info',
-    duration: 2500,
-    isClosable: true,
   });
 };
 
-const parameterNotSetToast = (parameter: string, description?: string) => {
+const parameterNotSetToast = (parameter: string, message?: string) => {
   toast({
-    title: t('toast.parameterNotSet', { parameter }),
-    description,
+    id: 'PARAMETER_NOT_SET',
+    title: t('toast.parameterNotSet'),
+    description: message
+      ? t('toast.parameterNotSetDescWithMessage', { parameter, message })
+      : t('toast.parameterNotSetDesc', { parameter }),
     status: 'warning',
-    duration: 2500,
-    isClosable: true,
   });
 };
 
@@ -458,7 +458,18 @@ export const parseAndRecallAllMetadata = async (
         });
       })
   );
+
   if (results.some((result) => result.status === 'fulfilled')) {
-    parameterSetToast(t('toast.parameters'));
+    toast({
+      id: 'PARAMETER_SET',
+      title: t('toast.parametersSet'),
+      status: 'info',
+    });
+  } else {
+    toast({
+      id: 'PARAMETER_SET',
+      title: t('toast.parametersNotSet'),
+      status: 'warning',
+    });
   }
 };

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

@@ -0,0 +1,48 @@
+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

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

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

@@ -1,11 +1,9 @@
 import { Button, Flex, FormControl, FormErrorMessage, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 import type { ChangeEventHandler } from 'react';
 import { useCallback, useState } from 'react';
 import { useTranslation } from 'react-i18next';
-import { useInstallModelMutation, useLazyGetHuggingFaceModelsQuery } from 'services/api/endpoints/models';
+import { useLazyGetHuggingFaceModelsQuery } from 'services/api/endpoints/models';
 
 import { HuggingFaceResults } from './HuggingFaceResults';
 
@@ -14,50 +12,19 @@ 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] = 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 [installModel] = useInstallModel();
 
   const getModels = useCallback(async () => {
     _getHuggingFaceModels(huggingFaceRepo)
       .unwrap()
       .then((response) => {
         if (response.is_diffusers) {
-          handleInstallModel(huggingFaceRepo);
+          installModel({ source: huggingFaceRepo });
           setDisplayResults(false);
         } else if (response.urls?.length === 1 && response.urls[0]) {
-          handleInstallModel(response.urls[0]);
+          installModel({ source: response.urls[0] });
           setDisplayResults(false);
         } else {
           setDisplayResults(true);
@@ -66,7 +33,7 @@ export const HuggingFaceForm = () => {
       .catch((error) => {
         setErrorMessage(error.data.detail || '');
       });
-  }, [_getHuggingFaceModels, handleInstallModel, huggingFaceRepo]);
+  }, [_getHuggingFaceModels, installModel, huggingFaceRepo]);
 
   const handleSetHuggingFaceRepo: ChangeEventHandler<HTMLInputElement> = useCallback((e) => {
     setHuggingFaceRepo(e.target.value);

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

@@ -1,47 +1,20 @@
 import { Flex, IconButton, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 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] = useInstallModelMutation();
+  const [installModel] = useInstallModel();
 
-  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]);
+  const onClick = useCallback(() => {
+    installModel({ source: result });
+  }, [installModel, result]);
 
   return (
     <Flex alignItems="center" justifyContent="space-between" w="100%" gap={3}>
@@ -51,7 +24,7 @@ export const HuggingFaceResultItem = ({ result }: Props) => {
           {result}
         </Text>
       </Flex>
-      <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={handleInstall} size="sm" />
+      <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={onClick} size="sm" />
     </Flex>
   );
 };

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

@@ -8,15 +8,12 @@ import {
   InputGroup,
   InputRightElement,
 } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 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';
 
@@ -27,9 +24,8 @@ type HuggingFaceResultsProps = {
 export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
   const { t } = useTranslation();
   const [searchTerm, setSearchTerm] = useState('');
-  const dispatch = useAppDispatch();
 
-  const [installModel] = useInstallModelMutation();
+  const [installModel] = useInstallModel();
 
   const filteredResults = useMemo(() => {
     return results.filter((result) => {
@@ -46,34 +42,11 @@ export const HuggingFaceResults = ({ results }: HuggingFaceResultsProps) => {
     setSearchTerm('');
   }, []);
 
-  const handleAddAll = useCallback(() => {
+  const onClickAddAll = useCallback(() => {
     for (const result of filteredResults) {
-      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({ source: result });
     }
-  }, [filteredResults, installModel, dispatch, t]);
+  }, [filteredResults, installModel]);
 
   return (
     <>
@@ -82,7 +55,7 @@ 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={handleAddAll} isDisabled={results.length === 0} flexShrink={0}>
+            <Button size="sm" onClick={onClickAddAll} 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

@@ -1,12 +1,9 @@
 import { Button, Checkbox, Flex, FormControl, FormHelperText, FormLabel, Input } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 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;
@@ -14,9 +11,7 @@ type SimpleImportModelConfig = {
 };
 
 export const InstallModelForm = () => {
-  const dispatch = useAppDispatch();
-
-  const [installModel, { isLoading }] = useInstallModelMutation();
+  const [installModel, { isLoading }] = useInstallModel();
 
   const { register, handleSubmit, formState, reset } = useForm<SimpleImportModelConfig>({
     defaultValues: {
@@ -26,40 +21,22 @@ 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 })
-        .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({
+        source: values.location,
+        inplace: values.inplace,
+        onSuccess: resetForm,
+        onError: resetForm,
+      });
     },
-    [dispatch, reset, installModel]
+    [installModel, resetForm]
   );
 
   return (

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

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

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

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

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

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

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

@@ -1,20 +1,16 @@
 import { Badge, Box, Flex, IconButton, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
+import { useInstallModel } from 'features/modelManagerV2/hooks/useInstallModel';
 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) {
@@ -22,36 +18,13 @@ export const StarterModelsResultItem = ({ result }: Props) => {
     }
     return _allSources;
   }, [result]);
-  const [installModel] = useInstallModelMutation();
+  const [installModel] = useInstallModel();
 
-  const handleQuickAdd = useCallback(() => {
+  const onClick = useCallback(() => {
     for (const source of allSources) {
-      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({ source });
     }
-  }, [allSources, installModel, dispatch, t]);
+  }, [allSources, installModel]);
 
   return (
     <Flex alignItems="center" justifyContent="space-between" w="100%" gap={3}>
@@ -67,7 +40,7 @@ export const StarterModelsResultItem = ({ result }: Props) => {
         {result.is_installed ? (
           <Badge>{t('common.installed')}</Badge>
         ) : (
-          <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={handleQuickAdd} size="sm" />
+          <IconButton aria-label={t('modelManager.install')} icon={<PiPlusBold />} onClick={onClick} size="sm" />
         )}
       </Box>
     </Flex>

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

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

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

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

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

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

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

@@ -1,11 +1,10 @@
 import { Button, Flex, Heading, SimpleGrid, Text } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useAppSelector } from 'app/store/storeHooks';
 import { useMainModelDefaultSettings } from 'features/modelManagerV2/hooks/useMainModelDefaultSettings';
 import { DefaultHeight } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultHeight';
 import { DefaultWidth } from 'features/modelManagerV2/subpanels/ModelPanel/MainModelDefaultSettings/DefaultWidth';
 import type { ParameterScheduler } from 'features/parameters/types/parameterSchemas';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
@@ -39,7 +38,6 @@ export type MainModelDefaultSettingsFormData = {
 export const MainModelDefaultSettings = () => {
   const selectedModelKey = useAppSelector((s) => s.modelmanagerV2.selectedModelKey);
   const { t } = useTranslation();
-  const dispatch = useAppDispatch();
 
   const {
     defaultSettingsDefaults,
@@ -76,30 +74,24 @@ export const MainModelDefaultSettings = () => {
       })
         .unwrap()
         .then((_) => {
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.defaultSettingsSaved'),
-                status: 'success',
-              })
-            )
-          );
+          toast({
+            id: 'DEFAULT_SETTINGS_SAVED',
+            title: t('modelManager.defaultSettingsSaved'),
+            status: 'success',
+          });
           reset(data);
         })
         .catch((error) => {
           if (error) {
-            dispatch(
-              addToast(
-                makeToast({
-                  title: `${error.data.detail} `,
-                  status: 'error',
-                })
-              )
-            );
+            toast({
+              id: 'DEFAULT_SETTINGS_SAVE_FAILED',
+              title: `${error.data.detail} `,
+              status: 'error',
+            });
           }
         });
     },
-    [selectedModelKey, dispatch, reset, updateModel, t]
+    [selectedModelKey, reset, updateModel, t]
   );
 
   if (isLoadingDefaultSettings) {

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

@@ -4,8 +4,7 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import { setSelectedModelMode } from 'features/modelManagerV2/store/modelManagerV2Slice';
 import { ModelConvertButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelConvertButton';
 import { ModelEditButton } from 'features/modelManagerV2/subpanels/ModelPanel/ModelEditButton';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { useCallback } from 'react';
 import type { SubmitHandler } from 'react-hook-form';
 import { useForm } from 'react-hook-form';
@@ -47,25 +46,19 @@ export const Model = () => {
         .then((payload) => {
           form.reset(payload, { keepDefaultValues: true });
           dispatch(setSelectedModelMode('view'));
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdated'),
-                status: 'success',
-              })
-            )
-          );
+          toast({
+            id: 'MODEL_UPDATED',
+            title: t('modelManager.modelUpdated'),
+            status: 'success',
+          });
         })
         .catch((_) => {
           form.reset();
-          dispatch(
-            addToast(
-              makeToast({
-                title: t('modelManager.modelUpdateFailed'),
-                status: 'error',
-              })
-            )
-          );
+          toast({
+            id: 'MODEL_UPDATE_FAILED',
+            title: t('modelManager.modelUpdateFailed'),
+            status: 'error',
+          });
         });
     },
     [dispatch, data?.key, form, t, updateModel]

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

@@ -9,9 +9,7 @@ import {
   useDisclosure,
 } from '@invoke-ai/ui-library';
 import { skipToken } from '@reduxjs/toolkit/query';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addToast } from 'features/system/store/systemSlice';
-import { makeToast } from 'features/system/util/makeToast';
+import { toast } from 'features/toast/toast';
 import { useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useConvertModelMutation, useGetModelConfigQuery } from 'services/api/endpoints/models';
@@ -22,7 +20,6 @@ interface ModelConvertProps {
 
 export const ModelConvertButton = (props: ModelConvertProps) => {
   const { modelKey } = props;
-  const dispatch = useAppDispatch();
   const { t } = useTranslation();
   const { data } = useGetModelConfigQuery(modelKey ?? skipToken);
   const [convertModel, { isLoading }] = useConvertModelMutation();
@@ -33,38 +30,26 @@ export const ModelConvertButton = (props: ModelConvertProps) => {
       return;
     }
 
-    dispatch(
-      addToast(
-        makeToast({
-          title: `${t('modelManager.convertingModelBegin')}: ${data?.name}`,
-          status: 'info',
-        })
-      )
-    );
+    const toastId = `CONVERTING_MODEL_${data.key}`;
+    toast({
+      id: toastId,
+      title: `${t('modelManager.convertingModelBegin')}: ${data?.name}`,
+      status: 'info',
+    });
 
     convertModel(data?.key)
       .unwrap()
       .then(() => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: `${t('modelManager.modelConverted')}: ${data?.name}`,
-              status: 'success',
-            })
-          )
-        );
+        toast({ id: toastId, title: `${t('modelManager.modelConverted')}: ${data?.name}`, status: 'success' });
       })
       .catch(() => {
-        dispatch(
-          addToast(
-            makeToast({
-              title: `${t('modelManager.modelConversionFailed')}: ${data?.name}`,
-              status: 'error',
-            })
-          )
-        );
+        toast({
+          id: toastId,
+          title: `${t('modelManager.modelConversionFailed')}: ${data?.name}`,
+          status: 'error',
+        });
       });
-  }, [data, isLoading, dispatch, t, convertModel]);
+  }, [data, isLoading, t, convertModel]);
 
   if (data?.format !== 'checkpoint') {
     return;

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

@@ -72,10 +72,12 @@ export const ModelEdit = ({ form }: Props) => {
               <FormLabel>{t('modelManager.baseModel')}</FormLabel>
               <BaseModelSelect control={form.control} />
             </FormControl>
-            <FormControl flexDir="column" alignItems="flex-start" gap={1}>
-              <FormLabel>{t('modelManager.variant')}</FormLabel>
-              <ModelVariantSelect control={form.control} />
-            </FormControl>
+            {data.type === 'main' && (
+              <FormControl flexDir="column" alignItems="flex-start" gap={1}>
+                <FormLabel>{t('modelManager.variant')}</FormLabel>
+                <ModelVariantSelect control={form.control} />
+              </FormControl>
+            )}
             {data.type === 'main' && data.format === 'checkpoint' && (
               <>
                 <FormControl flexDir="column" alignItems="flex-start" gap={1}>

invokeai/frontend/web/src/features/nodes/components/flow/AddNodePopover/AddNodePopover.tsx

@@ -3,7 +3,6 @@ import 'reactflow/dist/style.css';
 import type { ComboboxOnChange, ComboboxOption } from '@invoke-ai/ui-library';
 import { Combobox, Flex, Popover, PopoverAnchor, PopoverBody, PopoverContent } from '@invoke-ai/ui-library';
 import { useStore } from '@nanostores/react';
-import { useAppToaster } from 'app/components/Toaster';
 import { useAppDispatch, useAppStore } from 'app/store/storeHooks';
 import type { SelectInstance } from 'chakra-react-select';
 import { useBuildNode } from 'features/nodes/hooks/useBuildNode';
@@ -24,6 +23,7 @@ import { connectionToEdge } from 'features/nodes/store/util/reactFlowUtil';
 import { validateConnectionTypes } from 'features/nodes/store/util/validateConnectionTypes';
 import type { AnyNode } from 'features/nodes/types/invocation';
 import { isInvocationNode } from 'features/nodes/types/invocation';
+import { toast } from 'features/toast/toast';
 import { filter, map, memoize, some } from 'lodash-es';
 import { memo, useCallback, useMemo, useRef } from 'react';
 import { flushSync } from 'react-dom';
@@ -60,7 +60,6 @@ const filterOption = memoize((option: FilterOptionOption<ComboboxOption>, inputV
 const AddNodePopover = () => {
   const dispatch = useAppDispatch();
   const buildInvocation = useBuildNode();
-  const toaster = useAppToaster();
   const { t } = useTranslation();
   const selectRef = useRef<SelectInstance<ComboboxOption> | null>(null);
   const inputRef = useRef<HTMLInputElement>(null);
@@ -127,7 +126,7 @@ const AddNodePopover = () => {
         const errorMessage = t('nodes.unknownNode', {
           nodeType: nodeType,
         });
-        toaster({
+        toast({
           status: 'error',
           title: errorMessage,
         });
@@ -163,7 +162,7 @@ const AddNodePopover = () => {
       }
       return node;
     },
-    [buildInvocation, store, dispatch, t, toaster]
+    [buildInvocation, store, dispatch, t]
   );
 
   const onChange = useCallback<ComboboxOnChange>(

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

@@ -1,7 +1,7 @@
 import { Flex, Grid, GridItem } from '@invoke-ai/ui-library';
 import NodeWrapper from 'features/nodes/components/flow/nodes/common/NodeWrapper';
-import { useAnyOrDirectInputFieldNames } from 'features/nodes/hooks/useAnyOrDirectInputFieldNames';
-import { useConnectionInputFieldNames } from 'features/nodes/hooks/useConnectionInputFieldNames';
+import { InvocationInputFieldCheck } from 'features/nodes/components/flow/nodes/Invocation/fields/InvocationFieldCheck';
+import { useFieldNames } from 'features/nodes/hooks/useFieldNames';
 import { useOutputFieldNames } from 'features/nodes/hooks/useOutputFieldNames';
 import { useWithFooter } from 'features/nodes/hooks/useWithFooter';
 import { memo } from 'react';
@@ -20,8 +20,7 @@ type Props = {
 };
 
 const InvocationNode = ({ nodeId, isOpen, label, type, selected }: Props) => {
-  const inputConnectionFieldNames = useConnectionInputFieldNames(nodeId);
-  const inputAnyOrDirectFieldNames = useAnyOrDirectInputFieldNames(nodeId);
+  const fieldNames = useFieldNames(nodeId);
   const withFooter = useWithFooter(nodeId);
   const outputFieldNames = useOutputFieldNames(nodeId);
 
@@ -41,9 +40,11 @@ const InvocationNode = ({ nodeId, isOpen, label, type, selected }: Props) => {
           >
             <Flex flexDir="column" px={2} w="full" h="full">
               <Grid gridTemplateColumns="1fr auto" gridAutoRows="1fr">
-                {inputConnectionFieldNames.map((fieldName, i) => (
+                {fieldNames.connectionFields.map((fieldName, i) => (
                   <GridItem gridColumnStart={1} gridRowStart={i + 1} key={`${nodeId}.${fieldName}.input-field`}>
-                    <InputField nodeId={nodeId} fieldName={fieldName} />
+                    <InvocationInputFieldCheck nodeId={nodeId} fieldName={fieldName}>
+                      <InputField nodeId={nodeId} fieldName={fieldName} />
+                    </InvocationInputFieldCheck>
                   </GridItem>
                 ))}
                 {outputFieldNames.map((fieldName, i) => (
@@ -52,8 +53,23 @@ const InvocationNode = ({ nodeId, isOpen, label, type, selected }: Props) => {
                   </GridItem>
                 ))}
               </Grid>
-              {inputAnyOrDirectFieldNames.map((fieldName) => (
-                <InputField key={`${nodeId}.${fieldName}.input-field`} nodeId={nodeId} fieldName={fieldName} />
+              {fieldNames.anyOrDirectFields.map((fieldName) => (
+                <InvocationInputFieldCheck
+                  key={`${nodeId}.${fieldName}.input-field`}
+                  nodeId={nodeId}
+                  fieldName={fieldName}
+                >
+                  <InputField nodeId={nodeId} fieldName={fieldName} />
+                </InvocationInputFieldCheck>
+              ))}
+              {fieldNames.missingFields.map((fieldName) => (
+                <InvocationInputFieldCheck
+                  key={`${nodeId}.${fieldName}.input-field`}
+                  nodeId={nodeId}
+                  fieldName={fieldName}
+                >
+                  <InputField nodeId={nodeId} fieldName={fieldName} />
+                </InvocationInputFieldCheck>
               ))}
             </Flex>
           </Flex>