Update invokeai_version.py

This prevents a minor visual bug where collapsed edges between collapsed nodes didn't display correctly on first load of a workflow.

docs/contributing/frontend/WORKFLOWS.md

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

docs/installation/010_INSTALL_AUTOMATED.md

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

docs/installation/020_INSTALL_MANUAL.md

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

invokeai/app/api/routers/images.py

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

invokeai/app/api_app.py

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

invokeai/app/invocations/controlnet_image_processors.py

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

invokeai/app/invocations/ip_adapter.py

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

invokeai/app/invocations/model.py

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

invokeai/app/invocations/sdxl.py

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

invokeai/app/invocations/t2i_adapter.py

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

invokeai/app/services/events/events_base.py

@@ -122,6 +122,8 @@ class EventServiceBase:
         source_node_id: str,
         error_type: str,
         error: str,
+        user_id: str | None,
+        project_id: str | None,
     ) -> None:
         """Emitted when an invocation has completed"""
         self.__emit_queue_event(
@@ -135,6 +137,8 @@ class EventServiceBase:
                 "source_node_id": source_node_id,
                 "error_type": error_type,
                 "error": error,
+                "user_id": user_id,
+                "project_id": project_id,
             },
         )
 

invokeai/app/services/image_files/image_files_base.py

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

invokeai/app/services/image_files/image_files_disk.py

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

invokeai/app/services/image_records/image_records_base.py

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

invokeai/app/services/image_records/image_records_sqlite.py

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

invokeai/app/services/images/images_base.py

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

invokeai/app/services/images/images_default.py

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

invokeai/app/services/session_processor/session_processor_default.py

@@ -237,6 +237,8 @@ class DefaultSessionProcessor(SessionProcessorBase):
                                 source_node_id=source_invocation_id,
                                 error_type=e.__class__.__name__,
                                 error=error,
+                                user_id=None,
+                                project_id=None,
                             )
                             pass
 

invokeai/app/services/shared/invocation_context.py

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

invokeai/frontend/web/.eslintrc.js

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

invokeai/frontend/web/.gitignore

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

invokeai/frontend/web/package.json

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

invokeai/frontend/web/pnpm-lock.yaml

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

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

@@ -774,10 +774,15 @@
         "cannotConnectOutputToOutput": "Cannot connect output to output",
         "cannotConnectToSelf": "Cannot connect to self",
         "cannotDuplicateConnection": "Cannot create duplicate connections",
+        "cannotMixAndMatchCollectionItemTypes": "Cannot mix and match collection item types",
+        "missingNode": "Missing invocation node",
+        "missingInvocationTemplate": "Missing invocation template",
+        "missingFieldTemplate": "Missing field template",
         "nodePack": "Node pack",
         "collection": "Collection",
-        "collectionFieldType": "{{name}} Collection",
-        "collectionOrScalarFieldType": "{{name}} Collection|Scalar",
+        "singleFieldType": "{{name}} (Single)",
+        "collectionFieldType": "{{name}} (Collection)",
+        "collectionOrScalarFieldType": "{{name}} (Single or Collection)",
         "colorCodeEdges": "Color-Code Edges",
         "colorCodeEdgesHelp": "Color-code edges according to their connected fields",
         "connectionWouldCreateCycle": "Connection would create a cycle",
@@ -879,6 +884,7 @@
         "versionUnknown": " Version Unknown",
         "workflow": "Workflow",
         "graph": "Graph",
+        "noGraph": "No Graph",
         "workflowAuthor": "Author",
         "workflowContact": "Contact",
         "workflowDescription": "Short Description",
@@ -946,7 +952,7 @@
                 "controlAdapterIncompatibleBaseModel": "incompatible Control Adapter base model",
                 "controlAdapterNoImageSelected": "no Control Adapter image selected",
                 "controlAdapterImageNotProcessed": "Control Adapter image not processed",
-                "t2iAdapterIncompatibleDimensions": "T2I Adapter requires image dimension to be multiples of 64",
+                "t2iAdapterIncompatibleDimensions": "T2I Adapter requires image dimension to be multiples of {{multiple}}",
                 "ipAdapterNoModelSelected": "no IP adapter selected",
                 "ipAdapterIncompatibleBaseModel": "incompatible IP Adapter base model",
                 "ipAdapterNoImageSelected": "no IP Adapter image selected",

invokeai/frontend/web/scripts/typegen.js

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

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

@@ -21,6 +21,7 @@ import i18n from 'i18n';
 import { size } from 'lodash-es';
 import { memo, useCallback, useEffect } from 'react';
 import { ErrorBoundary } from 'react-error-boundary';
+import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
 
 import AppErrorBoundaryFallback from './AppErrorBoundaryFallback';
 import PreselectedImage from './PreselectedImage';
@@ -46,6 +47,7 @@ const App = ({ config = DEFAULT_CONFIG, selectedImage }: Props) => {
   useSocketIO();
   useGlobalModifiersInit();
   useGlobalHotkeys();
+  useGetOpenAPISchemaQuery();
 
   const { dropzone, isHandlingUpload, setIsHandlingUpload } = useFullscreenDropzone();
 

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

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

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

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

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

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

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

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

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

@@ -1,5 +1,6 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { parseify } from 'common/util/serialize';
 import { canvasSavedToGallery } from 'features/canvas/store/actions';
 import { getBaseLayerBlob } from 'features/canvas/util/getBaseLayerBlob';
 import { addToast } from 'features/system/store/systemSlice';
@@ -43,6 +44,9 @@ export const addCanvasSavedToGalleryListener = (startAppListening: AppStartListe
             type: 'TOAST',
             toastOptions: { title: t('toast.canvasSavedGallery') },
           },
+          metadata: {
+            _canvas_objects: parseify(state.canvas.layerState.objects),
+          },
         })
       );
     },

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

@@ -16,6 +16,7 @@ import { CA_PROCESSOR_DATA } from 'features/controlLayers/util/controlAdapters';
 import { isImageOutput } from 'features/nodes/types/common';
 import { addToast } from 'features/system/store/systemSlice';
 import { t } from 'i18next';
+import { isEqual } from 'lodash-es';
 import { getImageDTO } from 'services/api/endpoints/images';
 import { queueApi } from 'services/api/endpoints/queue';
 import type { BatchConfig } from 'services/api/types';
@@ -47,8 +48,10 @@ const cancelProcessorBatch = async (dispatch: AppDispatch, layerId: string, batc
 export const addControlAdapterPreprocessor = (startAppListening: AppStartListening) => {
   startAppListening({
     matcher,
-    effect: async (action, { dispatch, getState, cancelActiveListeners, delay, take, signal }) => {
+    effect: async (action, { dispatch, getState, getOriginalState, cancelActiveListeners, delay, take, signal }) => {
       const layerId = caLayerRecalled.match(action) ? action.payload.id : action.payload.layerId;
+      const state = getState();
+      const originalState = getOriginalState();
 
       // Cancel any in-progress instances of this listener
       cancelActiveListeners();
@@ -57,21 +60,33 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
       // Delay before starting actual work
       await delay(DEBOUNCE_MS);
 
-      // Double-check that we are still eligible for processing
-      const state = getState();
       const layer = state.controlLayers.present.layers.filter(isControlAdapterLayer).find((l) => l.id === layerId);
 
-      // If we have no image or there is no processor config, bail
       if (!layer) {
         return;
       }
 
+      // We should only process if the processor settings or image have changed
+      const originalLayer = originalState.controlLayers.present.layers
+        .filter(isControlAdapterLayer)
+        .find((l) => l.id === layerId);
+      const originalImage = originalLayer?.controlAdapter.image;
+      const originalConfig = originalLayer?.controlAdapter.processorConfig;
+
       const image = layer.controlAdapter.image;
       const config = layer.controlAdapter.processorConfig;
 
+      if (isEqual(config, originalConfig) && isEqual(image, originalImage)) {
+        // Neither config nor image have changed, we can bail
+        return;
+      }
+
       if (!image || !config) {
-        // The user has reset the image or config, so we should clear the processed image
+        // - If we have no image, we have nothing to process
+        // - If we have no processor config, we have nothing to process
+        // Clear the processed image and bail
         dispatch(caLayerProcessedImageChanged({ layerId, imageDTO: null }));
+        return;
       }
 
       // At this point, the user has stopped fiddling with the processor settings and there is a processor selected.
@@ -81,8 +96,8 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
         cancelProcessorBatch(dispatch, layerId, layer.controlAdapter.processorPendingBatchId);
       }
 
-      // @ts-expect-error: TS isn't able to narrow the typing of buildNode and `config` will error...
-      const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config);
+      // TODO(psyche): I can't get TS to be happy, it thinkgs `config` is `never` but it should be inferred from the generic... I'll just cast it for now
+      const processorNode = CA_PROCESSOR_DATA[config.type].buildNode(image, config as never);
       const enqueueBatchArg: BatchConfig = {
         prepend: true,
         batch: {
@@ -148,7 +163,6 @@ export const addControlAdapterPreprocessor = (startAppListening: AppStartListeni
           log.trace('Control Adapter preprocessor cancelled');
         } else {
           // Some other error condition...
-          console.log(error);
           log.error({ enqueueBatchArg: parseify(enqueueBatchArg) }, t('queue.graphFailedToQueue'));
 
           if (error instanceof Object) {

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

@@ -1,5 +1,8 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates, upsertExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
 import { socketInvocationError } from 'services/events/actions';
 
 const log = logger('socketio');
@@ -9,6 +12,15 @@ export const addInvocationErrorEventListener = (startAppListening: AppStartListe
     actionCreator: socketInvocationError,
     effect: (action) => {
       log.error(action.payload, `Invocation error (${action.payload.data.node.type})`);
+      const { source_node_id } = action.payload.data;
+      const nes = deepClone($nodeExecutionStates.get()[source_node_id]);
+      if (nes) {
+        nes.status = zNodeStatus.enum.FAILED;
+        nes.error = action.payload.data.error;
+        nes.progress = null;
+        nes.progressImage = null;
+        upsertExecutionState(nes.nodeId, nes);
+      }
     },
   });
 };

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

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

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

@@ -1,5 +1,9 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
+import { deepClone } from 'common/util/deepClone';
+import { $nodeExecutionStates } from 'features/nodes/hooks/useExecutionState';
+import { zNodeStatus } from 'features/nodes/types/invocation';
+import { forEach } from 'lodash-es';
 import { queueApi, queueItemsAdapter } from 'services/api/endpoints/queue';
 import { socketQueueItemStatusChanged } from 'services/events/actions';
 
@@ -54,6 +58,21 @@ export const addSocketQueueItemStatusChangedEventListener = (startAppListening:
       dispatch(
         queueApi.util.invalidateTags(['CurrentSessionQueueItem', 'NextSessionQueueItem', 'InvocationCacheStatus'])
       );
+
+      if (['in_progress'].includes(action.payload.data.queue_item.status)) {
+        forEach($nodeExecutionStates.get(), (nes) => {
+          if (!nes) {
+            return;
+          }
+          const clone = deepClone(nes);
+          clone.status = zNodeStatus.enum.PENDING;
+          clone.error = null;
+          clone.progress = null;
+          clone.progressImage = null;
+          clone.outputs = [];
+          $nodeExecutionStates.setKey(clone.nodeId, clone);
+        });
+      }
     },
   });
 };

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

@@ -1,7 +1,7 @@
 import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { updateAllNodesRequested } from 'features/nodes/store/actions';
-import { nodeReplaced } from 'features/nodes/store/nodesSlice';
+import { $templates, nodesChanged } from 'features/nodes/store/nodesSlice';
 import { NodeUpdateError } from 'features/nodes/types/error';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 import { getNeedsUpdate, updateNode } from 'features/nodes/util/node/nodeUpdate';
@@ -14,7 +14,8 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
     actionCreator: updateAllNodesRequested,
     effect: (action, { dispatch, getState }) => {
       const log = logger('nodes');
-      const { nodes, templates } = getState().nodes;
+      const { nodes } = getState().nodes.present;
+      const templates = $templates.get();
 
       let unableToUpdateCount = 0;
 
@@ -24,13 +25,18 @@ export const addUpdateAllNodesRequestedListener = (startAppListening: AppStartLi
           unableToUpdateCount++;
           return;
         }
-        if (!getNeedsUpdate(node, template)) {
+        if (!getNeedsUpdate(node.data, template)) {
           // No need to increment the count here, since we're not actually updating
           return;
         }
         try {
           const updatedNode = updateNode(node, template);
-          dispatch(nodeReplaced({ nodeId: updatedNode.id, node: updatedNode }));
+          dispatch(
+            nodesChanged([
+              { type: 'remove', id: updatedNode.id },
+              { type: 'add', item: updatedNode },
+            ])
+          );
         } catch (e) {
           if (e instanceof NodeUpdateError) {
             unableToUpdateCount++;

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

@@ -2,32 +2,51 @@ import { logger } from 'app/logging/logger';
 import type { AppStartListening } from 'app/store/middleware/listenerMiddleware';
 import { parseify } from 'common/util/serialize';
 import { workflowLoaded, workflowLoadRequested } from 'features/nodes/store/actions';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { $flow } from 'features/nodes/store/reactFlowInstance';
+import type { Templates } from 'features/nodes/store/types';
 import { WorkflowMigrationError, WorkflowVersionError } from 'features/nodes/types/error';
+import { graphToWorkflow } from 'features/nodes/util/workflow/graphToWorkflow';
 import { validateWorkflow } from 'features/nodes/util/workflow/validateWorkflow';
 import { addToast } from 'features/system/store/systemSlice';
 import { makeToast } from 'features/system/util/makeToast';
 import { t } from 'i18next';
+import type { GraphAndWorkflowResponse, NonNullableGraph } from 'services/api/types';
 import { z } from 'zod';
 import { fromZodError } from 'zod-validation-error';
 
+const getWorkflow = (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);
+  } 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);
+  } else {
+    throw new Error('No workflow or graph provided');
+  }
+};
+
 export const addWorkflowLoadRequestedListener = (startAppListening: AppStartListening) => {
   startAppListening({
     actionCreator: workflowLoadRequested,
-    effect: (action, { dispatch, getState }) => {
+    effect: (action, { dispatch }) => {
       const log = logger('nodes');
-      const { workflow, asCopy } = action.payload;
-      const nodeTemplates = getState().nodes.templates;
+      const { data, asCopy } = action.payload;
+      const nodeTemplates = $templates.get();
 
       try {
-        const { workflow: validatedWorkflow, warnings } = validateWorkflow(workflow, nodeTemplates);
+        const { workflow, warnings } = getWorkflow(data, nodeTemplates);
 
         if (asCopy) {
           // If we're loading a copy, we need to remove the ID so that the backend will create a new workflow
-          delete validatedWorkflow.id;
+          delete workflow.id;
         }
 
-        dispatch(workflowLoaded(validatedWorkflow));
+        dispatch(workflowLoaded(workflow));
         if (!warnings.length) {
           dispatch(
             addToast(

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

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

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

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

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

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

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

@@ -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);

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

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

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

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

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

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

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

@@ -11,10 +11,12 @@ import { iiLayerAdded } from 'features/controlLayers/store/controlLayersSlice';
 import { imagesToDeleteSelected } from 'features/deleteImageModal/store/slice';
 import { useImageActions } from 'features/gallery/hooks/useImageActions';
 import { sentImageToCanvas, sentImageToImg2Img } from 'features/gallery/store/actions';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { selectOptimalDimension } from 'features/parameters/store/generationSlice';
 import { useFeatureStatus } from 'features/system/hooks/useFeatureStatus';
 import { setActiveTab } from 'features/ui/store/uiSlice';
 import { useGetAndLoadEmbeddedWorkflow } from 'features/workflowLibrary/hooks/useGetAndLoadEmbeddedWorkflow';
+import { size } from 'lodash-es';
 import { memo, useCallback } from 'react';
 import { flushSync } from 'react-dom';
 import { useTranslation } from 'react-i18next';
@@ -48,6 +50,7 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
   const isCanvasEnabled = useFeatureStatus('canvas');
   const customStarUi = useStore($customStarUI);
   const { downloadImage } = useDownloadImage();
+  const templates = useStore($templates);
 
   const { recallAll, remix, recallSeed, recallPrompts, hasMetadata, hasSeed, hasPrompts, isLoadingMetadata } =
     useImageActions(imageDTO?.image_name);
@@ -133,7 +136,7 @@ const SingleSelectionMenuItems = (props: SingleSelectionMenuItemsProps) => {
       <MenuItem
         icon={getAndLoadEmbeddedWorkflowResult.isLoading ? <SpinnerIcon /> : <PiFlowArrowBold />}
         onClickCapture={handleLoadWorkflow}
-        isDisabled={!imageDTO.has_workflow}
+        isDisabled={!imageDTO.has_workflow || !size(templates)}
       >
         {t('nodes.loadWorkflow')}
       </MenuItem>

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

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

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

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

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

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

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

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

invokeai/frontend/web/src/features/lora/components/LoRACard.tsx

@@ -75,8 +75,8 @@ export const LoRACard = memo((props: LoRACardProps) => {
           <CompositeNumberInput
             value={lora.weight}
             onChange={handleChange}
-            min={-5}
-            max={5}
+            min={-10}
+            max={10}
             step={0.01}
             w={20}
             flexShrink={0}

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

@@ -2,26 +2,36 @@ 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 { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useAppDispatch, useAppStore } from 'app/store/storeHooks';
 import type { SelectInstance } from 'chakra-react-select';
 import { useBuildNode } from 'features/nodes/hooks/useBuildNode';
 import {
-  addNodePopoverClosed,
-  addNodePopoverOpened,
-  nodeAdded,
-  selectNodesSlice,
+  $cursorPos,
+  $edgePendingUpdate,
+  $isAddNodePopoverOpen,
+  $pendingConnection,
+  $templates,
+  closeAddNodePopover,
+  edgesChanged,
+  nodesChanged,
+  openAddNodePopover,
 } from 'features/nodes/store/nodesSlice';
-import { validateSourceAndTargetTypes } from 'features/nodes/store/util/validateSourceAndTargetTypes';
+import { findUnoccupiedPosition } from 'features/nodes/store/util/findUnoccupiedPosition';
+import { getFirstValidConnection } from 'features/nodes/store/util/getFirstValidConnection';
+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 { filter, map, memoize, some } from 'lodash-es';
-import type { KeyboardEventHandler } from 'react';
-import { memo, useCallback, useRef } from 'react';
+import { memo, useCallback, useMemo, useRef } from 'react';
 import { flushSync } from 'react-dom';
 import { useHotkeys } from 'react-hotkeys-hook';
 import type { HotkeyCallback } from 'react-hotkeys-hook/dist/types';
 import { useTranslation } from 'react-i18next';
 import type { FilterOptionOption } from 'react-select/dist/declarations/src/filters';
+import type { EdgeChange, NodeChange } from 'reactflow';
 
 const createRegex = memoize(
   (inputValue: string) =>
@@ -54,26 +64,32 @@ const AddNodePopover = () => {
   const { t } = useTranslation();
   const selectRef = useRef<SelectInstance<ComboboxOption> | null>(null);
   const inputRef = useRef<HTMLInputElement>(null);
+  const templates = useStore($templates);
+  const pendingConnection = useStore($pendingConnection);
+  const isOpen = useStore($isAddNodePopoverOpen);
+  const store = useAppStore();
 
-  const fieldFilter = useAppSelector((s) => s.nodes.connectionStartFieldType);
-  const handleFilter = useAppSelector((s) => s.nodes.connectionStartParams?.handleType);
-
-  const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
+  const filteredTemplates = useMemo(() => {
     // If we have a connection in progress, we need to filter the node choices
-    const filteredNodeTemplates = fieldFilter
-      ? filter(nodes.templates, (template) => {
-          const handles = handleFilter === 'source' ? template.inputs : template.outputs;
+    const templatesArray = map(templates);
+    if (!pendingConnection) {
+      return templatesArray;
+    }
 
-          return some(handles, (handle) => {
-            const sourceType = handleFilter === 'source' ? fieldFilter : handle.type;
-            const targetType = handleFilter === 'target' ? fieldFilter : handle.type;
+    return filter(templates, (template) => {
+      const candidateFields = pendingConnection.handleType === 'source' ? template.inputs : template.outputs;
+      return some(candidateFields, (field) => {
+        const sourceType =
+          pendingConnection.handleType === 'source' ? field.type : pendingConnection.fieldTemplate.type;
+        const targetType =
+          pendingConnection.handleType === 'target' ? field.type : pendingConnection.fieldTemplate.type;
+        return validateConnectionTypes(sourceType, targetType);
+      });
+    });
+  }, [templates, pendingConnection]);
 
-            return validateSourceAndTargetTypes(sourceType, targetType);
-          });
-        })
-      : map(nodes.templates);
-
-    const options: ComboboxOption[] = map(filteredNodeTemplates, (template) => {
+  const options = useMemo(() => {
+    const _options: ComboboxOption[] = map(filteredTemplates, (template) => {
       return {
         label: template.title,
         value: template.type,
@@ -83,15 +99,15 @@ const AddNodePopover = () => {
     });
 
     //We only want these nodes if we're not filtered
-    if (fieldFilter === null) {
-      options.push({
+    if (!pendingConnection) {
+      _options.push({
         label: t('nodes.currentImage'),
         value: 'current_image',
         description: t('nodes.currentImageDescription'),
         tags: ['progress'],
       });
 
-      options.push({
+      _options.push({
         label: t('nodes.notes'),
         value: 'notes',
         description: t('nodes.notesDescription'),
@@ -99,18 +115,15 @@ const AddNodePopover = () => {
       });
     }
 
-    options.sort((a, b) => a.label.localeCompare(b.label));
+    _options.sort((a, b) => a.label.localeCompare(b.label));
 
-    return { options };
-  });
-
-  const { options } = useAppSelector(selector);
-  const isOpen = useAppSelector((s) => s.nodes.isAddNodePopoverOpen);
+    return _options;
+  }, [filteredTemplates, pendingConnection, t]);
 
   const addNode = useCallback(
-    (nodeType: string) => {
-      const invocation = buildInvocation(nodeType);
-      if (!invocation) {
+    (nodeType: string): AnyNode | null => {
+      const node = buildInvocation(nodeType);
+      if (!node) {
         const errorMessage = t('nodes.unknownNode', {
           nodeType: nodeType,
         });
@@ -118,12 +131,39 @@ const AddNodePopover = () => {
           status: 'error',
           title: errorMessage,
         });
-        return;
+        return null;
       }
 
-      dispatch(nodeAdded(invocation));
+      // Find a cozy spot for the node
+      const cursorPos = $cursorPos.get();
+      const { nodes, edges } = store.getState().nodes.present;
+      node.position = findUnoccupiedPosition(nodes, cursorPos?.x ?? node.position.x, cursorPos?.y ?? node.position.y);
+      node.selected = true;
+
+      // Deselect all other nodes and edges
+      const nodeChanges: NodeChange[] = [{ type: 'add', item: node }];
+      const edgeChanges: EdgeChange[] = [];
+      nodes.forEach(({ id, selected }) => {
+        if (selected) {
+          nodeChanges.push({ type: 'select', id, selected: false });
+        }
+      });
+      edges.forEach(({ id, selected }) => {
+        if (selected) {
+          edgeChanges.push({ type: 'select', id, selected: false });
+        }
+      });
+
+      // Onwards!
+      if (nodeChanges.length > 0) {
+        dispatch(nodesChanged(nodeChanges));
+      }
+      if (edgeChanges.length > 0) {
+        dispatch(edgesChanged(edgeChanges));
+      }
+      return node;
     },
-    [dispatch, buildInvocation, toaster, t]
+    [buildInvocation, store, dispatch, t, toaster]
   );
 
   const onChange = useCallback<ComboboxOnChange>(
@@ -131,52 +171,65 @@ const AddNodePopover = () => {
       if (!v) {
         return;
       }
-      addNode(v.value);
-      dispatch(addNodePopoverClosed());
+      const node = addNode(v.value);
+
+      // Auto-connect an edge if we just added a node and have a pending connection
+      if (pendingConnection && isInvocationNode(node)) {
+        const edgePendingUpdate = $edgePendingUpdate.get();
+        const { handleType } = pendingConnection;
+
+        const source = handleType === 'source' ? pendingConnection.nodeId : node.id;
+        const sourceHandle = handleType === 'source' ? pendingConnection.handleId : null;
+        const target = handleType === 'target' ? pendingConnection.nodeId : node.id;
+        const targetHandle = handleType === 'target' ? pendingConnection.handleId : null;
+
+        const { nodes, edges } = store.getState().nodes.present;
+        const connection = getFirstValidConnection(
+          source,
+          sourceHandle,
+          target,
+          targetHandle,
+          nodes,
+          edges,
+          templates,
+          edgePendingUpdate
+        );
+        if (connection) {
+          const newEdge = connectionToEdge(connection);
+          dispatch(edgesChanged([{ type: 'add', item: newEdge }]));
+        }
+      }
+
+      closeAddNodePopover();
     },
-    [addNode, dispatch]
+    [addNode, dispatch, pendingConnection, store, templates]
   );
 
-  const onClose = useCallback(() => {
-    dispatch(addNodePopoverClosed());
-  }, [dispatch]);
-
-  const onOpen = useCallback(() => {
-    dispatch(addNodePopoverOpened());
-  }, [dispatch]);
-
-  const handleHotkeyOpen: HotkeyCallback = useCallback(
-    (e) => {
+  const handleHotkeyOpen: HotkeyCallback = useCallback((e) => {
+    if (!$isAddNodePopoverOpen.get()) {
       e.preventDefault();
-      onOpen();
+      openAddNodePopover();
       flushSync(() => {
         selectRef.current?.inputRef?.focus();
       });
-    },
-    [onOpen]
-  );
+    }
+  }, []);
 
   const handleHotkeyClose: HotkeyCallback = useCallback(() => {
-    onClose();
-  }, [onClose]);
+    if ($isAddNodePopoverOpen.get()) {
+      closeAddNodePopover();
+    }
+  }, []);
 
   useHotkeys(['shift+a', 'space'], handleHotkeyOpen);
-  useHotkeys(['escape'], handleHotkeyClose);
-  const onKeyDown: KeyboardEventHandler = useCallback(
-    (e) => {
-      if (e.key === 'Escape') {
-        onClose();
-      }
-    },
-    [onClose]
-  );
+  useHotkeys(['escape'], handleHotkeyClose, { enableOnFormTags: ['TEXTAREA'] });
 
   const noOptionsMessage = useCallback(() => t('nodes.noMatchingNodes'), [t]);
 
   return (
     <Popover
       isOpen={isOpen}
-      onClose={onClose}
+      onClose={closeAddNodePopover}
       placement="bottom"
       openDelay={0}
       closeDelay={0}
@@ -206,8 +259,7 @@ const AddNodePopover = () => {
             noOptionsMessage={noOptionsMessage}
             filterOption={filterOption}
             onChange={onChange}
-            onMenuClose={onClose}
-            onKeyDown={onKeyDown}
+            onMenuClose={closeAddNodePopover}
             inputRef={inputRef}
             closeMenuOnSelect={false}
           />

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

@@ -1,47 +1,42 @@
 import { useGlobalMenuClose, useToken } from '@invoke-ai/ui-library';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useStore } from '@nanostores/react';
+import { useAppDispatch, useAppSelector, useAppStore } from 'app/store/storeHooks';
+import { useConnection } from 'features/nodes/hooks/useConnection';
+import { useCopyPaste } from 'features/nodes/hooks/useCopyPaste';
+import { useSyncExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { useIsValidConnection } from 'features/nodes/hooks/useIsValidConnection';
-import { $mouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
 import { useWorkflowWatcher } from 'features/nodes/hooks/useWorkflowWatcher';
 import {
-  connectionEnded,
-  connectionMade,
-  connectionStarted,
-  edgeAdded,
-  edgeChangeStarted,
-  edgeDeleted,
+  $cursorPos,
+  $didUpdateEdge,
+  $edgePendingUpdate,
+  $isAddNodePopoverOpen,
+  $lastEdgeUpdateMouseEvent,
+  $pendingConnection,
+  $viewport,
   edgesChanged,
-  edgesDeleted,
   nodesChanged,
-  nodesDeleted,
-  selectedAll,
-  selectedEdgesChanged,
-  selectedNodesChanged,
-  selectionCopied,
-  selectionPasted,
-  viewportChanged,
+  redo,
+  undo,
 } from 'features/nodes/store/nodesSlice';
 import { $flow } from 'features/nodes/store/reactFlowInstance';
+import { connectionToEdge } from 'features/nodes/store/util/reactFlowUtil';
 import type { CSSProperties, MouseEvent } from 'react';
 import { memo, useCallback, useMemo, useRef } from 'react';
 import { useHotkeys } from 'react-hotkeys-hook';
 import type {
-  OnConnect,
-  OnConnectEnd,
-  OnConnectStart,
+  EdgeChange,
+  NodeChange,
   OnEdgesChange,
-  OnEdgesDelete,
   OnEdgeUpdateFunc,
   OnInit,
   OnMoveEnd,
   OnNodesChange,
-  OnNodesDelete,
-  OnSelectionChangeFunc,
   ProOptions,
   ReactFlowProps,
-  XYPosition,
+  ReactFlowState,
 } from 'reactflow';
-import { Background, ReactFlow } from 'reactflow';
+import { Background, ReactFlow, useStore as useReactFlowStore, useUpdateNodeInternals } from 'reactflow';
 
 import CustomConnectionLine from './connectionLines/CustomConnectionLine';
 import InvocationCollapsedEdge from './edges/InvocationCollapsedEdge';
@@ -50,8 +45,6 @@ import CurrentImageNode from './nodes/CurrentImage/CurrentImageNode';
 import InvocationNodeWrapper from './nodes/Invocation/InvocationNodeWrapper';
 import NotesNode from './nodes/Notes/NotesNode';
 
-const DELETE_KEYS = ['Delete', 'Backspace'];
-
 const edgeTypes = {
   collapsed: InvocationCollapsedEdge,
   default: InvocationDefaultEdge,
@@ -68,17 +61,25 @@ const proOptions: ProOptions = { hideAttribution: true };
 
 const snapGrid: [number, number] = [25, 25];
 
+const selectCancelConnection = (state: ReactFlowState) => state.cancelConnection;
+
 export const Flow = memo(() => {
   const dispatch = useAppDispatch();
-  const nodes = useAppSelector((s) => s.nodes.nodes);
-  const edges = useAppSelector((s) => s.nodes.edges);
-  const viewport = useAppSelector((s) => s.nodes.viewport);
-  const shouldSnapToGrid = useAppSelector((s) => s.nodes.shouldSnapToGrid);
-  const selectionMode = useAppSelector((s) => s.nodes.selectionMode);
+  const nodes = useAppSelector((s) => s.nodes.present.nodes);
+  const edges = useAppSelector((s) => s.nodes.present.edges);
+  const viewport = useStore($viewport);
+  const mayUndo = useAppSelector((s) => s.nodes.past.length > 0);
+  const mayRedo = useAppSelector((s) => s.nodes.future.length > 0);
+  const shouldSnapToGrid = useAppSelector((s) => s.workflowSettings.shouldSnapToGrid);
+  const selectionMode = useAppSelector((s) => s.workflowSettings.selectionMode);
+  const { onConnectStart, onConnect, onConnectEnd } = useConnection();
   const flowWrapper = useRef<HTMLDivElement>(null);
-  const cursorPosition = useRef<XYPosition | null>(null);
   const isValidConnection = useIsValidConnection();
+  const cancelConnection = useReactFlowStore(selectCancelConnection);
+  const updateNodeInternals = useUpdateNodeInternals();
+  const store = useAppStore();
   useWorkflowWatcher();
+  useSyncExecutionState();
   const [borderRadius] = useToken('radii', ['base']);
 
   const flowStyles = useMemo<CSSProperties>(
@@ -89,73 +90,24 @@ export const Flow = memo(() => {
   );
 
   const onNodesChange: OnNodesChange = useCallback(
-    (changes) => {
-      dispatch(nodesChanged(changes));
+    (nodeChanges) => {
+      dispatch(nodesChanged(nodeChanges));
     },
     [dispatch]
   );
 
   const onEdgesChange: OnEdgesChange = useCallback(
     (changes) => {
-      dispatch(edgesChanged(changes));
+      if (changes.length > 0) {
+        dispatch(edgesChanged(changes));
+      }
     },
     [dispatch]
   );
 
-  const onConnectStart: OnConnectStart = useCallback(
-    (event, params) => {
-      dispatch(connectionStarted(params));
-    },
-    [dispatch]
-  );
-
-  const onConnect: OnConnect = useCallback(
-    (connection) => {
-      dispatch(connectionMade(connection));
-    },
-    [dispatch]
-  );
-
-  const onConnectEnd: OnConnectEnd = useCallback(() => {
-    if (!cursorPosition.current) {
-      return;
-    }
-    dispatch(
-      connectionEnded({
-        cursorPosition: cursorPosition.current,
-        mouseOverNodeId: $mouseOverNode.get(),
-      })
-    );
-  }, [dispatch]);
-
-  const onEdgesDelete: OnEdgesDelete = useCallback(
-    (edges) => {
-      dispatch(edgesDeleted(edges));
-    },
-    [dispatch]
-  );
-
-  const onNodesDelete: OnNodesDelete = useCallback(
-    (nodes) => {
-      dispatch(nodesDeleted(nodes));
-    },
-    [dispatch]
-  );
-
-  const handleSelectionChange: OnSelectionChangeFunc = useCallback(
-    ({ nodes, edges }) => {
-      dispatch(selectedNodesChanged(nodes ? nodes.map((n) => n.id) : []));
-      dispatch(selectedEdgesChanged(edges ? edges.map((e) => e.id) : []));
-    },
-    [dispatch]
-  );
-
-  const handleMoveEnd: OnMoveEnd = useCallback(
-    (e, viewport) => {
-      dispatch(viewportChanged(viewport));
-    },
-    [dispatch]
-  );
+  const handleMoveEnd: OnMoveEnd = useCallback((e, viewport) => {
+    $viewport.set(viewport);
+  }, []);
 
   const { onCloseGlobal } = useGlobalMenuClose();
   const handlePaneClick = useCallback(() => {
@@ -169,11 +121,12 @@ export const Flow = memo(() => {
 
   const onMouseMove = useCallback((event: MouseEvent<HTMLDivElement>) => {
     if (flowWrapper.current?.getBoundingClientRect()) {
-      cursorPosition.current =
+      $cursorPos.set(
         $flow.get()?.screenToFlowPosition({
           x: event.clientX,
           y: event.clientY,
-        }) ?? null;
+        }) ?? null
+      );
     }
   }, []);
 
@@ -189,67 +142,157 @@ export const Flow = memo(() => {
    *   where the edge is deleted if you click it accidentally).
    */
 
-  // We have a ref for cursor position, but it is the *projected* cursor position.
-  // Easiest to just keep track of the last mouse event for this particular feature
-  const edgeUpdateMouseEvent = useRef<MouseEvent>();
-
-  const onEdgeUpdateStart: NonNullable<ReactFlowProps['onEdgeUpdateStart']> = useCallback(
-    (e, edge, _handleType) => {
-      // update mouse event
-      edgeUpdateMouseEvent.current = e;
-      // always delete the edge when starting an updated
-      dispatch(edgeDeleted(edge.id));
-      dispatch(edgeChangeStarted());
-    },
-    [dispatch]
-  );
+  const onEdgeUpdateStart: NonNullable<ReactFlowProps['onEdgeUpdateStart']> = useCallback((e, edge, _handleType) => {
+    $edgePendingUpdate.set(edge);
+    $didUpdateEdge.set(false);
+    $lastEdgeUpdateMouseEvent.set(e);
+  }, []);
 
   const onEdgeUpdate: OnEdgeUpdateFunc = useCallback(
-    (_oldEdge, newConnection) => {
-      // instead of updating the edge (we deleted it earlier), we instead create
-      // a new one.
-      dispatch(connectionMade(newConnection));
+    (oldEdge, newConnection) => {
+      // This event is fired when an edge update is successful
+      $didUpdateEdge.set(true);
+      // When an edge update is successful, we need to delete the old edge and create a new one
+      const newEdge = connectionToEdge(newConnection);
+      dispatch(
+        edgesChanged([
+          { type: 'remove', id: oldEdge.id },
+          { type: 'add', item: newEdge },
+        ])
+      );
+      // Because we shift the position of handles depending on whether a field is connected or not, we must use
+      // updateNodeInternals to tell reactflow to recalculate the positions of the handles
+      updateNodeInternals([oldEdge.source, oldEdge.target, newEdge.source, newEdge.target]);
     },
-    [dispatch]
+    [dispatch, updateNodeInternals]
   );
 
   const onEdgeUpdateEnd: NonNullable<ReactFlowProps['onEdgeUpdateEnd']> = useCallback(
     (e, edge, _handleType) => {
-      // Handle the case where user begins a drag but didn't move the cursor -
-      // bc we deleted the edge, we need to add it back
-      if (
-        // ignore touch events
-        !('touches' in e) &&
-        edgeUpdateMouseEvent.current?.clientX === e.clientX &&
-        edgeUpdateMouseEvent.current?.clientY === e.clientY
-      ) {
-        dispatch(edgeAdded(edge));
+      const didUpdateEdge = $didUpdateEdge.get();
+      // Fall back to a reasonable default event
+      const lastEvent = $lastEdgeUpdateMouseEvent.get() ?? { clientX: 0, clientY: 0 };
+      // We have to narrow this event down to MouseEvents - could be TouchEvent
+      const didMouseMove =
+        !('touches' in e) && Math.hypot(e.clientX - lastEvent.clientX, e.clientY - lastEvent.clientY) > 5;
+
+      // If we got this far and did not successfully update an edge, and the mouse moved away from the handle,
+      // the user probably intended to delete the edge
+      if (!didUpdateEdge && didMouseMove) {
+        dispatch(edgesChanged([{ type: 'remove', id: edge.id }]));
       }
-      // reset mouse event
-      edgeUpdateMouseEvent.current = undefined;
+
+      $edgePendingUpdate.set(null);
+      $didUpdateEdge.set(false);
+      $pendingConnection.set(null);
+      $lastEdgeUpdateMouseEvent.set(null);
     },
     [dispatch]
   );
 
   // #endregion
 
-  useHotkeys(['Ctrl+c', 'Meta+c'], (e) => {
-    e.preventDefault();
-    dispatch(selectionCopied());
-  });
+  const { copySelection, pasteSelection } = useCopyPaste();
 
-  useHotkeys(['Ctrl+a', 'Meta+a'], (e) => {
-    e.preventDefault();
-    dispatch(selectedAll());
-  });
+  const onCopyHotkey = useCallback(
+    (e: KeyboardEvent) => {
+      e.preventDefault();
+      copySelection();
+    },
+    [copySelection]
+  );
+  useHotkeys(['Ctrl+c', 'Meta+c'], onCopyHotkey);
 
-  useHotkeys(['Ctrl+v', 'Meta+v'], (e) => {
-    if (!cursorPosition.current) {
-      return;
+  const onSelectAllHotkey = useCallback(
+    (e: KeyboardEvent) => {
+      e.preventDefault();
+      const { nodes, edges } = store.getState().nodes.present;
+      const nodeChanges: NodeChange[] = [];
+      const edgeChanges: EdgeChange[] = [];
+      nodes.forEach(({ id, selected }) => {
+        if (!selected) {
+          nodeChanges.push({ type: 'select', id, selected: true });
+        }
+      });
+      edges.forEach(({ id, selected }) => {
+        if (!selected) {
+          edgeChanges.push({ type: 'select', id, selected: true });
+        }
+      });
+      if (nodeChanges.length > 0) {
+        dispatch(nodesChanged(nodeChanges));
+      }
+      if (edgeChanges.length > 0) {
+        dispatch(edgesChanged(edgeChanges));
+      }
+    },
+    [dispatch, store]
+  );
+  useHotkeys(['Ctrl+a', 'Meta+a'], onSelectAllHotkey);
+
+  const onPasteHotkey = useCallback(
+    (e: KeyboardEvent) => {
+      e.preventDefault();
+      pasteSelection();
+    },
+    [pasteSelection]
+  );
+  useHotkeys(['Ctrl+v', 'Meta+v'], onPasteHotkey);
+
+  const onPasteWithEdgesToNodesHotkey = useCallback(
+    (e: KeyboardEvent) => {
+      e.preventDefault();
+      pasteSelection(true);
+    },
+    [pasteSelection]
+  );
+  useHotkeys(['Ctrl+shift+v', 'Meta+shift+v'], onPasteWithEdgesToNodesHotkey);
+
+  const onUndoHotkey = useCallback(() => {
+    if (mayUndo) {
+      dispatch(undo());
     }
-    e.preventDefault();
-    dispatch(selectionPasted({ cursorPosition: cursorPosition.current }));
-  });
+  }, [dispatch, mayUndo]);
+  useHotkeys(['meta+z', 'ctrl+z'], onUndoHotkey);
+
+  const onRedoHotkey = useCallback(() => {
+    if (mayRedo) {
+      dispatch(redo());
+    }
+  }, [dispatch, mayRedo]);
+  useHotkeys(['meta+shift+z', 'ctrl+shift+z'], onRedoHotkey);
+
+  const onEscapeHotkey = useCallback(() => {
+    if (!$edgePendingUpdate.get()) {
+      $pendingConnection.set(null);
+      $isAddNodePopoverOpen.set(false);
+      cancelConnection();
+    }
+  }, [cancelConnection]);
+  useHotkeys('esc', onEscapeHotkey);
+
+  const onDeleteHotkey = useCallback(() => {
+    const { nodes, edges } = store.getState().nodes.present;
+    const nodeChanges: NodeChange[] = [];
+    const edgeChanges: EdgeChange[] = [];
+    nodes
+      .filter((n) => n.selected)
+      .forEach(({ id }) => {
+        nodeChanges.push({ type: 'remove', id });
+      });
+    edges
+      .filter((e) => e.selected)
+      .forEach(({ id }) => {
+        edgeChanges.push({ type: 'remove', id });
+      });
+    if (nodeChanges.length > 0) {
+      dispatch(nodesChanged(nodeChanges));
+    }
+    if (edgeChanges.length > 0) {
+      dispatch(edgesChanged(edgeChanges));
+    }
+  }, [dispatch, store]);
+  useHotkeys(['delete', 'backspace'], onDeleteHotkey);
 
   return (
     <ReactFlow
@@ -264,17 +307,14 @@ export const Flow = memo(() => {
       onMouseMove={onMouseMove}
       onNodesChange={onNodesChange}
       onEdgesChange={onEdgesChange}
-      onEdgesDelete={onEdgesDelete}
       onEdgeUpdate={onEdgeUpdate}
       onEdgeUpdateStart={onEdgeUpdateStart}
       onEdgeUpdateEnd={onEdgeUpdateEnd}
-      onNodesDelete={onNodesDelete}
       onConnectStart={onConnectStart}
       onConnect={onConnect}
       onConnectEnd={onConnectEnd}
       onMoveEnd={handleMoveEnd}
       connectionLineComponent={CustomConnectionLine}
-      onSelectionChange={handleSelectionChange}
       isValidConnection={isValidConnection}
       minZoom={0.1}
       snapToGrid={shouldSnapToGrid}
@@ -283,8 +323,10 @@ export const Flow = memo(() => {
       proOptions={proOptions}
       style={flowStyles}
       onPaneClick={handlePaneClick}
-      deleteKeyCode={DELETE_KEYS}
+      deleteKeyCode={null}
       selectionMode={selectionMode}
+      elevateEdgesOnSelect
+      nodeDragThreshold={1}
     >
       <Background />
     </ReactFlow>

invokeai/frontend/web/src/features/nodes/components/flow/connectionLines/CustomConnectionLine.tsx

@@ -1,26 +1,33 @@
-import { createSelector } from '@reduxjs/toolkit';
+import { useStore } from '@nanostores/react';
 import { useAppSelector } from 'app/store/storeHooks';
 import { colorTokenToCssVar } from 'common/util/colorTokenToCssVar';
 import { getFieldColor } from 'features/nodes/components/flow/edges/util/getEdgeColor';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { $pendingConnection } from 'features/nodes/store/nodesSlice';
 import type { CSSProperties } from 'react';
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
 import type { ConnectionLineComponentProps } from 'reactflow';
 import { getBezierPath } from 'reactflow';
 
-const selectStroke = createSelector(selectNodesSlice, (nodes) =>
-  nodes.shouldColorEdges ? getFieldColor(nodes.connectionStartFieldType) : colorTokenToCssVar('base.500')
-);
-
-const selectClassName = createSelector(selectNodesSlice, (nodes) =>
-  nodes.shouldAnimateEdges ? 'react-flow__custom_connection-path animated' : 'react-flow__custom_connection-path'
-);
-
 const pathStyles: CSSProperties = { opacity: 0.8 };
 
 const CustomConnectionLine = ({ fromX, fromY, fromPosition, toX, toY, toPosition }: ConnectionLineComponentProps) => {
-  const stroke = useAppSelector(selectStroke);
-  const className = useAppSelector(selectClassName);
+  const pendingConnection = useStore($pendingConnection);
+  const shouldColorEdges = useAppSelector((state) => state.workflowSettings.shouldColorEdges);
+  const shouldAnimateEdges = useAppSelector((state) => state.workflowSettings.shouldAnimateEdges);
+  const stroke = useMemo(() => {
+    if (shouldColorEdges && pendingConnection) {
+      return getFieldColor(pendingConnection.fieldTemplate.type);
+    } else {
+      return colorTokenToCssVar('base.500');
+    }
+  }, [pendingConnection, shouldColorEdges]);
+  const className = useMemo(() => {
+    if (shouldAnimateEdges) {
+      return 'react-flow__custom_connection-path animated';
+    } else {
+      return 'react-flow__custom_connection-path';
+    }
+  }, [shouldAnimateEdges]);
 
   const pathParams = {
     sourceX: fromX,

invokeai/frontend/web/src/features/nodes/components/flow/edges/InvocationCollapsedEdge.tsx

@@ -1,12 +1,14 @@
 import { Badge, Flex } from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
 import { useAppSelector } from 'app/store/storeHooks';
 import { useChakraThemeTokens } from 'common/hooks/useChakraThemeTokens';
+import { getEdgeStyles } from 'features/nodes/components/flow/edges/util/getEdgeColor';
+import { makeEdgeSelector } from 'features/nodes/components/flow/edges/util/makeEdgeSelector';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { memo, useMemo } from 'react';
 import type { EdgeProps } from 'reactflow';
 import { BaseEdge, EdgeLabelRenderer, getBezierPath } from 'reactflow';
 
-import { makeEdgeSelector } from './util/makeEdgeSelector';
-
 const InvocationCollapsedEdge = ({
   sourceX,
   sourceY,
@@ -16,18 +18,19 @@ const InvocationCollapsedEdge = ({
   targetPosition,
   markerEnd,
   data,
-  selected,
+  selected = false,
   source,
-  target,
   sourceHandleId,
+  target,
   targetHandleId,
 }: EdgeProps<{ count: number }>) => {
+  const templates = useStore($templates);
   const selector = useMemo(
-    () => makeEdgeSelector(source, sourceHandleId, target, targetHandleId, selected),
-    [selected, source, sourceHandleId, target, targetHandleId]
+    () => makeEdgeSelector(templates, source, sourceHandleId, target, targetHandleId),
+    [templates, source, sourceHandleId, target, targetHandleId]
   );
 
-  const { isSelected, shouldAnimate } = useAppSelector(selector);
+  const { shouldAnimateEdges, areConnectedNodesSelected } = useAppSelector(selector);
 
   const [edgePath, labelX, labelY] = getBezierPath({
     sourceX,
@@ -41,14 +44,8 @@ const InvocationCollapsedEdge = ({
   const { base500 } = useChakraThemeTokens();
 
   const edgeStyles = useMemo(
-    () => ({
-      strokeWidth: isSelected ? 3 : 2,
-      stroke: base500,
-      opacity: isSelected ? 0.8 : 0.5,
-      animation: shouldAnimate ? 'dashdraw 0.5s linear infinite' : undefined,
-      strokeDasharray: shouldAnimate ? 5 : 'none',
-    }),
-    [base500, isSelected, shouldAnimate]
+    () => getEdgeStyles(base500, selected, shouldAnimateEdges, areConnectedNodesSelected),
+    [areConnectedNodesSelected, base500, selected, shouldAnimateEdges]
   );
 
   return (
@@ -57,11 +54,15 @@ const InvocationCollapsedEdge = ({
       {data?.count && data.count > 1 && (
         <EdgeLabelRenderer>
           <Flex
+            data-testid="asdfasdfasdf"
             position="absolute"
             transform={`translate(-50%, -50%) translate(${labelX}px,${labelY}px)`}
             className="nodrag nopan"
+            // Unfortunately edge labels do not get the same zIndex treatment as edges do, so we need to manage this ourselves
+            // See: https://github.com/xyflow/xyflow/issues/3658
+            zIndex={1001}
           >
-            <Badge variant="solid" bg="base.500" opacity={isSelected ? 0.8 : 0.5} boxShadow="base">
+            <Badge variant="solid" bg="base.500" opacity={selected ? 0.8 : 0.5} boxShadow="base">
               {data.count}
             </Badge>
           </Flex>

invokeai/frontend/web/src/features/nodes/components/flow/edges/InvocationDefaultEdge.tsx

@@ -1,6 +1,8 @@
 import { Flex, Text } from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
 import { useAppSelector } from 'app/store/storeHooks';
-import type { CSSProperties } from 'react';
+import { getEdgeStyles } from 'features/nodes/components/flow/edges/util/getEdgeColor';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { memo, useMemo } from 'react';
 import type { EdgeProps } from 'reactflow';
 import { BaseEdge, EdgeLabelRenderer, getBezierPath } from 'reactflow';
@@ -15,19 +17,20 @@ const InvocationDefaultEdge = ({
   sourcePosition,
   targetPosition,
   markerEnd,
-  selected,
+  selected = false,
   source,
   target,
   sourceHandleId,
   targetHandleId,
 }: EdgeProps) => {
+  const templates = useStore($templates);
   const selector = useMemo(
-    () => makeEdgeSelector(source, sourceHandleId, target, targetHandleId, selected),
-    [source, sourceHandleId, target, targetHandleId, selected]
+    () => makeEdgeSelector(templates, source, sourceHandleId, target, targetHandleId),
+    [templates, source, sourceHandleId, target, targetHandleId]
   );
 
-  const { isSelected, shouldAnimate, stroke, label } = useAppSelector(selector);
-  const shouldShowEdgeLabels = useAppSelector((s) => s.nodes.shouldShowEdgeLabels);
+  const { shouldAnimateEdges, areConnectedNodesSelected, stroke, label } = useAppSelector(selector);
+  const shouldShowEdgeLabels = useAppSelector((s) => s.workflowSettings.shouldShowEdgeLabels);
 
   const [edgePath, labelX, labelY] = getBezierPath({
     sourceX,
@@ -38,15 +41,9 @@ const InvocationDefaultEdge = ({
     targetPosition,
   });
 
-  const edgeStyles = useMemo<CSSProperties>(
-    () => ({
-      strokeWidth: isSelected ? 3 : 2,
-      stroke,
-      opacity: isSelected ? 0.8 : 0.5,
-      animation: shouldAnimate ? 'dashdraw 0.5s linear infinite' : undefined,
-      strokeDasharray: shouldAnimate ? 5 : 'none',
-    }),
-    [isSelected, shouldAnimate, stroke]
+  const edgeStyles = useMemo(
+    () => getEdgeStyles(stroke, selected, shouldAnimateEdges, areConnectedNodesSelected),
+    [areConnectedNodesSelected, stroke, selected, shouldAnimateEdges]
   );
 
   return (
@@ -62,13 +59,13 @@ const InvocationDefaultEdge = ({
             bg="base.800"
             borderRadius="base"
             borderWidth={1}
-            borderColor={isSelected ? 'undefined' : 'transparent'}
-            opacity={isSelected ? 1 : 0.5}
+            borderColor={selected ? 'undefined' : 'transparent'}
+            opacity={selected ? 1 : 0.5}
             py={1}
             px={3}
             shadow="md"
           >
-            <Text size="sm" fontWeight="semibold" color={isSelected ? 'base.100' : 'base.300'}>
+            <Text size="sm" fontWeight="semibold" color={selected ? 'base.100' : 'base.300'}>
               {label}
             </Text>
           </Flex>

invokeai/frontend/web/src/features/nodes/components/flow/edges/util/getEdgeColor.ts

@@ -1,6 +1,7 @@
 import { colorTokenToCssVar } from 'common/util/colorTokenToCssVar';
 import { FIELD_COLORS } from 'features/nodes/types/constants';
 import type { FieldType } from 'features/nodes/types/field';
+import type { CSSProperties } from 'react';
 
 export const getFieldColor = (fieldType: FieldType | null): string => {
   if (!fieldType) {
@@ -10,3 +11,16 @@ export const getFieldColor = (fieldType: FieldType | null): string => {
 
   return color ? colorTokenToCssVar(color) : colorTokenToCssVar('base.500');
 };
+
+export const getEdgeStyles = (
+  stroke: string,
+  selected: boolean,
+  shouldAnimateEdges: boolean,
+  areConnectedNodesSelected: boolean
+): CSSProperties => ({
+  strokeWidth: 3,
+  stroke,
+  opacity: selected ? 1 : 0.5,
+  animation: shouldAnimateEdges ? 'dashdraw 0.5s linear infinite' : undefined,
+  strokeDasharray: selected || areConnectedNodesSelected ? 5 : 'none',
+});

invokeai/frontend/web/src/features/nodes/components/flow/edges/util/makeEdgeSelector.ts

@@ -1,53 +1,58 @@
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { colorTokenToCssVar } from 'common/util/colorTokenToCssVar';
+import { deepClone } from 'common/util/deepClone';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectFieldOutputTemplate, selectNodeTemplate } from 'features/nodes/store/selectors';
+import type { Templates } from 'features/nodes/store/types';
+import { selectWorkflowSettingsSlice } from 'features/nodes/store/workflowSettingsSlice';
 import { isInvocationNode } from 'features/nodes/types/invocation';
 
 import { getFieldColor } from './getEdgeColor';
 
 const defaultReturnValue = {
-  isSelected: false,
-  shouldAnimate: false,
+  areConnectedNodesSelected: false,
+  shouldAnimateEdges: false,
   stroke: colorTokenToCssVar('base.500'),
   label: '',
 };
 
 export const makeEdgeSelector = (
+  templates: Templates,
   source: string,
   sourceHandleId: string | null | undefined,
   target: string,
-  targetHandleId: string | null | undefined,
-  selected?: boolean
+  targetHandleId: string | null | undefined
 ) =>
   createMemoizedSelector(
     selectNodesSlice,
-    (nodes): { isSelected: boolean; shouldAnimate: boolean; stroke: string; label: string } => {
+    selectWorkflowSettingsSlice,
+    (
+      nodes,
+      workflowSettings
+    ): { areConnectedNodesSelected: boolean; shouldAnimateEdges: boolean; stroke: string; label: string } => {
+      const { shouldAnimateEdges, shouldColorEdges } = workflowSettings;
       const sourceNode = nodes.nodes.find((node) => node.id === source);
       const targetNode = nodes.nodes.find((node) => node.id === target);
 
+      const returnValue = deepClone(defaultReturnValue);
+      returnValue.shouldAnimateEdges = shouldAnimateEdges;
+
       const isInvocationToInvocationEdge = isInvocationNode(sourceNode) && isInvocationNode(targetNode);
 
-      const isSelected = Boolean(sourceNode?.selected || targetNode?.selected || selected);
+      returnValue.areConnectedNodesSelected = Boolean(sourceNode?.selected || targetNode?.selected);
       if (!sourceNode || !sourceHandleId || !targetNode || !targetHandleId) {
-        return defaultReturnValue;
+        return returnValue;
       }
 
-      const outputFieldTemplate = selectFieldOutputTemplate(nodes, sourceNode.id, sourceHandleId);
+      const sourceNodeTemplate = templates[sourceNode.data.type];
+      const targetNodeTemplate = templates[targetNode.data.type];
+
+      const outputFieldTemplate = sourceNodeTemplate?.outputs[sourceHandleId];
       const sourceType = isInvocationToInvocationEdge ? outputFieldTemplate?.type : undefined;
 
-      const stroke = sourceType && nodes.shouldColorEdges ? getFieldColor(sourceType) : colorTokenToCssVar('base.500');
+      returnValue.stroke = sourceType && shouldColorEdges ? getFieldColor(sourceType) : colorTokenToCssVar('base.500');
 
-      const sourceNodeTemplate = selectNodeTemplate(nodes, sourceNode.id);
-      const targetNodeTemplate = selectNodeTemplate(nodes, targetNode.id);
+      returnValue.label = `${sourceNodeTemplate?.title || sourceNode.data?.label} -> ${targetNodeTemplate?.title || targetNode.data?.label}`;
 
-      const label = `${sourceNodeTemplate?.title || sourceNode.data?.label} -> ${targetNodeTemplate?.title || targetNode.data?.label}`;
-
-      return {
-        isSelected,
-        shouldAnimate: nodes.shouldAnimateEdges && isSelected,
-        stroke,
-        label,
-      };
+      return returnValue;
     }
   );

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

@@ -1,12 +1,10 @@
 import type { SystemStyleObject } from '@invoke-ai/ui-library';
 import { Badge, CircularProgress, Flex, Icon, Image, Text, Tooltip } from '@invoke-ai/ui-library';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { useExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { DRAG_HANDLE_CLASSNAME } from 'features/nodes/types/constants';
 import type { NodeExecutionState } from 'features/nodes/types/invocation';
 import { zNodeStatus } from 'features/nodes/types/invocation';
-import { memo, useMemo } from 'react';
+import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiCheckBold, PiDotsThreeOutlineFill, PiWarningBold } from 'react-icons/pi';
 
@@ -24,12 +22,7 @@ const circleStyles: SystemStyleObject = {
 };
 
 const InvocationNodeStatusIndicator = ({ nodeId }: Props) => {
-  const selectNodeExecutionState = useMemo(
-    () => createMemoizedSelector(selectNodesSlice, (nodes) => nodes.nodeExecutionStates[nodeId]),
-    [nodeId]
-  );
-
-  const nodeExecutionState = useAppSelector(selectNodeExecutionState);
+  const nodeExecutionState = useExecutionState(nodeId);
 
   if (!nodeExecutionState) {
     return null;

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

@@ -1,7 +1,7 @@
-import { createSelector } from '@reduxjs/toolkit';
+import { useStore } from '@nanostores/react';
 import { useAppSelector } from 'app/store/storeHooks';
 import InvocationNode from 'features/nodes/components/flow/nodes/Invocation/InvocationNode';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import type { InvocationNodeData } from 'features/nodes/types/invocation';
 import { memo, useMemo } from 'react';
 import type { NodeProps } from 'reactflow';
@@ -11,13 +11,13 @@ import InvocationNodeUnknownFallback from './InvocationNodeUnknownFallback';
 const InvocationNodeWrapper = (props: NodeProps<InvocationNodeData>) => {
   const { data, selected } = props;
   const { id: nodeId, type, isOpen, label } = data;
+  const templates = useStore($templates);
+  const hasTemplate = useMemo(() => Boolean(templates[type]), [templates, type]);
+  const nodeExists = useAppSelector((s) => Boolean(s.nodes.present.nodes.find((n) => n.id === nodeId)));
 
-  const hasTemplateSelector = useMemo(
-    () => createSelector(selectNodesSlice, (nodes) => Boolean(nodes.templates[type])),
-    [type]
-  );
-
-  const hasTemplate = useAppSelector(hasTemplateSelector);
+  if (!nodeExists) {
+    return null;
+  }
 
   if (!hasTemplate) {
     return (

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

@@ -0,0 +1,20 @@
+import { useDoesFieldExist } from 'features/nodes/hooks/useDoesFieldExist';
+import type { PropsWithChildren } from 'react';
+import { memo } from 'react';
+
+type Props = PropsWithChildren<{
+  nodeId: string;
+  fieldName?: string;
+}>;
+
+export const MissingFallback = memo((props: Props) => {
+  // We must be careful here to avoid race conditions where a deleted node is still referenced as an exposed field
+  const exists = useDoesFieldExist(props.nodeId, props.fieldName);
+  if (!exists) {
+    return null;
+  }
+
+  return props.children;
+});
+
+MissingFallback.displayName = 'MissingFallback';

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

@@ -25,10 +25,11 @@ interface Props {
   kind: 'inputs' | 'outputs';
   isMissingInput?: boolean;
   withTooltip?: boolean;
+  shouldDim?: boolean;
 }
 
 const EditableFieldTitle = forwardRef((props: Props, ref) => {
-  const { nodeId, fieldName, kind, isMissingInput = false, withTooltip = false } = props;
+  const { nodeId, fieldName, kind, isMissingInput = false, withTooltip = false, shouldDim = false } = props;
   const label = useFieldLabel(nodeId, fieldName);
   const fieldTemplateTitle = useFieldTemplateTitle(nodeId, fieldName, kind);
   const { t } = useTranslation();
@@ -37,14 +38,13 @@ const EditableFieldTitle = forwardRef((props: Props, ref) => {
   const [localTitle, setLocalTitle] = useState(label || fieldTemplateTitle || t('nodes.unknownField'));
 
   const handleSubmit = useCallback(
-    async (newTitle: string) => {
-      if (newTitle && (newTitle === label || newTitle === fieldTemplateTitle)) {
-        return;
-      }
-      setLocalTitle(newTitle || fieldTemplateTitle || t('nodes.unknownField'));
-      dispatch(fieldLabelChanged({ nodeId, fieldName, label: newTitle }));
+    async (newTitleRaw: string) => {
+      const newTitle = newTitleRaw.trim();
+      const finalTitle = newTitle || fieldTemplateTitle || t('nodes.unknownField');
+      setLocalTitle(finalTitle);
+      dispatch(fieldLabelChanged({ nodeId, fieldName, label: finalTitle }));
     },
-    [label, fieldTemplateTitle, dispatch, nodeId, fieldName, t]
+    [fieldTemplateTitle, dispatch, nodeId, fieldName, t]
   );
 
   const handleChange = useCallback((newTitle: string) => {
@@ -57,33 +57,34 @@ const EditableFieldTitle = forwardRef((props: Props, ref) => {
   }, [label, fieldTemplateTitle, t]);
 
   return (
-    <Tooltip
-      label={withTooltip ? <FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="inputs" /> : undefined}
-      openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
+    <Editable
+      value={localTitle}
+      onChange={handleChange}
+      onSubmit={handleSubmit}
+      as={Flex}
+      ref={ref}
+      position="relative"
+      overflow="hidden"
+      alignItems="center"
+      justifyContent="flex-start"
+      gap={1}
+      w="full"
     >
-      <Editable
-        value={localTitle}
-        onChange={handleChange}
-        onSubmit={handleSubmit}
-        as={Flex}
-        ref={ref}
-        position="relative"
-        overflow="hidden"
-        alignItems="center"
-        justifyContent="flex-start"
-        gap={1}
-        w="full"
+      <Tooltip
+        label={withTooltip ? <FieldTooltipContent nodeId={nodeId} fieldName={fieldName} kind="inputs" /> : undefined}
+        openDelay={HANDLE_TOOLTIP_OPEN_DELAY}
       >
         <EditablePreview
           fontWeight="semibold"
           sx={editablePreviewStyles}
           noOfLines={1}
           color={isMissingInput ? 'error.300' : 'base.300'}
+          opacity={shouldDim ? 0.5 : 1}
         />
-        <EditableInput className="nodrag" sx={editableInputStyles} />
-        <EditableControls />
-      </Editable>
-    </Tooltip>
+      </Tooltip>
+      <EditableInput className="nodrag" sx={editableInputStyles} />
+      <EditableControls />
+    </Editable>
   );
 });
 
@@ -127,7 +128,15 @@ const EditableControls = memo(() => {
   }
 
   return (
-    <Flex onClick={handleClick} position="absolute" w="full" h="full" top={0} insetInlineStart={0} cursor="text" />
+    <Flex
+      onClick={handleClick}
+      position="absolute"
+      w="min-content"
+      h="full"
+      top={0}
+      insetInlineStart={0}
+      cursor="text"
+    />
   );
 });
 

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

@@ -2,10 +2,12 @@ import { Tooltip } from '@invoke-ai/ui-library';
 import { colorTokenToCssVar } from 'common/util/colorTokenToCssVar';
 import { getFieldColor } from 'features/nodes/components/flow/edges/util/getEdgeColor';
 import { useFieldTypeName } from 'features/nodes/hooks/usePrettyFieldType';
+import type { ValidationResult } from 'features/nodes/store/util/validateConnection';
 import { HANDLE_TOOLTIP_OPEN_DELAY, MODEL_TYPES } from 'features/nodes/types/constants';
-import type { FieldInputTemplate, FieldOutputTemplate } from 'features/nodes/types/field';
+import { type FieldInputTemplate, type FieldOutputTemplate, isSingle } from 'features/nodes/types/field';
 import type { CSSProperties } from 'react';
 import { memo, useMemo } from 'react';
+import { useTranslation } from 'react-i18next';
 import type { HandleType } from 'reactflow';
 import { Handle, Position } from 'reactflow';
 
@@ -14,11 +16,12 @@ type FieldHandleProps = {
   handleType: HandleType;
   isConnectionInProgress: boolean;
   isConnectionStartField: boolean;
-  connectionError?: string;
+  validationResult: ValidationResult;
 };
 
 const FieldHandle = (props: FieldHandleProps) => {
-  const { fieldTemplate, handleType, isConnectionInProgress, isConnectionStartField, connectionError } = props;
+  const { fieldTemplate, handleType, isConnectionInProgress, isConnectionStartField, validationResult } = props;
+  const { t } = useTranslation();
   const { name } = fieldTemplate;
   const type = fieldTemplate.type;
   const fieldTypeName = useFieldTypeName(type);
@@ -26,11 +29,11 @@ const FieldHandle = (props: FieldHandleProps) => {
     const isModelType = MODEL_TYPES.some((t) => t === type.name);
     const color = getFieldColor(type);
     const s: CSSProperties = {
-      backgroundColor: type.isCollection || type.isCollectionOrScalar ? colorTokenToCssVar('base.900') : color,
+      backgroundColor: !isSingle(type) ? colorTokenToCssVar('base.900') : color,
       position: 'absolute',
       width: '1rem',
       height: '1rem',
-      borderWidth: type.isCollection || type.isCollectionOrScalar ? 4 : 0,
+      borderWidth: !isSingle(type) ? 4 : 0,
       borderStyle: 'solid',
       borderColor: color,
       borderRadius: isModelType ? 4 : '100%',
@@ -43,11 +46,11 @@ const FieldHandle = (props: FieldHandleProps) => {
       s.insetInlineEnd = '-1rem';
     }
 
-    if (isConnectionInProgress && !isConnectionStartField && connectionError) {
+    if (isConnectionInProgress && !isConnectionStartField && !validationResult.isValid) {
       s.filter = 'opacity(0.4) grayscale(0.7)';
     }
 
-    if (isConnectionInProgress && connectionError) {
+    if (isConnectionInProgress && !validationResult.isValid) {
       if (isConnectionStartField) {
         s.cursor = 'grab';
       } else {
@@ -58,14 +61,14 @@ const FieldHandle = (props: FieldHandleProps) => {
     }
 
     return s;
-  }, [connectionError, handleType, isConnectionInProgress, isConnectionStartField, type]);
+  }, [handleType, isConnectionInProgress, isConnectionStartField, type, validationResult.isValid]);
 
   const tooltip = useMemo(() => {
-    if (isConnectionInProgress && connectionError) {
-      return connectionError;
+    if (isConnectionInProgress && validationResult.messageTKey) {
+      return t(validationResult.messageTKey);
     }
     return fieldTypeName;
-  }, [connectionError, fieldTypeName, isConnectionInProgress]);
+  }, [fieldTypeName, isConnectionInProgress, t, validationResult.messageTKey]);
 
   return (
     <Tooltip

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

@@ -24,7 +24,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
   const doesFieldHaveValue = useDoesInputHaveValue(nodeId, fieldName);
   const [isHovered, setIsHovered] = useState(false);
 
-  const { isConnected, isConnectionInProgress, isConnectionStartField, connectionError, shouldDim } =
+  const { isConnected, isConnectionInProgress, isConnectionStartField, validationResult, shouldDim } =
     useConnectionState({ nodeId, fieldName, kind: 'inputs' });
 
   const isMissingInput = useMemo(() => {
@@ -69,7 +69,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
     );
   }
 
-  if (fieldTemplate.input === 'connection') {
+  if (fieldTemplate.input === 'connection' || isConnected) {
     return (
       <InputFieldWrapper shouldDim={shouldDim}>
         <FormControl isInvalid={isMissingInput} isDisabled={isConnected} px={2}>
@@ -79,6 +79,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
             kind="inputs"
             isMissingInput={isMissingInput}
             withTooltip
+            shouldDim
           />
         </FormControl>
 
@@ -87,7 +88,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
           handleType="target"
           isConnectionInProgress={isConnectionInProgress}
           isConnectionStartField={isConnectionStartField}
-          connectionError={connectionError}
+          validationResult={validationResult}
         />
       </InputFieldWrapper>
     );
@@ -95,7 +96,15 @@ const InputField = ({ nodeId, fieldName }: Props) => {
 
   return (
     <InputFieldWrapper shouldDim={shouldDim}>
-      <FormControl isInvalid={isMissingInput} isDisabled={isConnected} orientation="vertical" px={2}>
+      <FormControl
+        isInvalid={isMissingInput}
+        isDisabled={isConnected}
+        // Without pointerEvents prop, disabled inputs don't trigger reactflow events. For example, when making a
+        // connection, the mouse up to end the connection won't fire, leaving the connection in-progress.
+        pointerEvents={isConnected ? 'none' : 'auto'}
+        orientation="vertical"
+        px={2}
+      >
         <Flex flexDir="column" w="full" gap={1} onMouseEnter={onMouseEnter} onMouseLeave={onMouseLeave}>
           <Flex>
             <EditableFieldTitle
@@ -117,7 +126,7 @@ const InputField = ({ nodeId, fieldName }: Props) => {
           handleType="target"
           isConnectionInProgress={isConnectionInProgress}
           isConnectionStartField={isConnectionStartField}
-          connectionError={connectionError}
+          validationResult={validationResult}
         />
       )}
     </InputFieldWrapper>

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

@@ -1,3 +1,4 @@
+import ModelIdentifierFieldInputComponent from 'features/nodes/components/flow/nodes/Invocation/fields/inputs/ModelIdentifierFieldInputComponent';
 import { useFieldInputInstance } from 'features/nodes/hooks/useFieldInputInstance';
 import { useFieldInputTemplate } from 'features/nodes/hooks/useFieldInputTemplate';
 import {
@@ -23,6 +24,8 @@ import {
   isLoRAModelFieldInputTemplate,
   isMainModelFieldInputInstance,
   isMainModelFieldInputTemplate,
+  isModelIdentifierFieldInputInstance,
+  isModelIdentifierFieldInputTemplate,
   isSchedulerFieldInputInstance,
   isSchedulerFieldInputTemplate,
   isSDXLMainModelFieldInputInstance,
@@ -95,6 +98,10 @@ const InputFieldRenderer = ({ nodeId, fieldName }: InputFieldProps) => {
     return <MainModelFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
   }
 
+  if (isModelIdentifierFieldInputInstance(fieldInstance) && isModelIdentifierFieldInputTemplate(fieldTemplate)) {
+    return <ModelIdentifierFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
+  }
+
   if (isSDXLRefinerModelFieldInputInstance(fieldInstance) && isSDXLRefinerModelFieldInputTemplate(fieldTemplate)) {
     return <RefinerModelFieldInputComponent nodeId={nodeId} field={fieldInstance} fieldTemplate={fieldTemplate} />;
   }

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

@@ -3,6 +3,7 @@ import { CSS } from '@dnd-kit/utilities';
 import { Flex, Icon, IconButton, Spacer, Tooltip } from '@invoke-ai/ui-library';
 import { useAppDispatch } from 'app/store/storeHooks';
 import NodeSelectionOverlay from 'common/components/NodeSelectionOverlay';
+import { MissingFallback } from 'features/nodes/components/flow/nodes/Invocation/MissingFallback';
 import { useFieldOriginalValue } from 'features/nodes/hooks/useFieldOriginalValue';
 import { useMouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
 import { workflowExposedFieldRemoved } from 'features/nodes/store/workflowSlice';
@@ -20,7 +21,7 @@ type Props = {
   fieldName: string;
 };
 
-const LinearViewField = ({ nodeId, fieldName }: Props) => {
+const LinearViewFieldInternal = ({ nodeId, fieldName }: Props) => {
   const dispatch = useAppDispatch();
   const { isValueChanged, onReset } = useFieldOriginalValue(nodeId, fieldName);
   const { isMouseOverNode, handleMouseOut, handleMouseOver } = useMouseOverNode(nodeId);
@@ -99,4 +100,12 @@ const LinearViewField = ({ nodeId, fieldName }: Props) => {
   );
 };
 
+const LinearViewField = ({ nodeId, fieldName }: Props) => {
+  return (
+    <MissingFallback nodeId={nodeId} fieldName={fieldName}>
+      <LinearViewFieldInternal nodeId={nodeId} fieldName={fieldName} />
+    </MissingFallback>
+  );
+};
+
 export default memo(LinearViewField);

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

@@ -18,7 +18,7 @@ const OutputField = ({ nodeId, fieldName }: Props) => {
   const { t } = useTranslation();
   const fieldTemplate = useFieldOutputTemplate(nodeId, fieldName);
 
-  const { isConnected, isConnectionInProgress, isConnectionStartField, connectionError, shouldDim } =
+  const { isConnected, isConnectionInProgress, isConnectionStartField, validationResult, shouldDim } =
     useConnectionState({ nodeId, fieldName, kind: 'outputs' });
 
   if (!fieldTemplate) {
@@ -52,7 +52,7 @@ const OutputField = ({ nodeId, fieldName }: Props) => {
         handleType="source"
         isConnectionInProgress={isConnectionInProgress}
         isConnectionStartField={isConnectionStartField}
-        connectionError={connectionError}
+        validationResult={validationResult}
       />
     </OutputFieldWrapper>
   );

invokeai/frontend/web/src/features/nodes/components/flow/nodes/Invocation/fields/inputs/ModelIdentifierFieldInputComponent.tsx

@@ -0,0 +1,66 @@
+import { Combobox, Flex, FormControl } from '@invoke-ai/ui-library';
+import { EMPTY_ARRAY } from 'app/store/constants';
+import { useAppDispatch } from 'app/store/storeHooks';
+import { useGroupedModelCombobox } from 'common/hooks/useGroupedModelCombobox';
+import { fieldModelIdentifierValueChanged } from 'features/nodes/store/nodesSlice';
+import type { ModelIdentifierFieldInputInstance, ModelIdentifierFieldInputTemplate } from 'features/nodes/types/field';
+import { memo, useCallback, useMemo } from 'react';
+import { modelConfigsAdapterSelectors, useGetModelConfigsQuery } from 'services/api/endpoints/models';
+import type { AnyModelConfig } from 'services/api/types';
+
+import type { FieldComponentProps } from './types';
+
+type Props = FieldComponentProps<ModelIdentifierFieldInputInstance, ModelIdentifierFieldInputTemplate>;
+
+const ModelIdentifierFieldInputComponent = (props: Props) => {
+  const { nodeId, field } = props;
+  const dispatch = useAppDispatch();
+  const { data, isLoading } = useGetModelConfigsQuery();
+  const _onChange = useCallback(
+    (value: AnyModelConfig | null) => {
+      if (!value) {
+        return;
+      }
+      dispatch(
+        fieldModelIdentifierValueChanged({
+          nodeId,
+          fieldName: field.name,
+          value,
+        })
+      );
+    },
+    [dispatch, field.name, nodeId]
+  );
+
+  const modelConfigs = useMemo(() => {
+    if (!data) {
+      return EMPTY_ARRAY;
+    }
+
+    return modelConfigsAdapterSelectors.selectAll(data);
+  }, [data]);
+
+  const { options, value, onChange, placeholder, noOptionsMessage } = useGroupedModelCombobox({
+    modelConfigs,
+    onChange: _onChange,
+    isLoading,
+    selectedModel: field.value,
+    groupByType: true,
+  });
+
+  return (
+    <Flex w="full" alignItems="center" gap={2}>
+      <FormControl className="nowheel nodrag" isDisabled={!options.length} isInvalid={!value}>
+        <Combobox
+          value={value}
+          placeholder={placeholder}
+          options={options}
+          onChange={onChange}
+          noOptionsMessage={noOptionsMessage}
+        />
+      </FormControl>
+    </Flex>
+  );
+};
+
+export default memo(ModelIdentifierFieldInputComponent);

invokeai/frontend/web/src/features/nodes/components/flow/nodes/common/NodeWrapper.tsx

@@ -1,14 +1,15 @@
 import type { ChakraProps } from '@invoke-ai/ui-library';
 import { Box, useGlobalMenuClose, useToken } from '@invoke-ai/ui-library';
-import { createSelector } from '@reduxjs/toolkit';
-import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
+import { useAppDispatch, useAppSelector, useAppStore } from 'app/store/storeHooks';
 import NodeSelectionOverlay from 'common/components/NodeSelectionOverlay';
+import { useExecutionState } from 'features/nodes/hooks/useExecutionState';
 import { useMouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
-import { nodeExclusivelySelected, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { nodesChanged } from 'features/nodes/store/nodesSlice';
 import { DRAG_HANDLE_CLASSNAME, NODE_WIDTH } from 'features/nodes/types/constants';
 import { zNodeStatus } from 'features/nodes/types/invocation';
 import type { MouseEvent, PropsWithChildren } from 'react';
-import { memo, useCallback, useMemo } from 'react';
+import { memo, useCallback } from 'react';
+import type { NodeChange } from 'reactflow';
 
 type NodeWrapperProps = PropsWithChildren & {
   nodeId: string;
@@ -18,18 +19,11 @@ type NodeWrapperProps = PropsWithChildren & {
 
 const NodeWrapper = (props: NodeWrapperProps) => {
   const { nodeId, width, children, selected } = props;
+  const store = useAppStore();
   const { isMouseOverNode, handleMouseOut, handleMouseOver } = useMouseOverNode(nodeId);
 
-  const selectIsInProgress = useMemo(
-    () =>
-      createSelector(
-        selectNodesSlice,
-        (nodes) => nodes.nodeExecutionStates[nodeId]?.status === zNodeStatus.enum.IN_PROGRESS
-      ),
-    [nodeId]
-  );
-
-  const isInProgress = useAppSelector(selectIsInProgress);
+  const executionState = useExecutionState(nodeId);
+  const isInProgress = executionState?.status === zNodeStatus.enum.IN_PROGRESS;
 
   const [nodeInProgress, shadowsXl, shadowsBase] = useToken('shadows', [
     'nodeInProgress',
@@ -39,17 +33,26 @@ const NodeWrapper = (props: NodeWrapperProps) => {
 
   const dispatch = useAppDispatch();
 
-  const opacity = useAppSelector((s) => s.nodes.nodeOpacity);
+  const opacity = useAppSelector((s) => s.workflowSettings.nodeOpacity);
   const { onCloseGlobal } = useGlobalMenuClose();
 
   const handleClick = useCallback(
     (e: MouseEvent<HTMLDivElement>) => {
       if (!e.ctrlKey && !e.altKey && !e.metaKey && !e.shiftKey) {
-        dispatch(nodeExclusivelySelected(nodeId));
+        const { nodes } = store.getState().nodes.present;
+        const nodeChanges: NodeChange[] = [];
+        nodes.forEach(({ id, selected }) => {
+          if (selected !== (id === nodeId)) {
+            nodeChanges.push({ type: 'select', id, selected: id === nodeId });
+          }
+        });
+        if (nodeChanges.length > 0) {
+          dispatch(nodesChanged(nodeChanges));
+        }
       }
       onCloseGlobal();
     },
-    [dispatch, onCloseGlobal, nodeId]
+    [onCloseGlobal, store, dispatch, nodeId]
   );
 
   return (

invokeai/frontend/web/src/features/nodes/components/flow/panels/BottomLeftPanel/NodeOpacitySlider.tsx

@@ -1,12 +1,12 @@
 import { CompositeSlider, Flex } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import { nodeOpacityChanged } from 'features/nodes/store/nodesSlice';
+import { nodeOpacityChanged } from 'features/nodes/store/workflowSettingsSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 
 const NodeOpacitySlider = () => {
   const dispatch = useAppDispatch();
-  const nodeOpacity = useAppSelector((s) => s.nodes.nodeOpacity);
+  const nodeOpacity = useAppSelector((s) => s.workflowSettings.nodeOpacity);
   const { t } = useTranslation();
 
   const handleChange = useCallback(

invokeai/frontend/web/src/features/nodes/components/flow/panels/BottomLeftPanel/ViewportControls.tsx

@@ -1,9 +1,6 @@
 import { ButtonGroup, IconButton } from '@invoke-ai/ui-library';
 import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
-import {
-  // shouldShowFieldTypeLegendChanged,
-  shouldShowMinimapPanelChanged,
-} from 'features/nodes/store/nodesSlice';
+import { shouldShowMinimapPanelChanged } from 'features/nodes/store/workflowSettingsSlice';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
 import {
@@ -19,9 +16,9 @@ const ViewportControls = () => {
   const { zoomIn, zoomOut, fitView } = useReactFlow();
   const dispatch = useAppDispatch();
   // const shouldShowFieldTypeLegend = useAppSelector(
-  //   (s) => s.nodes.shouldShowFieldTypeLegend
+  //   (s) => s.nodes.present.shouldShowFieldTypeLegend
   // );
-  const shouldShowMinimapPanel = useAppSelector((s) => s.nodes.shouldShowMinimapPanel);
+  const shouldShowMinimapPanel = useAppSelector((s) => s.workflowSettings.shouldShowMinimapPanel);
 
   const handleClickedZoomIn = useCallback(() => {
     zoomIn();

invokeai/frontend/web/src/features/nodes/components/flow/panels/MinimapPanel/MinimapPanel.tsx

@@ -16,7 +16,7 @@ const minimapStyles: SystemStyleObject = {
 };
 
 const MinimapPanel = () => {
-  const shouldShowMinimapPanel = useAppSelector((s) => s.nodes.shouldShowMinimapPanel);
+  const shouldShowMinimapPanel = useAppSelector((s) => s.workflowSettings.shouldShowMinimapPanel);
 
   return (
     <Flex gap={2} position="absolute" bottom={0} insetInlineEnd={0}>

invokeai/frontend/web/src/features/nodes/components/flow/panels/TopPanel/AddNodeButton.tsx

@@ -1,23 +1,18 @@
 import { IconButton } from '@invoke-ai/ui-library';
-import { useAppDispatch } from 'app/store/storeHooks';
-import { addNodePopoverOpened } from 'features/nodes/store/nodesSlice';
-import { memo, useCallback } from 'react';
+import { openAddNodePopover } from 'features/nodes/store/nodesSlice';
+import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { PiPlusBold } from 'react-icons/pi';
 
 const AddNodeButton = () => {
-  const dispatch = useAppDispatch();
   const { t } = useTranslation();
-  const handleOpenAddNodePopover = useCallback(() => {
-    dispatch(addNodePopoverOpened());
-  }, [dispatch]);
 
   return (
     <IconButton
       tooltip={t('nodes.addNodeToolTip')}
       aria-label={t('nodes.addNode')}
       icon={<PiPlusBold />}
-      onClick={handleOpenAddNodePopover}
+      onClick={openAddNodePopover}
       pointerEvents="auto"
     />
   );

invokeai/frontend/web/src/features/nodes/components/flow/panels/TopRightPanel/WorkflowEditorSettings.tsx

@@ -21,13 +21,13 @@ import { useAppDispatch, useAppSelector } from 'app/store/storeHooks';
 import ReloadNodeTemplatesButton from 'features/nodes/components/flow/panels/TopRightPanel/ReloadSchemaButton';
 import {
   selectionModeChanged,
-  selectNodesSlice,
+  selectWorkflowSettingsSlice,
   shouldAnimateEdgesChanged,
   shouldColorEdgesChanged,
   shouldShowEdgeLabelsChanged,
   shouldSnapToGridChanged,
   shouldValidateGraphChanged,
-} from 'features/nodes/store/nodesSlice';
+} from 'features/nodes/store/workflowSettingsSlice';
 import type { ChangeEvent, ReactNode } from 'react';
 import { memo, useCallback } from 'react';
 import { useTranslation } from 'react-i18next';
@@ -35,7 +35,7 @@ import { SelectionMode } from 'reactflow';
 
 const formLabelProps: FormLabelProps = { flexGrow: 1 };
 
-const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
+const selector = createMemoizedSelector(selectWorkflowSettingsSlice, (workflowSettings) => {
   const {
     shouldAnimateEdges,
     shouldValidateGraph,
@@ -43,7 +43,7 @@ const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
     shouldColorEdges,
     shouldShowEdgeLabels,
     selectionMode,
-  } = nodes;
+  } = workflowSettings;
   return {
     shouldAnimateEdges,
     shouldValidateGraph,

invokeai/frontend/web/src/features/nodes/components/sidePanel/WorkflowName.tsx

@@ -7,8 +7,10 @@ import WorkflowInfoTooltipContent from './viewMode/WorkflowInfoTooltipContent';
 import { WorkflowWarning } from './viewMode/WorkflowWarning';
 
 export const WorkflowName = () => {
-  const { name, isTouched, mode } = useAppSelector((s) => s.workflow);
   const { t } = useTranslation();
+  const name = useAppSelector((s) => s.workflow.name);
+  const isTouched = useAppSelector((s) => s.workflow.isTouched);
+  const mode = useAppSelector((s) => s.workflow.mode);
 
   return (
     <Flex gap="1" alignItems="center">

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDataTab.tsx

@@ -3,27 +3,21 @@ import { useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
 import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { selectLastSelectedNode } from 'features/nodes/store/selectors';
 import { memo } from 'react';
 import { useTranslation } from 'react-i18next';
-const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
-  const lastSelectedNodeId = nodes.selectedNodes[nodes.selectedNodes.length - 1];
 
-  const lastSelectedNode = nodes.nodes.find((node) => node.id === lastSelectedNodeId);
-
-  return {
-    data: lastSelectedNode?.data,
-  };
-});
+const selector = createMemoizedSelector(selectNodesSlice, (nodes) => selectLastSelectedNode(nodes));
 
 const InspectorDataTab = () => {
   const { t } = useTranslation();
-  const { data } = useAppSelector(selector);
+  const lastSelectedNode = useAppSelector(selector);
 
-  if (!data) {
+  if (!lastSelectedNode) {
     return <IAINoContentFallback label={t('nodes.noNodeSelected')} icon={null} />;
   }
 
-  return <DataViewer data={data} label="Node Data" />;
+  return <DataViewer data={lastSelectedNode.data} label="Node Data" />;
 };
 
 export default memo(InspectorDataTab);

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorDetailsTab.tsx

@@ -1,36 +1,39 @@
 import { Box, Flex, FormControl, FormLabel, HStack, Text } from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import NotesTextarea from 'features/nodes/components/flow/nodes/Invocation/NotesTextarea';
 import { useNodeNeedsUpdate } from 'features/nodes/hooks/useNodeNeedsUpdate';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { $templates, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { selectLastSelectedNode } from 'features/nodes/store/selectors';
 import { isInvocationNode } from 'features/nodes/types/invocation';
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 
 import EditableNodeTitle from './details/EditableNodeTitle';
 
-const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
-  const lastSelectedNodeId = nodes.selectedNodes[nodes.selectedNodes.length - 1];
-
-  const lastSelectedNode = nodes.nodes.find((node) => node.id === lastSelectedNodeId);
-
-  const lastSelectedNodeTemplate = lastSelectedNode ? nodes.templates[lastSelectedNode.data.type] : undefined;
-
-  if (!isInvocationNode(lastSelectedNode) || !lastSelectedNodeTemplate) {
-    return;
-  }
-
-  return {
-    nodeId: lastSelectedNode.data.id,
-    nodeVersion: lastSelectedNode.data.version,
-    templateTitle: lastSelectedNodeTemplate.title,
-  };
-});
-
 const InspectorDetailsTab = () => {
+  const templates = useStore($templates);
+  const selector = useMemo(
+    () =>
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        const lastSelectedNode = selectLastSelectedNode(nodes);
+        const lastSelectedNodeTemplate = lastSelectedNode ? templates[lastSelectedNode.data.type] : undefined;
+
+        if (!isInvocationNode(lastSelectedNode) || !lastSelectedNodeTemplate) {
+          return;
+        }
+
+        return {
+          nodeId: lastSelectedNode.data.id,
+          nodeVersion: lastSelectedNode.data.version,
+          templateTitle: lastSelectedNodeTemplate.title,
+        };
+      }),
+    [templates]
+  );
   const data = useAppSelector(selector);
   const { t } = useTranslation();
 

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorOutputsTab.tsx

@@ -1,46 +1,49 @@
 import { Box, Flex } from '@invoke-ai/ui-library';
+import { useStore } from '@nanostores/react';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { useExecutionState } from 'features/nodes/hooks/useExecutionState';
+import { $templates, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { selectLastSelectedNode } from 'features/nodes/store/selectors';
 import { isInvocationNode } from 'features/nodes/types/invocation';
-import { memo } from 'react';
+import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import type { ImageOutput } from 'services/api/types';
 import type { AnyResult } from 'services/events/types';
 
 import ImageOutputPreview from './outputs/ImageOutputPreview';
 
-const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
-  const lastSelectedNodeId = nodes.selectedNodes[nodes.selectedNodes.length - 1];
-
-  const lastSelectedNode = nodes.nodes.find((node) => node.id === lastSelectedNodeId);
-
-  const lastSelectedNodeTemplate = lastSelectedNode ? nodes.templates[lastSelectedNode.data.type] : undefined;
-
-  const nes = nodes.nodeExecutionStates[lastSelectedNodeId ?? '__UNKNOWN_NODE__'];
-
-  if (!isInvocationNode(lastSelectedNode) || !nes || !lastSelectedNodeTemplate) {
-    return;
-  }
-
-  return {
-    outputs: nes.outputs,
-    outputType: lastSelectedNodeTemplate.outputType,
-  };
-});
-
 const InspectorOutputsTab = () => {
+  const templates = useStore($templates);
+  const selector = useMemo(
+    () =>
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        const lastSelectedNode = selectLastSelectedNode(nodes);
+        const lastSelectedNodeTemplate = lastSelectedNode ? templates[lastSelectedNode.data.type] : undefined;
+
+        if (!isInvocationNode(lastSelectedNode) || !lastSelectedNodeTemplate) {
+          return;
+        }
+
+        return {
+          nodeId: lastSelectedNode.id,
+          outputType: lastSelectedNodeTemplate.outputType,
+        };
+      }),
+    [templates]
+  );
   const data = useAppSelector(selector);
+  const nes = useExecutionState(data?.nodeId);
   const { t } = useTranslation();
 
-  if (!data) {
+  if (!data || !nes) {
     return <IAINoContentFallback label={t('nodes.noNodeSelected')} icon={null} />;
   }
 
-  if (data.outputs.length === 0) {
+  if (nes.outputs.length === 0) {
     return <IAINoContentFallback label={t('nodes.noOutputRecorded')} icon={null} />;
   }
 
@@ -49,11 +52,11 @@ const InspectorOutputsTab = () => {
       <ScrollableContent>
         <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
           {data.outputType === 'image_output' ? (
-            data.outputs.map((result, i) => (
+            nes.outputs.map((result, i) => (
               <ImageOutputPreview key={getKey(result, i)} output={result as ImageOutput} />
             ))
           ) : (
-            <DataViewer data={data.outputs} label={t('nodes.nodeOutputs')} />
+            <DataViewer data={nes.outputs} label={t('nodes.nodeOutputs')} />
           )}
         </Flex>
       </ScrollableContent>

invokeai/frontend/web/src/features/nodes/components/sidePanel/inspector/InspectorTemplateTab.tsx

@@ -1,25 +1,26 @@
+import { useStore } from '@nanostores/react';
 import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
 import { useAppSelector } from 'app/store/storeHooks';
 import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import DataViewer from 'features/gallery/components/ImageMetadataViewer/DataViewer';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { memo } from 'react';
+import { $templates, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { selectLastSelectedNode } from 'features/nodes/store/selectors';
+import { memo, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 
-const selector = createMemoizedSelector(selectNodesSlice, (nodes) => {
-  const lastSelectedNodeId = nodes.selectedNodes[nodes.selectedNodes.length - 1];
-
-  const lastSelectedNode = nodes.nodes.find((node) => node.id === lastSelectedNodeId);
-
-  const lastSelectedNodeTemplate = lastSelectedNode ? nodes.templates[lastSelectedNode.data.type] : undefined;
-
-  return {
-    template: lastSelectedNodeTemplate,
-  };
-});
-
 const NodeTemplateInspector = () => {
-  const { template } = useAppSelector(selector);
+  const templates = useStore($templates);
+  const selector = useMemo(
+    () =>
+      createMemoizedSelector(selectNodesSlice, (nodes) => {
+        const lastSelectedNode = selectLastSelectedNode(nodes);
+        const lastSelectedNodeTemplate = lastSelectedNode ? templates[lastSelectedNode.data.type] : undefined;
+
+        return lastSelectedNodeTemplate;
+      }),
+    [templates]
+  );
+  const template = useAppSelector(selector);
   const { t } = useTranslation();
 
   if (!template) {

invokeai/frontend/web/src/features/nodes/components/sidePanel/viewMode/WorkflowField.tsx

@@ -1,6 +1,7 @@
 import { Flex, FormLabel, Icon, IconButton, Spacer, Tooltip } from '@invoke-ai/ui-library';
 import FieldTooltipContent from 'features/nodes/components/flow/nodes/Invocation/fields/FieldTooltipContent';
 import InputFieldRenderer from 'features/nodes/components/flow/nodes/Invocation/fields/InputFieldRenderer';
+import { MissingFallback } from 'features/nodes/components/flow/nodes/Invocation/MissingFallback';
 import { useFieldLabel } from 'features/nodes/hooks/useFieldLabel';
 import { useFieldOriginalValue } from 'features/nodes/hooks/useFieldOriginalValue';
 import { useFieldTemplateTitle } from 'features/nodes/hooks/useFieldTemplateTitle';
@@ -14,7 +15,7 @@ type Props = {
   fieldName: string;
 };
 
-const WorkflowField = ({ nodeId, fieldName }: Props) => {
+const WorkflowFieldInternal = ({ nodeId, fieldName }: Props) => {
   const label = useFieldLabel(nodeId, fieldName);
   const fieldTemplateTitle = useFieldTemplateTitle(nodeId, fieldName, 'inputs');
   const { isValueChanged, onReset } = useFieldOriginalValue(nodeId, fieldName);
@@ -50,4 +51,12 @@ const WorkflowField = ({ nodeId, fieldName }: Props) => {
   );
 };
 
+const WorkflowField = ({ nodeId, fieldName }: Props) => {
+  return (
+    <MissingFallback nodeId={nodeId} fieldName={fieldName}>
+      <WorkflowFieldInternal nodeId={nodeId} fieldName={fieldName} />
+    </MissingFallback>
+  );
+};
+
 export default memo(WorkflowField);

invokeai/frontend/web/src/features/nodes/components/sidePanel/workflow/WorkflowLinearTab.tsx

@@ -6,10 +6,10 @@ import { IAINoContentFallback } from 'common/components/IAIImageFallback';
 import ScrollableContent from 'common/components/OverlayScrollbars/ScrollableContent';
 import DndSortable from 'features/dnd/components/DndSortable';
 import type { DragEndEvent } from 'features/dnd/types';
-import LinearViewField from 'features/nodes/components/flow/nodes/Invocation/fields/LinearViewField';
+import LinearViewFieldInternal from 'features/nodes/components/flow/nodes/Invocation/fields/LinearViewField';
 import { selectWorkflowSlice, workflowExposedFieldsReordered } from 'features/nodes/store/workflowSlice';
 import type { FieldIdentifier } from 'features/nodes/types/field';
-import { memo, useCallback } from 'react';
+import { memo, useCallback, useMemo } from 'react';
 import { useTranslation } from 'react-i18next';
 import { useGetOpenAPISchemaQuery } from 'services/api/endpoints/appInfo';
 
@@ -40,16 +40,18 @@ const WorkflowLinearTab = () => {
     [dispatch, fields]
   );
 
+  const items = useMemo(() => fields.map((field) => `${field.nodeId}.${field.fieldName}`), [fields]);
+
   return (
     <Box position="relative" w="full" h="full">
       <ScrollableContent>
-        <DndSortable onDragEnd={handleDragEnd} items={fields.map((field) => `${field.nodeId}.${field.fieldName}`)}>
+        <DndSortable onDragEnd={handleDragEnd} items={items}>
           <Flex position="relative" flexDir="column" alignItems="flex-start" p={1} gap={2} h="full" w="full">
             {isLoading ? (
               <IAINoContentFallback label={t('nodes.loadingNodes')} icon={null} />
             ) : fields.length ? (
               fields.map(({ nodeId, fieldName }) => (
-                <LinearViewField key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
+                <LinearViewFieldInternal key={`${nodeId}.${fieldName}`} nodeId={nodeId} fieldName={fieldName} />
               ))
             ) : (
               <IAINoContentFallback label={t('nodes.noFieldsLinearview')} icon={null} />

invokeai/frontend/web/src/features/nodes/hooks/useAnyOrDirectInputFieldNames.ts

@@ -1,31 +1,27 @@
 import { EMPTY_ARRAY } from 'app/store/constants';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplate } from 'features/nodes/store/selectors';
+import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
+import { isSingleOrCollection } from 'features/nodes/types/field';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
 import { TEMPLATE_BUILDER_MAP } from 'features/nodes/util/schema/buildFieldInputTemplate';
 import { keys, map } from 'lodash-es';
 import { useMemo } from 'react';
 
 export const useAnyOrDirectInputFieldNames = (nodeId: string): string[] => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const template = selectNodeTemplate(nodes, nodeId);
-        if (!template) {
-          return EMPTY_ARRAY;
-        }
-        const fields = map(template.inputs).filter(
-          (field) =>
-            (['any', 'direct'].includes(field.input) || field.type.isCollectionOrScalar) &&
-            keys(TEMPLATE_BUILDER_MAP).includes(field.type.name)
-        );
-        return getSortedFilteredFieldNames(fields);
-      }),
-    [nodeId]
-  );
+  const template = useNodeTemplate(nodeId);
+
+  const fieldNames = useMemo(() => {
+    const fields = map(template.inputs).filter((field) => {
+      return (
+        (['any', 'direct'].includes(field.input) || isSingleOrCollection(field.type)) &&
+        keys(TEMPLATE_BUILDER_MAP).includes(field.type.name)
+      );
+    });
+    const _fieldNames = getSortedFilteredFieldNames(fields);
+    if (_fieldNames.length === 0) {
+      return EMPTY_ARRAY;
+    }
+    return _fieldNames;
+  }, [template.inputs]);
 
-  const fieldNames = useAppSelector(selector);
   return fieldNames;
 };

invokeai/frontend/web/src/features/nodes/hooks/useBuildNode.ts

@@ -1,4 +1,5 @@
-import { useAppSelector } from 'app/store/storeHooks';
+import { useStore } from '@nanostores/react';
+import { $templates } from 'features/nodes/store/nodesSlice';
 import { NODE_WIDTH } from 'features/nodes/types/constants';
 import type { AnyNode, InvocationTemplate } from 'features/nodes/types/invocation';
 import { buildCurrentImageNode } from 'features/nodes/util/node/buildCurrentImageNode';
@@ -8,8 +9,7 @@ import { useCallback } from 'react';
 import { useReactFlow } from 'reactflow';
 
 export const useBuildNode = () => {
-  const nodeTemplates = useAppSelector((s) => s.nodes.templates);
-
+  const templates = useStore($templates);
   const flow = useReactFlow();
 
   return useCallback(
@@ -41,10 +41,10 @@ export const useBuildNode = () => {
 
       // TODO: Keep track of invocation types so we do not need to cast this
       // We know it is safe because the caller of this function gets the `type` arg from the list of invocation templates.
-      const template = nodeTemplates[type] as InvocationTemplate;
+      const template = templates[type] as InvocationTemplate;
 
       return buildInvocationNode(position, template);
     },
-    [nodeTemplates, flow]
+    [templates, flow]
   );
 };

invokeai/frontend/web/src/features/nodes/hooks/useConnection.ts

@@ -0,0 +1,115 @@
+import { useStore } from '@nanostores/react';
+import { useAppStore } from 'app/store/storeHooks';
+import { $mouseOverNode } from 'features/nodes/hooks/useMouseOverNode';
+import {
+  $didUpdateEdge,
+  $edgePendingUpdate,
+  $isAddNodePopoverOpen,
+  $pendingConnection,
+  $templates,
+  edgesChanged,
+} from 'features/nodes/store/nodesSlice';
+import { getFirstValidConnection } from 'features/nodes/store/util/getFirstValidConnection';
+import { connectionToEdge } from 'features/nodes/store/util/reactFlowUtil';
+import { useCallback, useMemo } from 'react';
+import type { EdgeChange, OnConnect, OnConnectEnd, OnConnectStart } from 'reactflow';
+import { useUpdateNodeInternals } from 'reactflow';
+import { assert } from 'tsafe';
+
+export const useConnection = () => {
+  const store = useAppStore();
+  const templates = useStore($templates);
+  const updateNodeInternals = useUpdateNodeInternals();
+
+  const onConnectStart = useCallback<OnConnectStart>(
+    (event, { nodeId, handleId, handleType }) => {
+      assert(nodeId && handleId && handleType, 'Invalid connection start event');
+      const nodes = store.getState().nodes.present.nodes;
+
+      const node = nodes.find((n) => n.id === nodeId);
+      if (!node) {
+        return;
+      }
+
+      const template = templates[node.data.type];
+      if (!template) {
+        return;
+      }
+
+      const fieldTemplates = template[handleType === 'source' ? 'outputs' : 'inputs'];
+      const fieldTemplate = fieldTemplates[handleId];
+      if (!fieldTemplate) {
+        return;
+      }
+
+      $pendingConnection.set({ nodeId, handleId, handleType, fieldTemplate });
+    },
+    [store, templates]
+  );
+  const onConnect = useCallback<OnConnect>(
+    (connection) => {
+      const { dispatch } = store;
+      const newEdge = connectionToEdge(connection);
+      dispatch(edgesChanged([{ type: 'add', item: newEdge }]));
+      updateNodeInternals([newEdge.source, newEdge.target]);
+      $pendingConnection.set(null);
+    },
+    [store, updateNodeInternals]
+  );
+  const onConnectEnd = useCallback<OnConnectEnd>(() => {
+    const { dispatch } = store;
+    const pendingConnection = $pendingConnection.get();
+    const edgePendingUpdate = $edgePendingUpdate.get();
+    const mouseOverNodeId = $mouseOverNode.get();
+
+    // If we are in the middle of an edge update, and the mouse isn't over a node, we should just bail so the edge
+    // update logic can finish up
+    if (edgePendingUpdate && !mouseOverNodeId) {
+      $pendingConnection.set(null);
+      return;
+    }
+
+    if (!pendingConnection) {
+      return;
+    }
+    const { nodes, edges } = store.getState().nodes.present;
+    if (mouseOverNodeId) {
+      const { handleType } = pendingConnection;
+      const source = handleType === 'source' ? pendingConnection.nodeId : mouseOverNodeId;
+      const sourceHandle = handleType === 'source' ? pendingConnection.handleId : null;
+      const target = handleType === 'target' ? pendingConnection.nodeId : mouseOverNodeId;
+      const targetHandle = handleType === 'target' ? pendingConnection.handleId : null;
+
+      const connection = getFirstValidConnection(
+        source,
+        sourceHandle,
+        target,
+        targetHandle,
+        nodes,
+        edges,
+        templates,
+        edgePendingUpdate
+      );
+      if (connection) {
+        const newEdge = connectionToEdge(connection);
+        const edgeChanges: EdgeChange[] = [{ type: 'add', item: newEdge }];
+
+        const nodesToUpdate = [newEdge.source, newEdge.target];
+        if (edgePendingUpdate) {
+          $didUpdateEdge.set(true);
+          edgeChanges.push({ type: 'remove', id: edgePendingUpdate.id });
+          nodesToUpdate.push(edgePendingUpdate.source, edgePendingUpdate.target);
+        }
+        dispatch(edgesChanged(edgeChanges));
+        updateNodeInternals(nodesToUpdate);
+      }
+      $pendingConnection.set(null);
+    } else {
+      // The mouse is not over a node - we should open the add node popover
+      $isAddNodePopoverOpen.set(true);
+    }
+  }, [store, templates, updateNodeInternals]);
+
+  const api = useMemo(() => ({ onConnectStart, onConnect, onConnectEnd }), [onConnectStart, onConnect, onConnectEnd]);
+  return api;
+};

invokeai/frontend/web/src/features/nodes/hooks/useConnectionInputFieldNames.ts

@@ -1,34 +1,29 @@
 import { EMPTY_ARRAY } from 'app/store/constants';
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectNodeTemplate } from 'features/nodes/store/selectors';
+import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
+import { isSingleOrCollection } from 'features/nodes/types/field';
 import { getSortedFilteredFieldNames } from 'features/nodes/util/node/getSortedFilteredFieldNames';
 import { TEMPLATE_BUILDER_MAP } from 'features/nodes/util/schema/buildFieldInputTemplate';
 import { keys, map } from 'lodash-es';
 import { useMemo } from 'react';
 
 export const useConnectionInputFieldNames = (nodeId: string): string[] => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        const template = selectNodeTemplate(nodes, nodeId);
-        if (!template) {
-          return EMPTY_ARRAY;
-        }
+  const template = useNodeTemplate(nodeId);
+  const fieldNames = useMemo(() => {
+    // get the visible fields
+    const fields = map(template.inputs).filter(
+      (field) =>
+        (field.input === 'connection' && !isSingleOrCollection(field.type)) ||
+        !keys(TEMPLATE_BUILDER_MAP).includes(field.type.name)
+    );
 
-        // get the visible fields
-        const fields = map(template.inputs).filter(
-          (field) =>
-            (field.input === 'connection' && !field.type.isCollectionOrScalar) ||
-            !keys(TEMPLATE_BUILDER_MAP).includes(field.type.name)
-        );
+    const _fieldNames = getSortedFilteredFieldNames(fields);
 
-        return getSortedFilteredFieldNames(fields);
-      }),
-    [nodeId]
-  );
+    if (_fieldNames.length === 0) {
+      return EMPTY_ARRAY;
+    }
+
+    return _fieldNames;
+  }, [template.inputs]);
 
-  const fieldNames = useAppSelector(selector);
   return fieldNames;
 };

invokeai/frontend/web/src/features/nodes/hooks/useConnectionState.ts

@@ -1,16 +1,10 @@
+import { useStore } from '@nanostores/react';
 import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { makeConnectionErrorSelector } from 'features/nodes/store/util/makeIsConnectionValidSelector';
+import { $edgePendingUpdate, $pendingConnection, $templates, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { makeConnectionErrorSelector } from 'features/nodes/store/util/makeConnectionErrorSelector';
 import { useMemo } from 'react';
 
-import { useFieldType } from './useFieldType.ts';
-
-const selectIsConnectionInProgress = createSelector(
-  selectNodesSlice,
-  (nodes) => nodes.connectionStartFieldType !== null && nodes.connectionStartParams !== null
-);
-
 type UseConnectionStateProps = {
   nodeId: string;
   fieldName: string;
@@ -18,7 +12,9 @@ type UseConnectionStateProps = {
 };
 
 export const useConnectionState = ({ nodeId, fieldName, kind }: UseConnectionStateProps) => {
-  const fieldType = useFieldType(nodeId, fieldName, kind);
+  const pendingConnection = useStore($pendingConnection);
+  const templates = useStore($templates);
+  const edgePendingUpdate = useStore($edgePendingUpdate);
 
   const selectIsConnected = useMemo(
     () =>
@@ -35,38 +31,35 @@ export const useConnectionState = ({ nodeId, fieldName, kind }: UseConnectionSta
     [fieldName, kind, nodeId]
   );
 
-  const selectConnectionError = useMemo(
-    () => makeConnectionErrorSelector(nodeId, fieldName, kind === 'inputs' ? 'target' : 'source', fieldType),
-    [nodeId, fieldName, kind, fieldType]
-  );
-
-  const selectIsConnectionStartField = useMemo(
-    () =>
-      createSelector(selectNodesSlice, (nodes) =>
-        Boolean(
-          nodes.connectionStartParams?.nodeId === nodeId &&
-            nodes.connectionStartParams?.handleId === fieldName &&
-            nodes.connectionStartParams?.handleType === { inputs: 'target', outputs: 'source' }[kind]
-        )
-      ),
-    [fieldName, kind, nodeId]
+  const selectValidationResult = useMemo(
+    () => makeConnectionErrorSelector(templates, nodeId, fieldName, kind === 'inputs' ? 'target' : 'source'),
+    [templates, nodeId, fieldName, kind]
   );
 
   const isConnected = useAppSelector(selectIsConnected);
-  const isConnectionInProgress = useAppSelector(selectIsConnectionInProgress);
-  const isConnectionStartField = useAppSelector(selectIsConnectionStartField);
-  const connectionError = useAppSelector(selectConnectionError);
+  const isConnectionInProgress = useMemo(() => Boolean(pendingConnection), [pendingConnection]);
+  const isConnectionStartField = useMemo(() => {
+    if (!pendingConnection) {
+      return false;
+    }
+    return (
+      pendingConnection.nodeId === nodeId &&
+      pendingConnection.handleId === fieldName &&
+      pendingConnection.fieldTemplate.fieldKind === { inputs: 'input', outputs: 'output' }[kind]
+    );
+  }, [fieldName, kind, nodeId, pendingConnection]);
+  const validationResult = useAppSelector((s) => selectValidationResult(s, pendingConnection, edgePendingUpdate));
 
   const shouldDim = useMemo(
-    () => Boolean(isConnectionInProgress && connectionError && !isConnectionStartField),
-    [connectionError, isConnectionInProgress, isConnectionStartField]
+    () => Boolean(isConnectionInProgress && !validationResult.isValid && !isConnectionStartField),
+    [validationResult, isConnectionInProgress, isConnectionStartField]
   );
 
   return {
     isConnected,
     isConnectionInProgress,
     isConnectionStartField,
-    connectionError,
+    validationResult,
     shouldDim,
   };
 };

invokeai/frontend/web/src/features/nodes/hooks/useCopyPaste.ts

@@ -0,0 +1,121 @@
+import { getStore } from 'app/store/nanostores/store';
+import { deepClone } from 'common/util/deepClone';
+import {
+  $copiedEdges,
+  $copiedNodes,
+  $cursorPos,
+  $edgesToCopiedNodes,
+  edgesChanged,
+  nodesChanged,
+  selectNodesSlice,
+} from 'features/nodes/store/nodesSlice';
+import { findUnoccupiedPosition } from 'features/nodes/store/util/findUnoccupiedPosition';
+import { isEqual, uniqWith } from 'lodash-es';
+import type { EdgeChange, NodeChange } from 'reactflow';
+import { v4 as uuidv4 } from 'uuid';
+
+const copySelection = () => {
+  // Use the imperative API here so we don't have to pass the whole slice around
+  const { getState } = getStore();
+  const { nodes, edges } = selectNodesSlice(getState());
+  const selectedNodes = nodes.filter((node) => node.selected);
+  const selectedEdges = edges.filter((edge) => edge.selected);
+  const edgesToSelectedNodes = edges.filter((edge) => selectedNodes.some((node) => node.id === edge.target));
+  $copiedNodes.set(selectedNodes);
+  $copiedEdges.set(selectedEdges);
+  $edgesToCopiedNodes.set(edgesToSelectedNodes);
+};
+
+const pasteSelection = (withEdgesToCopiedNodes?: boolean) => {
+  const { getState, dispatch } = getStore();
+  const { nodes, edges } = selectNodesSlice(getState());
+  const cursorPos = $cursorPos.get();
+
+  const copiedNodes = deepClone($copiedNodes.get());
+  let copiedEdges = deepClone($copiedEdges.get());
+
+  if (withEdgesToCopiedNodes) {
+    const edgesToCopiedNodes = deepClone($edgesToCopiedNodes.get());
+    copiedEdges = uniqWith([...copiedEdges, ...edgesToCopiedNodes], isEqual);
+  }
+
+  // Calculate an offset to reposition nodes to surround the cursor position, maintaining relative positioning
+  const xCoords = copiedNodes.map((node) => node.position.x);
+  const yCoords = copiedNodes.map((node) => node.position.y);
+  const minX = Math.min(...xCoords);
+  const minY = Math.min(...yCoords);
+  const offsetX = cursorPos ? cursorPos.x - minX : 50;
+  const offsetY = cursorPos ? cursorPos.y - minY : 50;
+
+  copiedNodes.forEach((node) => {
+    const { x, y } = findUnoccupiedPosition(nodes, node.position.x + offsetX, node.position.y + offsetY);
+    node.position.x = x;
+    node.position.y = y;
+    // Pasted nodes are selected
+    node.selected = true;
+    // Also give em a fresh id
+    const id = uuidv4();
+    // Update the edges to point to the new node id
+    for (const edge of copiedEdges) {
+      if (edge.source === node.id) {
+        edge.source = id;
+        edge.id = edge.id.replace(node.data.id, id);
+      }
+      if (edge.target === node.id) {
+        edge.target = id;
+        edge.id = edge.id.replace(node.data.id, id);
+      }
+    }
+    node.id = id;
+    node.data.id = id;
+  });
+
+  const nodeChanges: NodeChange[] = [];
+  const edgeChanges: EdgeChange[] = [];
+  // Deselect existing nodes
+  nodes.forEach(({ id, selected }) => {
+    if (selected) {
+      nodeChanges.push({
+        type: 'select',
+        id,
+        selected: false,
+      });
+    }
+  });
+  // Add new nodes
+  copiedNodes.forEach((n) => {
+    nodeChanges.push({
+      type: 'add',
+      item: n,
+    });
+  });
+  // Deselect existing edges
+  edges.forEach(({ id, selected }) => {
+    if (selected) {
+      edgeChanges.push({
+        type: 'select',
+        id,
+        selected: false,
+      });
+    }
+  });
+  // Add new edges
+  copiedEdges.forEach((e) => {
+    edgeChanges.push({
+      type: 'add',
+      item: e,
+    });
+  });
+  if (nodeChanges.length > 0) {
+    dispatch(nodesChanged(nodeChanges));
+  }
+  if (edgeChanges.length > 0) {
+    dispatch(edgesChanged(edgeChanges));
+  }
+};
+
+const api = { copySelection, pasteSelection };
+
+export const useCopyPaste = () => {
+  return api;
+};

invokeai/frontend/web/src/features/nodes/hooks/useDoesFieldExist.ts

@@ -0,0 +1,20 @@
+import { useAppSelector } from 'app/store/storeHooks';
+import { isInvocationNode } from 'features/nodes/types/invocation';
+
+export const useDoesFieldExist = (nodeId: string, fieldName?: string) => {
+  const doesFieldExist = useAppSelector((s) => {
+    const node = s.nodes.present.nodes.find((n) => n.id === nodeId);
+    if (!isInvocationNode(node)) {
+      return false;
+    }
+    if (fieldName === undefined) {
+      return true;
+    }
+    if (!node.data.inputs[fieldName]) {
+      return false;
+    }
+    return true;
+  });
+
+  return doesFieldExist;
+};

invokeai/frontend/web/src/features/nodes/hooks/useExecutionState.ts

@@ -0,0 +1,56 @@
+import { useStore } from '@nanostores/react';
+import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useAppSelector } from 'app/store/storeHooks';
+import { deepClone } from 'common/util/deepClone';
+import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import type { NodeExecutionStates } from 'features/nodes/store/types';
+import type { NodeExecutionState } from 'features/nodes/types/invocation';
+import { zNodeStatus } from 'features/nodes/types/invocation';
+import { map } from 'nanostores';
+import { useEffect, useMemo } from 'react';
+
+export const $nodeExecutionStates = map<NodeExecutionStates>({});
+
+const initialNodeExecutionState: Omit<NodeExecutionState, 'nodeId'> = {
+  status: zNodeStatus.enum.PENDING,
+  error: null,
+  progress: null,
+  progressImage: null,
+  outputs: [],
+};
+
+export const useExecutionState = (nodeId?: string) => {
+  const executionStates = useStore($nodeExecutionStates, nodeId ? { keys: [nodeId] } : undefined);
+  const executionState = useMemo(() => (nodeId ? executionStates[nodeId] : undefined), [executionStates, nodeId]);
+  return executionState;
+};
+
+const removeNodeExecutionState = (nodeId: string) => {
+  $nodeExecutionStates.setKey(nodeId, undefined);
+};
+
+export const upsertExecutionState = (nodeId: string, updates?: Partial<NodeExecutionState>) => {
+  const state = $nodeExecutionStates.get()[nodeId];
+  if (!state) {
+    $nodeExecutionStates.setKey(nodeId, { ...deepClone(initialNodeExecutionState), nodeId, ...updates });
+  } else {
+    $nodeExecutionStates.setKey(nodeId, { ...state, ...updates });
+  }
+};
+
+const selectNodeIds = createMemoizedSelector(selectNodesSlice, (nodesSlice) => nodesSlice.nodes.map((node) => node.id));
+
+export const useSyncExecutionState = () => {
+  const nodeIds = useAppSelector(selectNodeIds);
+  useEffect(() => {
+    const nodeExecutionStates = $nodeExecutionStates.get();
+    const nodeIdsToAdd = nodeIds.filter((id) => !nodeExecutionStates[id]);
+    const nodeIdsToRemove = Object.keys(nodeExecutionStates).filter((id) => !nodeIds.includes(id));
+    for (const id of nodeIdsToAdd) {
+      upsertExecutionState(id);
+    }
+    for (const id of nodeIdsToRemove) {
+      removeNodeExecutionState(id);
+    }
+  }, [nodeIds]);
+};

invokeai/frontend/web/src/features/nodes/hooks/useFieldInputTemplate.ts

@@ -1,20 +1,9 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectFieldInputTemplate } from 'features/nodes/store/selectors';
+import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import type { FieldInputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
 export const useFieldInputTemplate = (nodeId: string, fieldName: string): FieldInputTemplate | null => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        return selectFieldInputTemplate(nodes, nodeId, fieldName);
-      }),
-    [fieldName, nodeId]
-  );
-
-  const fieldTemplate = useAppSelector(selector);
-
+  const template = useNodeTemplate(nodeId);
+  const fieldTemplate = useMemo(() => template.inputs[fieldName] ?? null, [fieldName, template.inputs]);
   return fieldTemplate;
 };

invokeai/frontend/web/src/features/nodes/hooks/useFieldOutputTemplate.ts

@@ -1,20 +1,9 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectFieldOutputTemplate } from 'features/nodes/store/selectors';
+import { useNodeTemplate } from 'features/nodes/hooks/useNodeTemplate';
 import type { FieldOutputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
 
 export const useFieldOutputTemplate = (nodeId: string, fieldName: string): FieldOutputTemplate | null => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        return selectFieldOutputTemplate(nodes, nodeId, fieldName);
-      }),
-    [fieldName, nodeId]
-  );
-
-  const fieldTemplate = useAppSelector(selector);
-
+  const template = useNodeTemplate(nodeId);
+  const fieldTemplate = useMemo(() => template.outputs[fieldName] ?? null, [fieldName, template.outputs]);
   return fieldTemplate;
 };

invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplate.ts

@@ -1,27 +1,36 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
+import { useStore } from '@nanostores/react';
+import { createSelector } from '@reduxjs/toolkit';
 import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectFieldInputTemplate, selectFieldOutputTemplate } from 'features/nodes/store/selectors';
+import { $templates, selectNodesSlice } from 'features/nodes/store/nodesSlice';
+import { selectInvocationNodeType } from 'features/nodes/store/selectors';
 import type { FieldInputTemplate, FieldOutputTemplate } from 'features/nodes/types/field';
 import { useMemo } from 'react';
+import { assert } from 'tsafe';
 
 export const useFieldTemplate = (
   nodeId: string,
   fieldName: string,
   kind: 'inputs' | 'outputs'
-): FieldInputTemplate | FieldOutputTemplate | null => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        if (kind === 'inputs') {
-          return selectFieldInputTemplate(nodes, nodeId, fieldName);
-        }
-        return selectFieldOutputTemplate(nodes, nodeId, fieldName);
-      }),
-    [fieldName, kind, nodeId]
+): FieldInputTemplate | FieldOutputTemplate => {
+  const templates = useStore($templates);
+  const selectNodeType = useMemo(
+    () => createSelector(selectNodesSlice, (nodes) => selectInvocationNodeType(nodes, nodeId)),
+    [nodeId]
   );
-
-  const fieldTemplate = useAppSelector(selector);
+  const nodeType = useAppSelector(selectNodeType);
+  const fieldTemplate = useMemo(() => {
+    const template = templates[nodeType];
+    assert(template, `Template for node type ${nodeType} not found`);
+    if (kind === 'inputs') {
+      const fieldTemplate = template.inputs[fieldName];
+      assert(fieldTemplate, `Field template for field ${fieldName} not found`);
+      return fieldTemplate;
+    } else {
+      const fieldTemplate = template.outputs[fieldName];
+      assert(fieldTemplate, `Field template for field ${fieldName} not found`);
+      return fieldTemplate;
+    }
+  }, [fieldName, kind, nodeType, templates]);
 
   return fieldTemplate;
 };

invokeai/frontend/web/src/features/nodes/hooks/useFieldTemplateTitle.ts

@@ -1,22 +1,8 @@
-import { createSelector } from '@reduxjs/toolkit';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectFieldInputTemplate, selectFieldOutputTemplate } from 'features/nodes/store/selectors';
+import { useFieldTemplate } from 'features/nodes/hooks/useFieldTemplate';
 import { useMemo } from 'react';
 
 export const useFieldTemplateTitle = (nodeId: string, fieldName: string, kind: 'inputs' | 'outputs'): string | null => {
-  const selector = useMemo(
-    () =>
-      createSelector(selectNodesSlice, (nodes) => {
-        if (kind === 'inputs') {
-          return selectFieldInputTemplate(nodes, nodeId, fieldName)?.title ?? null;
-        }
-        return selectFieldOutputTemplate(nodes, nodeId, fieldName)?.title ?? null;
-      }),
-    [fieldName, kind, nodeId]
-  );
-
-  const fieldTemplateTitle = useAppSelector(selector);
-
+  const fieldTemplate = useFieldTemplate(nodeId, fieldName, kind);
+  const fieldTemplateTitle = useMemo(() => fieldTemplate.title, [fieldTemplate]);
   return fieldTemplateTitle;
 };

invokeai/frontend/web/src/features/nodes/hooks/useFieldType.ts.ts

@@ -1,23 +0,0 @@
-import { createMemoizedSelector } from 'app/store/createMemoizedSelector';
-import { useAppSelector } from 'app/store/storeHooks';
-import { selectNodesSlice } from 'features/nodes/store/nodesSlice';
-import { selectFieldInputTemplate, selectFieldOutputTemplate } from 'features/nodes/store/selectors';
-import type { FieldType } from 'features/nodes/types/field';
-import { useMemo } from 'react';
-
-export const useFieldType = (nodeId: string, fieldName: string, kind: 'inputs' | 'outputs'): FieldType | null => {
-  const selector = useMemo(
-    () =>
-      createMemoizedSelector(selectNodesSlice, (nodes) => {
-        if (kind === 'inputs') {
-          return selectFieldInputTemplate(nodes, nodeId, fieldName)?.type ?? null;
-        }
-        return selectFieldOutputTemplate(nodes, nodeId, fieldName)?.type ?? null;
-      }),
-    [fieldName, kind, nodeId]
-  );
-
-  const fieldType = useAppSelector(selector);
-
-  return fieldType;
-};