diff --git a/docs/contributing/INVOCATIONS.md b/docs/contributing/INVOCATIONS.md
index 3809bd4178..b34a2f25ac 100644
--- a/docs/contributing/INVOCATIONS.md
+++ b/docs/contributing/INVOCATIONS.md
@@ -29,12 +29,13 @@ The first set of things we need to do when creating a new Invocation are -
 
 - Create a new class that derives from a predefined parent class called
   `BaseInvocation`.
-- The name of every Invocation must end with the word `Invocation` in order for
-  it to be recognized as an Invocation.
 - Every Invocation must have a `docstring` that describes what this Invocation
   does.
-- Every Invocation must have a unique `type` field defined which becomes its
-  indentifier.
+- While not strictly required, we suggest every invocation class name ends in
+  "Invocation", eg "CropImageInvocation".
+- Every Invocation must use the `@invocation` decorator to provide its unique
+  invocation type. You may also provide its title, tags and category using the
+  decorator.
 - Invocations are strictly typed. We make use of the native
   [typing](https://docs.python.org/3/library/typing.html) library and the
   installed [pydantic](https://pydantic-docs.helpmanual.io/) library for
@@ -43,12 +44,11 @@ The first set of things we need to do when creating a new Invocation are -
 So let us do that.
 
 ```python
-from typing import Literal
-from .baseinvocation import BaseInvocation
+from .baseinvocation import BaseInvocation, invocation
 
+@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
-    type: Literal['resize'] = 'resize'
 ```
 
 That's great.
@@ -62,8 +62,10 @@ our Invocation takes.
 
 ### **Inputs**
 
-Every Invocation input is a pydantic `Field` and like everything else should be
-strictly typed and defined.
+Every Invocation input must be defined using the `InputField` function. This is
+a wrapper around the pydantic `Field` function, which handles a few extra things
+and provides type hints. Like everything else, this should be strictly typed and
+defined.
 
 So let us create these inputs for our Invocation. First up, the `image` input we
 need. Generally, we can use standard variable types in Python but InvokeAI
@@ -76,55 +78,51 @@ create your own custom field types later in this guide. For now, let's go ahead
 and use it.
 
 ```python
-from typing import Literal, Union
-from pydantic import Field
-
-from .baseinvocation import BaseInvocation
-from ..models.image import ImageField
+from .baseinvocation import BaseInvocation, InputField, invocation
+from .primitives import ImageField
 
+@invocation('resize')
 class ResizeInvocation(BaseInvocation):
-    '''Resizes an image'''
-    type: Literal['resize'] = 'resize'
 
     # Inputs
-    image: Union[ImageField, None] = Field(description="The input image", default=None)
+    image: ImageField = InputField(description="The input image")
 ```
 
 Let us break down our input code.
 
 ```python
-image: Union[ImageField, None] = Field(description="The input image", default=None)
+image: ImageField = InputField(description="The input image")
 ```
 
-| Part      | Value                                                | Description                                                                                        |
-| --------- | ---------------------------------------------------- | -------------------------------------------------------------------------------------------------- |
-| Name      | `image`                                              | The variable that will hold our image                                                              |
-| Type Hint | `Union[ImageField, None]`                            | The types for our field. Indicates that the image can either be an `ImageField` type or `None`     |
-| Field     | `Field(description="The input image", default=None)` | The image variable is a field which needs a description and a default value that we set to `None`. |
+| Part      | Value                                       | Description                                                                     |
+| --------- | ------------------------------------------- | ------------------------------------------------------------------------------- |
+| Name      | `image`                                     | The variable that will hold our image                                           |
+| Type Hint | `ImageField`                                | The types for our field. Indicates that the image must be an `ImageField` type. |
+| Field     | `InputField(description="The input image")` | The image variable is an `InputField` which needs a description.                |
 
 Great. Now let us create our other inputs for `width` and `height`
 
 ```python
-from typing import Literal, Union
-from pydantic import Field
-
-from .baseinvocation import BaseInvocation
-from ..models.image import ImageField
+from .baseinvocation import BaseInvocation, InputField, invocation
+from .primitives import ImageField
 
+@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
-    type: Literal['resize'] = 'resize'
 
     # Inputs
-    image: Union[ImageField, None] = Field(description="The input image", default=None)
-    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
+    image: ImageField = InputField(description="The input image")
+    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 ```
 
-As you might have noticed, we added two new parameters to the field type for
-`width` and `height` called `gt` and `le`. These basically stand for _greater
-than or equal to_ and _less than or equal to_. There are various other param
-types for field that you can find on the **pydantic** documentation.
+As you might have noticed, we added two new arguments to the `InputField`
+definition for `width` and `height`, called `gt` and `le`. They stand for
+_greater than or equal to_ and _less than or equal to_.
+
+These impose contraints on those fields, and will raise an exception if the
+values do not meet the constraints. Field constraints are provided by
+**pydantic**, so anything you see in the **pydantic docs** will work.
 
 **Note:** _Any time it is possible to define constraints for our field, we
 should do it so the frontend has more information on how to parse this field._
@@ -141,20 +139,17 @@ that are provided by it by InvokeAI.
 Let us create this function first.
 
 ```python
-from typing import Literal, Union
-from pydantic import Field
-
-from .baseinvocation import BaseInvocation, InvocationContext
-from ..models.image import ImageField
+from .baseinvocation import BaseInvocation, InputField, invocation
+from .primitives import ImageField
 
+@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
-    type: Literal['resize'] = 'resize'
 
     # Inputs
-    image: Union[ImageField, None] = Field(description="The input image", default=None)
-    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
+    image: ImageField = InputField(description="The input image")
+    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
     def invoke(self, context: InvocationContext):
         pass
@@ -173,21 +168,18 @@ all the necessary info related to image outputs. So let us use that.
 We will cover how to create your own output types later in this guide.
 
 ```python
-from typing import Literal, Union
-from pydantic import Field
-
-from .baseinvocation import BaseInvocation, InvocationContext
-from ..models.image import ImageField
+from .baseinvocation import BaseInvocation, InputField, invocation
+from .primitives import ImageField
 from .image import ImageOutput
 
+@invocation('resize')
 class ResizeInvocation(BaseInvocation):
     '''Resizes an image'''
-    type: Literal['resize'] = 'resize'
 
     # Inputs
-    image: Union[ImageField, None] = Field(description="The input image", default=None)
-    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
+    image: ImageField = InputField(description="The input image")
+    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
         pass
@@ -195,39 +187,34 @@ class ResizeInvocation(BaseInvocation):
 
 Perfect. Now that we have our Invocation setup, let us do what we want to do.
 
-- We will first load the image. Generally we do this using the `PIL` library but
-  we can use one of the services provided by InvokeAI to load the image.
+- We will first load the image using one of the services provided by InvokeAI to
+  load the image.
 - We will resize the image using `PIL` to our input data.
 - We will output this image in the format we set above.
 
 So let's do that.
 
 ```python
-from typing import Literal, Union
-from pydantic import Field
-
-from .baseinvocation import BaseInvocation, InvocationContext
-from ..models.image import ImageField, ResourceOrigin, ImageCategory
+from .baseinvocation import BaseInvocation, InputField, invocation
+from .primitives import ImageField
 from .image import ImageOutput
 
+@invocation("resize")
 class ResizeInvocation(BaseInvocation):
-    '''Resizes an image'''
-    type: Literal['resize'] = 'resize'
+    """Resizes an image"""
 
-    # Inputs
-    image: Union[ImageField, None] = Field(description="The input image", default=None)
-    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
+    image: ImageField = InputField(description="The input image")
+    width: int = InputField(default=512, ge=64, le=2048, description="Width of the new image")
+    height: int = InputField(default=512, ge=64, le=2048, description="Height of the new image")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
-        # Load the image using InvokeAI's predefined Image Service.
-        image = context.services.images.get_pil_image(self.image.image_origin, self.image.image_name)
+        # Load the image using InvokeAI's predefined Image Service. Returns the PIL image.
+        image = context.services.images.get_pil_image(self.image.image_name)
 
         # Resizing the image
-        # Because we used the above service, we already have a PIL image. So we can simply resize.
         resized_image = image.resize((self.width, self.height))
 
-        # Preparing the image for output using InvokeAI's predefined Image Service.
+        # Save the image using InvokeAI's predefined Image Service. Returns the prepared PIL image.
         output_image = context.services.images.create(
             image=resized_image,
             image_origin=ResourceOrigin.INTERNAL,
@@ -241,7 +228,6 @@ class ResizeInvocation(BaseInvocation):
         return ImageOutput(
             image=ImageField(
                 image_name=output_image.image_name,
-                image_origin=output_image.image_origin,
             ),
             width=output_image.width,
             height=output_image.height,
@@ -253,6 +239,20 @@ certain way that the images need to be dispatched in order to be stored and read
 correctly. In 99% of the cases when dealing with an image output, you can simply
 copy-paste the template above.
 
+### Customization
+
+We can use the `@invocation` decorator to provide some additional info to the
+UI, like a custom title, tags and category.
+
+```python
+@invocation("resize", title="My Resizer", tags=["resize", "image"], category="My Invocations")
+class ResizeInvocation(BaseInvocation):
+    """Resizes an image"""
+
+    image: ImageField = InputField(description="The input image")
+    ...
+```
+
 That's it. You made your own **Resize Invocation**.
 
 ## Result
@@ -271,10 +271,57 @@ new Invocation ready to be used.
 ![resize node editor](../assets/contributing/resize_node_editor.png)
 
 ## Contributing Nodes
-Once you've created a Node, the next step is to share it with the community! The best way to do this is to submit a Pull Request to add the Node to the [Community Nodes](nodes/communityNodes) list. If you're not sure how to do that, take a look a at our [contributing nodes overview](contributingNodes). 
+
+Once you've created a Node, the next step is to share it with the community! The
+best way to do this is to submit a Pull Request to add the Node to the
+[Community Nodes](nodes/communityNodes) list. If you're not sure how to do that,
+take a look a at our [contributing nodes overview](contributingNodes).
 
 ## Advanced
 
+-->
+
+### Custom Output Types
+
+Like with custom inputs, sometimes you might find yourself needing custom
+outputs that InvokeAI does not provide. We can easily set one up.
+
+Now that you are familiar with Invocations and Inputs, let us use that knowledge
+to create an output that has an `image` field, a `color` field and a `string`
+field.
+
+- An invocation output is a class that derives from the parent class of
+  `BaseInvocationOutput`.
+- All invocation outputs must use the `@invocation_output` decorator to provide
+  their unique output type.
+- Output fields must use the provided `OutputField` function. This is very
+  similar to the `InputField` function described earlier - it's a wrapper around
+  `pydantic`'s `Field()`.
+- It is not mandatory but we recommend using names ending with `Output` for
+  output types.
+- It is not mandatory but we highly recommend adding a `docstring` to describe
+  what your output type is for.
+
+Now that we know the basic rules for creating a new output type, let us go ahead
+and make it.
+
+```python
+from .baseinvocation import BaseInvocationOutput, OutputField, invocation_output
+from .primitives import ImageField, ColorField
+
+@invocation_output('image_color_string_output')
+class ImageColorStringOutput(BaseInvocationOutput):
+    '''Base class for nodes that output a single image'''
+
+    image: ImageField = OutputField(description="The image")
+    color: ColorField = OutputField(description="The color")
+    text: str = OutputField(description="The string")
+```
+
+That's all there is to it.
+
+<!-- TODO: DANGER - we probably do not want people to create their own field types, because this requires a lot of work on the frontend to accomodate.
+
 ### Custom Input Fields
 
 Now that you know how to create your own Invocations, let us dive into slightly
@@ -329,172 +376,6 @@ like this.
 color: ColorField = Field(default=ColorField(r=0, g=0, b=0, a=0), description='Background color of an image')
 ```
 
-**Extra Config**
-
-All input fields also take an additional `Config` class that you can use to do
-various advanced things like setting required parameters and etc.
-
-Let us do that for our _ColorField_ and enforce all the values because we did
-not define any defaults for our fields.
-
-```python
-class ColorField(BaseModel):
-    '''A field that holds the rgba values of a color'''
-    r: int = Field(ge=0, le=255, description="The red channel")
-    g: int = Field(ge=0, le=255, description="The green channel")
-    b: int = Field(ge=0, le=255, description="The blue channel")
-    a: int = Field(ge=0, le=255, description="The alpha channel")
-
-    class Config:
-        schema_extra = {"required": ["r", "g", "b", "a"]}
-```
-
-Now it becomes mandatory for the user to supply all the values required by our
-input field.
-
-We will discuss the `Config` class in extra detail later in this guide and how
-you can use it to make your Invocations more robust.
-
-### Custom Output Types
-
-Like with custom inputs, sometimes you might find yourself needing custom
-outputs that InvokeAI does not provide. We can easily set one up.
-
-Now that you are familiar with Invocations and Inputs, let us use that knowledge
-to put together a custom output type for an Invocation that returns _width_,
-_height_ and _background_color_ that we need to create a blank image.
-
-- A custom output type is a class that derives from the parent class of
-  `BaseInvocationOutput`.
-- It is not mandatory but we recommend using names ending with `Output` for
-  output types. So we'll call our class `BlankImageOutput`
-- It is not mandatory but we highly recommend adding a `docstring` to describe
-  what your output type is for.
-- Like Invocations, each output type should have a `type` variable that is
-  **unique**
-
-Now that we know the basic rules for creating a new output type, let us go ahead
-and make it.
-
-```python
-from typing import Literal
-from pydantic import Field
-
-from .baseinvocation import BaseInvocationOutput
-
-class BlankImageOutput(BaseInvocationOutput):
-    '''Base output type for creating a blank image'''
-    type: Literal['blank_image_output'] = 'blank_image_output'
-
-    # Inputs
-    width: int = Field(description='Width of blank image')
-    height: int = Field(description='Height of blank image')
-    bg_color: ColorField = Field(description='Background color of blank image')
-
-    class Config:
-        schema_extra = {"required": ["type", "width", "height", "bg_color"]}
-```
-
-All set. We now have an output type that requires what we need to create a
-blank_image. And if you noticed it, we even used the `Config` class to ensure
-the fields are required.
-
-### Custom Configuration
-
-As you might have noticed when making inputs and outputs, we used a class called
-`Config` from _pydantic_ to further customize them. Because our inputs and
-outputs essentially inherit from _pydantic_'s `BaseModel` class, all
-[configuration options](https://docs.pydantic.dev/latest/usage/schema/#schema-customization)
-that are valid for _pydantic_ classes are also valid for our inputs and outputs.
-You can do the same for your Invocations too but InvokeAI makes our life a
-little bit easier on that end.
-
-InvokeAI provides a custom configuration class called `InvocationConfig`
-particularly for configuring Invocations. This is exactly the same as the raw
-`Config` class from _pydantic_ with some extra stuff on top to help faciliate
-parsing of the scheme in the frontend UI.
-
-At the current moment, tihs `InvocationConfig` class is further improved with
-the following features related the `ui`.
-
-| Config Option | Field Type                                                                                                    | Example                                                                                                               |
-| ------------- | ------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- |
-| type_hints    | `Dict[str, Literal["integer", "float", "boolean", "string", "enum", "image", "latents", "model", "control"]]` | `type_hint: "model"` provides type hints related to the model like displaying a list of available models              |
-| tags          | `List[str]`                                                                                                   | `tags: ['resize', 'image']` will classify your invocation under the tags of resize and image.                         |
-| title         | `str`                                                                                                         | `title: 'Resize Image` will rename your to this custom title rather than infer from the name of the Invocation class. |
-
-So let us update your `ResizeInvocation` with some extra configuration and see
-how that works.
-
-```python
-from typing import Literal, Union
-from pydantic import Field
-
-from .baseinvocation import BaseInvocation, InvocationContext, InvocationConfig
-from ..models.image import ImageField, ResourceOrigin, ImageCategory
-from .image import ImageOutput
-
-class ResizeInvocation(BaseInvocation):
-    '''Resizes an image'''
-    type: Literal['resize'] = 'resize'
-
-    # Inputs
-    image: Union[ImageField, None] = Field(description="The input image", default=None)
-    width: int = Field(default=512, ge=64, le=2048, description="Width of the new image")
-    height: int = Field(default=512, ge=64, le=2048, description="Height of the new image")
-
-    class Config(InvocationConfig):
-        schema_extra: {
-            ui: {
-                tags: ['resize', 'image'],
-                title: ['My Custom Resize']
-            }
-        }
-
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        # Load the image using InvokeAI's predefined Image Service.
-        image = context.services.images.get_pil_image(self.image.image_origin, self.image.image_name)
-
-        # Resizing the image
-        # Because we used the above service, we already have a PIL image. So we can simply resize.
-        resized_image = image.resize((self.width, self.height))
-
-        # Preparing the image for output using InvokeAI's predefined Image Service.
-        output_image = context.services.images.create(
-            image=resized_image,
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-        )
-
-        # Returning the Image
-        return ImageOutput(
-            image=ImageField(
-                image_name=output_image.image_name,
-                image_origin=output_image.image_origin,
-            ),
-            width=output_image.width,
-            height=output_image.height,
-        )
-```
-
-We now customized our code to let the frontend know that our Invocation falls
-under `resize` and `image` categories. So when the user searches for these
-particular words, our Invocation will show up too.
-
-We also set a custom title for our Invocation. So instead of being called
-`Resize`, it will be called `My Custom Resize`.
-
-As simple as that.
-
-As time goes by, InvokeAI will further improve and add more customizability for
-Invocation configuration. We will have more documentation regarding this at a
-later time.
-
-# **[TODO]**
-
 ### Custom Components For Frontend
 
 Every backend input type should have a corresponding frontend component so the
@@ -513,282 +394,4 @@ Let us create a new component for our custom color field we created above. When
 we use a color field, let us say we want the UI to display a color picker for
 the user to pick from rather than entering values. That is what we will build
 now.
-
----
-
-<!-- # OLD -- TO BE DELETED OR MOVED LATER
-
----
-
-## Creating a new invocation
-
-To create a new invocation, either find the appropriate module file in
-`/ldm/invoke/app/invocations` to add your invocation to, or create a new one in
-that folder. All invocations in that folder will be discovered and made
-available to the CLI and API automatically. Invocations make use of
-[typing](https://docs.python.org/3/library/typing.html) and
-[pydantic](https://pydantic-docs.helpmanual.io/) for validation and integration
-into the CLI and API.
-
-An invocation looks like this:
-
-```py
-class UpscaleInvocation(BaseInvocation):
-    """Upscales an image."""
-
-    # fmt: off
-    type: Literal["upscale"] = "upscale"
-
-    # Inputs
-    image: Union[ImageField, None] = Field(description="The input image", default=None)
-    strength: float                = Field(default=0.75, gt=0, le=1, description="The strength")
-    level: Literal[2, 4]           = Field(default=2, description="The upscale level")
-    # fmt: on
-
-    # Schema customisation
-    class Config(InvocationConfig):
-        schema_extra = {
-            "ui": {
-                "tags": ["upscaling", "image"],
-            },
-        }
-
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
-        results = context.services.restoration.upscale_and_reconstruct(
-            image_list=[[image, 0]],
-            upscale=(self.level, self.strength),
-            strength=0.0,  # GFPGAN strength
-            save_original=False,
-            image_callback=None,
-        )
-
-        # Results are image and seed, unwrap for now
-        # TODO: can this return multiple results?
-        image_dto = context.services.images.create(
-            image=results[0][0],
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-        )
-
-        return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
-
-```
-
-Each portion is important to implement correctly.
-
-### Class definition and type
-
-```py
-class UpscaleInvocation(BaseInvocation):
-    """Upscales an image."""
-    type: Literal['upscale'] = 'upscale'
-```
-
-All invocations must derive from `BaseInvocation`. They should have a docstring
-that declares what they do in a single, short line. They should also have a
-`type` with a type hint that's `Literal["command_name"]`, where `command_name`
-is what the user will type on the CLI or use in the API to create this
-invocation. The `command_name` must be unique. The `type` must be assigned to
-the value of the literal in the type hint.
-
-### Inputs
-
-```py
-    # Inputs
-    image: Union[ImageField,None] = Field(description="The input image")
-    strength: float               = Field(default=0.75, gt=0, le=1, description="The strength")
-    level: Literal[2,4]           = Field(default=2, description="The upscale level")
-```
-
-Inputs consist of three parts: a name, a type hint, and a `Field` with default,
-description, and validation information. For example:
-
-| Part      | Value                                                         | Description                                                                                                               |
-| --------- | ------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- |
-| Name      | `strength`                                                    | This field is referred to as `strength`                                                                                   |
-| Type Hint | `float`                                                       | This field must be of type `float`                                                                                        |
-| Field     | `Field(default=0.75, gt=0, le=1, description="The strength")` | The default value is `0.75`, the value must be in the range (0,1], and help text will show "The strength" for this field. |
-
-Notice that `image` has type `Union[ImageField,None]`. The `Union` allows this
-field to be parsed with `None` as a value, which enables linking to previous
-invocations. All fields should either provide a default value or allow `None` as
-a value, so that they can be overwritten with a linked output from another
-invocation.
-
-The special type `ImageField` is also used here. All images are passed as
-`ImageField`, which protects them from pydantic validation errors (since images
-only ever come from links).
-
-Finally, note that for all linking, the `type` of the linked fields must match.
-If the `name` also matches, then the field can be **automatically linked** to a
-previous invocation by name and matching.
-
-### Config
-
-```py
-    # Schema customisation
-    class Config(InvocationConfig):
-        schema_extra = {
-            "ui": {
-                "tags": ["upscaling", "image"],
-            },
-        }
-```
-
-This is an optional configuration for the invocation. It inherits from
-pydantic's model `Config` class, and it used primarily to customize the
-autogenerated OpenAPI schema.
-
-The UI relies on the OpenAPI schema in two ways:
-
-- An API client & Typescript types are generated from it. This happens at build
-  time.
-- The node editor parses the schema into a template used by the UI to create the
-  node editor UI. This parsing happens at runtime.
-
-In this example, a `ui` key has been added to the `schema_extra` dict to provide
-some tags for the UI, to facilitate filtering nodes.
-
-See the Schema Generation section below for more information.
-
-### Invoke Function
-
-```py
-    def invoke(self, context: InvocationContext) -> ImageOutput:
-        image = context.services.images.get_pil_image(
-            self.image.image_origin, self.image.image_name
-        )
-        results = context.services.restoration.upscale_and_reconstruct(
-            image_list=[[image, 0]],
-            upscale=(self.level, self.strength),
-            strength=0.0,  # GFPGAN strength
-            save_original=False,
-            image_callback=None,
-        )
-
-        # Results are image and seed, unwrap for now
-        # TODO: can this return multiple results?
-        image_dto = context.services.images.create(
-            image=results[0][0],
-            image_origin=ResourceOrigin.INTERNAL,
-            image_category=ImageCategory.GENERAL,
-            node_id=self.id,
-            session_id=context.graph_execution_state_id,
-            is_intermediate=self.is_intermediate,
-        )
-
-        return ImageOutput(
-            image=ImageField(
-                image_name=image_dto.image_name,
-                image_origin=image_dto.image_origin,
-            ),
-            width=image_dto.width,
-            height=image_dto.height,
-        )
-```
-
-The `invoke` function is the last portion of an invocation. It is provided an
-`InvocationContext` which contains services to perform work as well as a
-`session_id` for use as needed. It should return a class with output values that
-derives from `BaseInvocationOutput`.
-
-Before being called, the invocation will have all of its fields set from
-defaults, inputs, and finally links (overriding in that order).
-
-Assume that this invocation may be running simultaneously with other
-invocations, may be running on another machine, or in other interesting
-scenarios. If you need functionality, please provide it as a service in the
-`InvocationServices` class, and make sure it can be overridden.
-
-### Outputs
-
-```py
-class ImageOutput(BaseInvocationOutput):
-    """Base class for invocations that output an image"""
-
-    # fmt: off
-    type: Literal["image_output"] = "image_output"
-    image:      ImageField = Field(default=None, description="The output image")
-    width:             int = Field(description="The width of the image in pixels")
-    height:            int = Field(description="The height of the image in pixels")
-    # fmt: on
-
-    class Config:
-        schema_extra = {"required": ["type", "image", "width", "height"]}
-```
-
-Output classes look like an invocation class without the invoke method. Prefer
-to use an existing output class if available, and prefer to name inputs the same
-as outputs when possible, to promote automatic invocation linking.
-
-## Schema Generation
-
-Invocation, output and related classes are used to generate an OpenAPI schema.
-
-### Required Properties
-
-The schema generation treat all properties with default values as optional. This
-makes sense internally, but when when using these classes via the generated
-schema, we end up with e.g. the `ImageOutput` class having its `image` property
-marked as optional.
-
-We know that this property will always be present, so the additional logic
-needed to always check if the property exists adds a lot of extraneous cruft.
-
-To fix this, we can leverage `pydantic`'s
-[schema customisation](https://docs.pydantic.dev/usage/schema/#schema-customization)
-to mark properties that we know will always be present as required.
-
-Here's that `ImageOutput` class, without the needed schema customisation:
-
-```python
-class ImageOutput(BaseInvocationOutput):
-    """Base class for invocations that output an image"""
-
-    # fmt: off
-    type: Literal["image_output"] = "image_output"
-    image:      ImageField = Field(default=None, description="The output image")
-    width:             int = Field(description="The width of the image in pixels")
-    height:            int = Field(description="The height of the image in pixels")
-    # fmt: on
-```
-
-The OpenAPI schema that results from this `ImageOutput` will have the `type`,
-`image`, `width` and `height` properties marked as optional, even though we know
-they will always have a value.
-
-```python
-class ImageOutput(BaseInvocationOutput):
-    """Base class for invocations that output an image"""
-
-    # fmt: off
-    type: Literal["image_output"] = "image_output"
-    image:      ImageField = Field(default=None, description="The output image")
-    width:             int = Field(description="The width of the image in pixels")
-    height:            int = Field(description="The height of the image in pixels")
-    # fmt: on
-
-    # Add schema customization
-    class Config:
-        schema_extra = {"required": ["type", "image", "width", "height"]}
-```
-
-With the customization in place, the schema will now show these properties as
-required, obviating the need for extensive null checks in client code.
-
-See this `pydantic` issue for discussion on this solution:
-<https://github.com/pydantic/pydantic/discussions/4577> -->
-
+-->
diff --git a/invokeai/app/invocations/baseinvocation.py b/invokeai/app/invocations/baseinvocation.py
index f56e7c7aa5..e6f4f52f25 100644
--- a/invokeai/app/invocations/baseinvocation.py
+++ b/invokeai/app/invocations/baseinvocation.py
@@ -2,16 +2,18 @@
 
 from __future__ import annotations
 
+import json
 from abc import ABC, abstractmethod
 from enum import Enum
 from inspect import signature
-import json
+import re
 from typing import (
     TYPE_CHECKING,
     AbstractSet,
     Any,
     Callable,
     ClassVar,
+    Literal,
     Mapping,
     Optional,
     Type,
@@ -22,7 +24,7 @@ from typing import (
 )
 
 from pydantic import BaseModel, Field, validator
-from pydantic.fields import Undefined
+from pydantic.fields import Undefined, ModelField
 from pydantic.typing import NoArgAnyCallable
 
 if TYPE_CHECKING:
@@ -368,8 +370,7 @@ def OutputField(
 class UIConfigBase(BaseModel):
     """
     Provides additional node configuration to the UI.
-    This is used internally by the @tags and @title decorator logic. You probably want to use those
-    decorators, though you may add this class to a node definition to specify the title and tags.
+    This is used internally by the @invocation decorator logic. Do not use this directly.
     """
 
     tags: Optional[list[str]] = Field(default_factory=None, description="The node's tags")
@@ -387,10 +388,11 @@ class InvocationContext:
 
 
 class BaseInvocationOutput(BaseModel):
-    """Base class for all invocation outputs"""
+    """
+    Base class for all invocation outputs.
 
-    # All outputs must include a type name like this:
-    # type: Literal['your_output_name'] # noqa f821
+    All invocation outputs must use the `@invocation_output` decorator to provide their unique type.
+    """
 
     @classmethod
     def get_all_subclasses_tuple(cls):
@@ -426,12 +428,12 @@ class MissingInputException(Exception):
 
 
 class BaseInvocation(ABC, BaseModel):
-    """A node to process inputs and produce outputs.
-    May use dependency injection in __init__ to receive providers.
     """
+    A node to process inputs and produce outputs.
+    May use dependency injection in __init__ to receive providers.
 
-    # All invocations must include a type name like this:
-    # type: Literal['your_output_name'] # noqa f821
+    All invocations must use the `@invocation` decorator to provide their unique type.
+    """
 
     @classmethod
     def get_all_subclasses(cls):
@@ -511,9 +513,11 @@ class BaseInvocation(ABC, BaseModel):
                     raise MissingInputException(self.__fields__["type"].default, field_name)
         return self.invoke(context)
 
-    id: str = Field(description="The id of this node. Must be unique among all nodes.")
+    id: str = Field(
+        description="The id of this instance of an invocation. Must be unique among all instances of invocations."
+    )
     is_intermediate: bool = InputField(
-        default=False, description="Whether or not this node is an intermediate node.", ui_type=UIType.IsIntermediate
+        default=False, description="Whether or not this is an intermediate invocation.", ui_type=UIType.IsIntermediate
     )
     workflow: Optional[str] = InputField(
         default=None,
@@ -534,66 +538,85 @@ class BaseInvocation(ABC, BaseModel):
     UIConfig: ClassVar[Type[UIConfigBase]]
 
 
-T = TypeVar("T", bound=BaseInvocation)
+GenericBaseInvocation = TypeVar("GenericBaseInvocation", bound=BaseInvocation)
 
 
-def title(title: str) -> Callable[[Type[T]], Type[T]]:
-    """Adds a title to the invocation. Use this to override the default title generation, which is based on the class name."""
-
-    def wrapper(cls: Type[T]) -> Type[T]:
-        uiconf_name = cls.__qualname__ + ".UIConfig"
-        if not hasattr(cls, "UIConfig") or cls.UIConfig.__qualname__ != uiconf_name:
-            cls.UIConfig = type(uiconf_name, (UIConfigBase,), dict())
-        cls.UIConfig.title = title
-        return cls
-
-    return wrapper
-
-
-def tags(*tags: str) -> Callable[[Type[T]], Type[T]]:
-    """Adds tags to the invocation. Use this to improve the streamline finding the invocation in the UI."""
-
-    def wrapper(cls: Type[T]) -> Type[T]:
-        uiconf_name = cls.__qualname__ + ".UIConfig"
-        if not hasattr(cls, "UIConfig") or cls.UIConfig.__qualname__ != uiconf_name:
-            cls.UIConfig = type(uiconf_name, (UIConfigBase,), dict())
-        cls.UIConfig.tags = list(tags)
-        return cls
-
-    return wrapper
-
-
-def category(category: str) -> Callable[[Type[T]], Type[T]]:
-    """Adds a category to the invocation. This is used to group invocations in the UI."""
-
-    def wrapper(cls: Type[T]) -> Type[T]:
-        uiconf_name = cls.__qualname__ + ".UIConfig"
-        if not hasattr(cls, "UIConfig") or cls.UIConfig.__qualname__ != uiconf_name:
-            cls.UIConfig = type(uiconf_name, (UIConfigBase,), dict())
-        cls.UIConfig.category = category
-        return cls
-
-    return wrapper
-
-
-def node(
-    title: Optional[str] = None, tags: Optional[list[str]] = None, category: Optional[str] = None
-) -> Callable[[Type[T]], Type[T]]:
+def invocation(
+    invocation_type: str, title: Optional[str] = None, tags: Optional[list[str]] = None, category: Optional[str] = None
+) -> Callable[[Type[GenericBaseInvocation]], Type[GenericBaseInvocation]]:
     """
-    Adds metadata to the invocation as a decorator.
+    Adds metadata to an invocation.
 
-    :param Optional[str] title: Adds a title to the node. Use if the auto-generated title isn't quite right. Defaults to None.
-    :param Optional[list[str]] tags: Adds tags to the node. Nodes may be searched for by their tags. Defaults to None.
-    :param Optional[str] category: Adds a category to the node. Used to group the nodes in the UI. Defaults to None.
+    :param str invocation_type: The type of the invocation. Must be unique among all invocations.
+    :param Optional[str] title: Adds a title to the invocation. Use if the auto-generated title isn't quite right. Defaults to None.
+    :param Optional[list[str]] tags: Adds tags to the invocation. Invocations may be searched for by their tags. Defaults to None.
+    :param Optional[str] category: Adds a category to the invocation. Used to group the invocations in the UI. Defaults to None.
     """
 
-    def wrapper(cls: Type[T]) -> Type[T]:
+    def wrapper(cls: Type[GenericBaseInvocation]) -> Type[GenericBaseInvocation]:
+        # Validate invocation types on creation of invocation classes
+        # TODO: ensure unique?
+        if re.compile(r"^\S+$").match(invocation_type) is None:
+            raise ValueError(f'"invocation_type" must consist of non-whitespace characters, got "{invocation_type}"')
+
+        # Add OpenAPI schema extras
         uiconf_name = cls.__qualname__ + ".UIConfig"
         if not hasattr(cls, "UIConfig") or cls.UIConfig.__qualname__ != uiconf_name:
             cls.UIConfig = type(uiconf_name, (UIConfigBase,), dict())
-        cls.UIConfig.title = title
-        cls.UIConfig.tags = tags
-        cls.UIConfig.category = category
+        if title is not None:
+            cls.UIConfig.title = title
+        if tags is not None:
+            cls.UIConfig.tags = tags
+        if category is not None:
+            cls.UIConfig.category = category
+
+        # Add the invocation type to the pydantic model of the invocation
+        invocation_type_annotation = Literal[invocation_type]  # type: ignore
+        invocation_type_field = ModelField.infer(
+            name="type",
+            value=invocation_type,
+            annotation=invocation_type_annotation,
+            class_validators=None,
+            config=cls.__config__,
+        )
+        cls.__fields__.update({"type": invocation_type_field})
+        cls.__annotations__.update({"type": invocation_type_annotation})
+
+        return cls
+
+    return wrapper
+
+
+GenericBaseInvocationOutput = TypeVar("GenericBaseInvocationOutput", bound=BaseInvocationOutput)
+
+
+def invocation_output(
+    output_type: str,
+) -> Callable[[Type[GenericBaseInvocationOutput]], Type[GenericBaseInvocationOutput]]:
+    """
+    Adds metadata to an invocation output.
+
+    :param str output_type: The type of the invocation output. Must be unique among all invocation outputs.
+    """
+
+    def wrapper(cls: Type[GenericBaseInvocationOutput]) -> Type[GenericBaseInvocationOutput]:
+        # Validate output types on creation of invocation output classes
+        # TODO: ensure unique?
+        if re.compile(r"^\S+$").match(output_type) is None:
+            raise ValueError(f'"output_type" must consist of non-whitespace characters, got "{output_type}"')
+
+        # Add the output type to the pydantic model of the invocation output
+        output_type_annotation = Literal[output_type]  # type: ignore
+        output_type_field = ModelField.infer(
+            name="type",
+            value=output_type,
+            annotation=output_type_annotation,
+            class_validators=None,
+            config=cls.__config__,
+        )
+        cls.__fields__.update({"type": output_type_field})
+        cls.__annotations__.update({"type": output_type_annotation})
+
         return cls
 
     return wrapper
diff --git a/invokeai/app/invocations/collections.py b/invokeai/app/invocations/collections.py
index 1f8568beed..979f2e43b7 100644
--- a/invokeai/app/invocations/collections.py
+++ b/invokeai/app/invocations/collections.py
@@ -1,6 +1,5 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) and the InvokeAI Team
 
-from typing import Literal
 
 import numpy as np
 from pydantic import validator
@@ -8,16 +7,13 @@ from pydantic import validator
 from invokeai.app.invocations.primitives import IntegerCollectionOutput
 from invokeai.app.util.misc import SEED_MAX, get_random_seed
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, node
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 
 
-@node(title="Integer Range", tags=["collection", "integer", "range"], category="collections")
+@invocation("range", title="Integer Range", tags=["collection", "integer", "range"], category="collections")
 class RangeInvocation(BaseInvocation):
     """Creates a range of numbers from start to stop with step"""
 
-    type: Literal["range"] = "range"
-
-    # Inputs
     start: int = InputField(default=0, description="The start of the range")
     stop: int = InputField(default=10, description="The stop of the range")
     step: int = InputField(default=1, description="The step of the range")
@@ -32,13 +28,15 @@ class RangeInvocation(BaseInvocation):
         return IntegerCollectionOutput(collection=list(range(self.start, self.stop, self.step)))
 
 
-@node(title="Integer Range of Size", tags=["collection", "integer", "size", "range"], category="collections")
+@invocation(
+    "range_of_size",
+    title="Integer Range of Size",
+    tags=["collection", "integer", "size", "range"],
+    category="collections",
+)
 class RangeOfSizeInvocation(BaseInvocation):
     """Creates a range from start to start + size with step"""
 
-    type: Literal["range_of_size"] = "range_of_size"
-
-    # Inputs
     start: int = InputField(default=0, description="The start of the range")
     size: int = InputField(default=1, description="The number of values")
     step: int = InputField(default=1, description="The step of the range")
@@ -47,13 +45,15 @@ class RangeOfSizeInvocation(BaseInvocation):
         return IntegerCollectionOutput(collection=list(range(self.start, self.start + self.size, self.step)))
 
 
-@node(title="Random Range", tags=["range", "integer", "random", "collection"], category="collections")
+@invocation(
+    "random_range",
+    title="Random Range",
+    tags=["range", "integer", "random", "collection"],
+    category="collections",
+)
 class RandomRangeInvocation(BaseInvocation):
     """Creates a collection of random numbers"""
 
-    type: Literal["random_range"] = "random_range"
-
-    # Inputs
     low: int = InputField(default=0, description="The inclusive low value")
     high: int = InputField(default=np.iinfo(np.int32).max, description="The exclusive high value")
     size: int = InputField(default=1, description="The number of values to generate")
diff --git a/invokeai/app/invocations/compel.py b/invokeai/app/invocations/compel.py
index 9d0f848986..65b1a794b0 100644
--- a/invokeai/app/invocations/compel.py
+++ b/invokeai/app/invocations/compel.py
@@ -1,6 +1,6 @@
 import re
 from dataclasses import dataclass
-from typing import List, Literal, Union
+from typing import List, Union
 
 import torch
 from compel import Compel, ReturnedEmbeddingsType
@@ -26,9 +26,8 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     UIComponent,
-    category,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 from .model import ClipField
 
@@ -45,14 +44,10 @@ class ConditioningFieldData:
 #    PerpNeg = "perp_neg"
 
 
-@title("Prompt")
-@tags("prompt", "compel")
-@category("conditioning")
+@invocation("compel", title="Prompt", tags=["prompt", "compel"], category="conditioning")
 class CompelInvocation(BaseInvocation):
     """Parse prompt using compel package to conditioning."""
 
-    type: Literal["compel"] = "compel"
-
     prompt: str = InputField(
         default="",
         description=FieldDescriptions.compel_prompt,
@@ -267,14 +262,15 @@ class SDXLPromptInvocationBase:
         return c, c_pooled, ec
 
 
-@title("SDXL Prompt")
-@tags("sdxl", "compel", "prompt")
-@category("conditioning")
+@invocation(
+    "sdxl_compel_prompt",
+    title="SDXL Prompt",
+    tags=["sdxl", "compel", "prompt"],
+    category="conditioning",
+)
 class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
 
-    type: Literal["sdxl_compel_prompt"] = "sdxl_compel_prompt"
-
     prompt: str = InputField(default="", description=FieldDescriptions.compel_prompt, ui_component=UIComponent.Textarea)
     style: str = InputField(default="", description=FieldDescriptions.compel_prompt, ui_component=UIComponent.Textarea)
     original_width: int = InputField(default=1024, description="")
@@ -327,14 +323,15 @@ class SDXLCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
         )
 
 
-@title("SDXL Refiner Prompt")
-@tags("sdxl", "compel", "prompt")
-@category("conditioning")
+@invocation(
+    "sdxl_refiner_compel_prompt",
+    title="SDXL Refiner Prompt",
+    tags=["sdxl", "compel", "prompt"],
+    category="conditioning",
+)
 class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase):
     """Parse prompt using compel package to conditioning."""
 
-    type: Literal["sdxl_refiner_compel_prompt"] = "sdxl_refiner_compel_prompt"
-
     style: str = InputField(
         default="", description=FieldDescriptions.compel_prompt, ui_component=UIComponent.Textarea
     )  # TODO: ?
@@ -376,21 +373,17 @@ class SDXLRefinerCompelPromptInvocation(BaseInvocation, SDXLPromptInvocationBase
         )
 
 
+@invocation_output("clip_skip_output")
 class ClipSkipInvocationOutput(BaseInvocationOutput):
     """Clip skip node output"""
 
-    type: Literal["clip_skip_output"] = "clip_skip_output"
     clip: ClipField = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
 
 
-@title("CLIP Skip")
-@tags("clipskip", "clip", "skip")
-@category("conditioning")
+@invocation("clip_skip", title="CLIP Skip", tags=["clipskip", "clip", "skip"], category="conditioning")
 class ClipSkipInvocation(BaseInvocation):
     """Skip layers in clip text_encoder model."""
 
-    type: Literal["clip_skip"] = "clip_skip"
-
     clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection, title="CLIP")
     skipped_layers: int = InputField(default=0, description=FieldDescriptions.skipped_layers)
 
diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index cc6455a714..a666c5d6f4 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -40,10 +40,8 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     UIType,
-    category,
-    node,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 
 
@@ -89,22 +87,18 @@ class ControlField(BaseModel):
         return v
 
 
+@invocation_output("control_output")
 class ControlOutput(BaseInvocationOutput):
     """node output for ControlNet info"""
 
-    type: Literal["control_output"] = "control_output"
-
     # Outputs
     control: ControlField = OutputField(description=FieldDescriptions.control)
 
 
-@node(title="ControlNet", tags=["controlnet"], category="controlnet")
+@invocation("controlnet", title="ControlNet", tags=["controlnet"], category="controlnet")
 class ControlNetInvocation(BaseInvocation):
     """Collects ControlNet info to pass to other nodes"""
 
-    type: Literal["controlnet"] = "controlnet"
-
-    # Inputs
     image: ImageField = InputField(description="The control image")
     control_model: ControlNetModelField = InputField(
         default="lllyasviel/sd-controlnet-canny", description=FieldDescriptions.controlnet_model, input=Input.Direct
@@ -135,12 +129,10 @@ class ControlNetInvocation(BaseInvocation):
         )
 
 
+@invocation("image_processor", title="Base Image Processor", tags=["controlnet"], category="controlnet")
 class ImageProcessorInvocation(BaseInvocation):
     """Base class for invocations that preprocess images for ControlNet"""
 
-    type: Literal["image_processor"] = "image_processor"
-
-    # Inputs
     image: ImageField = InputField(description="The image to process")
 
     def run_processor(self, image):
@@ -176,15 +168,15 @@ class ImageProcessorInvocation(BaseInvocation):
         )
 
 
-@title("Canny Processor")
-@tags("controlnet", "canny")
-@category("controlnet")
+@invocation(
+    "canny_image_processor",
+    title="Canny Processor",
+    tags=["controlnet", "canny"],
+    category="controlnet",
+)
 class CannyImageProcessorInvocation(ImageProcessorInvocation):
     """Canny edge detection for ControlNet"""
 
-    type: Literal["canny_image_processor"] = "canny_image_processor"
-
-    # Input
     low_threshold: int = InputField(
         default=100, ge=0, le=255, description="The low threshold of the Canny pixel gradient (0-255)"
     )
@@ -198,15 +190,15 @@ class CannyImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("HED (softedge) Processor")
-@tags("controlnet", "hed", "softedge")
-@category("controlnet")
+@invocation(
+    "hed_image_processor",
+    title="HED (softedge) Processor",
+    tags=["controlnet", "hed", "softedge"],
+    category="controlnet",
+)
 class HedImageProcessorInvocation(ImageProcessorInvocation):
     """Applies HED edge detection to image"""
 
-    type: Literal["hed_image_processor"] = "hed_image_processor"
-
-    # Inputs
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     # safe not supported in controlnet_aux v0.0.3
@@ -226,15 +218,15 @@ class HedImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Lineart Processor")
-@tags("controlnet", "lineart")
-@category("controlnet")
+@invocation(
+    "lineart_image_processor",
+    title="Lineart Processor",
+    tags=["controlnet", "lineart"],
+    category="controlnet",
+)
 class LineartImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art processing to image"""
 
-    type: Literal["lineart_image_processor"] = "lineart_image_processor"
-
-    # Inputs
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     coarse: bool = InputField(default=False, description="Whether to use coarse mode")
@@ -247,15 +239,15 @@ class LineartImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Lineart Anime Processor")
-@tags("controlnet", "lineart", "anime")
-@category("controlnet")
+@invocation(
+    "lineart_anime_image_processor",
+    title="Lineart Anime Processor",
+    tags=["controlnet", "lineart", "anime"],
+    category="controlnet",
+)
 class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies line art anime processing to image"""
 
-    type: Literal["lineart_anime_image_processor"] = "lineart_anime_image_processor"
-
-    # Inputs
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
@@ -269,15 +261,15 @@ class LineartAnimeImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Openpose Processor")
-@tags("controlnet", "openpose", "pose")
-@category("controlnet")
+@invocation(
+    "openpose_image_processor",
+    title="Openpose Processor",
+    tags=["controlnet", "openpose", "pose"],
+    category="controlnet",
+)
 class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Openpose processing to image"""
 
-    type: Literal["openpose_image_processor"] = "openpose_image_processor"
-
-    # Inputs
     hand_and_face: bool = InputField(default=False, description="Whether to use hands and face mode")
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
@@ -293,15 +285,15 @@ class OpenposeImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Midas (Depth) Processor")
-@tags("controlnet", "midas", "depth")
-@category("controlnet")
+@invocation(
+    "midas_depth_image_processor",
+    title="Midas Depth Processor",
+    tags=["controlnet", "midas"],
+    category="controlnet",
+)
 class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Midas depth processing to image"""
 
-    type: Literal["midas_depth_image_processor"] = "midas_depth_image_processor"
-
-    # Inputs
     a_mult: float = InputField(default=2.0, ge=0, description="Midas parameter `a_mult` (a = a_mult * PI)")
     bg_th: float = InputField(default=0.1, ge=0, description="Midas parameter `bg_th`")
     # depth_and_normal not supported in controlnet_aux v0.0.3
@@ -319,15 +311,15 @@ class MidasDepthImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Normal BAE Processor")
-@tags("controlnet", "normal", "bae")
-@category("controlnet")
+@invocation(
+    "normalbae_image_processor",
+    title="Normal BAE Processor",
+    tags=["controlnet"],
+    category="controlnet",
+)
 class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
     """Applies NormalBae processing to image"""
 
-    type: Literal["normalbae_image_processor"] = "normalbae_image_processor"
-
-    # Inputs
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
 
@@ -339,15 +331,10 @@ class NormalbaeImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("MLSD Processor")
-@tags("controlnet", "mlsd")
-@category("controlnet")
+@invocation("mlsd_image_processor", title="MLSD Processor", tags=["controlnet", "mlsd"], category="controlnet")
 class MlsdImageProcessorInvocation(ImageProcessorInvocation):
     """Applies MLSD processing to image"""
 
-    type: Literal["mlsd_image_processor"] = "mlsd_image_processor"
-
-    # Inputs
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     thr_v: float = InputField(default=0.1, ge=0, description="MLSD parameter `thr_v`")
@@ -365,15 +352,10 @@ class MlsdImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("PIDI Processor")
-@tags("controlnet", "pidi")
-@category("controlnet")
+@invocation("pidi_image_processor", title="PIDI Processor", tags=["controlnet", "pidi"], category="controlnet")
 class PidiImageProcessorInvocation(ImageProcessorInvocation):
     """Applies PIDI processing to image"""
 
-    type: Literal["pidi_image_processor"] = "pidi_image_processor"
-
-    # Inputs
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     safe: bool = InputField(default=False, description=FieldDescriptions.safe_mode)
@@ -391,15 +373,15 @@ class PidiImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Content Shuffle Processor")
-@tags("controlnet", "contentshuffle")
-@category("controlnet")
+@invocation(
+    "content_shuffle_image_processor",
+    title="Content Shuffle Processor",
+    tags=["controlnet", "contentshuffle"],
+    category="controlnet",
+)
 class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
     """Applies content shuffle processing to image"""
 
-    type: Literal["content_shuffle_image_processor"] = "content_shuffle_image_processor"
-
-    # Inputs
     detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
     image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
     h: Optional[int] = InputField(default=512, ge=0, description="Content shuffle `h` parameter")
@@ -420,29 +402,30 @@ class ContentShuffleImageProcessorInvocation(ImageProcessorInvocation):
 
 
 # should work with controlnet_aux >= 0.0.4 and timm <= 0.6.13
-@title("Zoe (Depth) Processor")
-@tags("controlnet", "zoe", "depth")
-@category("controlnet")
+@invocation(
+    "zoe_depth_image_processor",
+    title="Zoe (Depth) Processor",
+    tags=["controlnet", "zoe", "depth"],
+    category="controlnet",
+)
 class ZoeDepthImageProcessorInvocation(ImageProcessorInvocation):
     """Applies Zoe depth processing to image"""
 
-    type: Literal["zoe_depth_image_processor"] = "zoe_depth_image_processor"
-
     def run_processor(self, image):
         zoe_depth_processor = ZoeDetector.from_pretrained("lllyasviel/Annotators")
         processed_image = zoe_depth_processor(image)
         return processed_image
 
 
-@title("Mediapipe Face Processor")
-@tags("controlnet", "mediapipe", "face")
-@category("controlnet")
+@invocation(
+    "mediapipe_face_processor",
+    title="Mediapipe Face Processor",
+    tags=["controlnet", "mediapipe", "face"],
+    category="controlnet",
+)
 class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
     """Applies mediapipe face processing to image"""
 
-    type: Literal["mediapipe_face_processor"] = "mediapipe_face_processor"
-
-    # Inputs
     max_faces: int = InputField(default=1, ge=1, description="Maximum number of faces to detect")
     min_confidence: float = InputField(default=0.5, ge=0, le=1, description="Minimum confidence for face detection")
 
@@ -456,15 +439,15 @@ class MediapipeFaceProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Leres (Depth) Processor")
-@tags("controlnet", "leres", "depth")
-@category("controlnet")
+@invocation(
+    "leres_image_processor",
+    title="Leres (Depth) Processor",
+    tags=["controlnet", "leres", "depth"],
+    category="controlnet",
+)
 class LeresImageProcessorInvocation(ImageProcessorInvocation):
     """Applies leres processing to image"""
 
-    type: Literal["leres_image_processor"] = "leres_image_processor"
-
-    # Inputs
     thr_a: float = InputField(default=0, description="Leres parameter `thr_a`")
     thr_b: float = InputField(default=0, description="Leres parameter `thr_b`")
     boost: bool = InputField(default=False, description="Whether to use boost mode")
@@ -484,15 +467,15 @@ class LeresImageProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Tile Resample Processor")
-@tags("controlnet", "tile")
-@category("controlnet")
+@invocation(
+    "tile_image_processor",
+    title="Tile Resample Processor",
+    tags=["controlnet", "tile"],
+    category="controlnet",
+)
 class TileResamplerProcessorInvocation(ImageProcessorInvocation):
     """Tile resampler processor"""
 
-    type: Literal["tile_image_processor"] = "tile_image_processor"
-
-    # Inputs
     # res: int = InputField(default=512, ge=0, le=1024, description="The pixel resolution for each tile")
     down_sampling_rate: float = InputField(default=1.0, ge=1.0, le=8.0, description="Down sampling rate")
 
@@ -523,14 +506,15 @@ class TileResamplerProcessorInvocation(ImageProcessorInvocation):
         return processed_image
 
 
-@title("Segment Anything Processor")
-@tags("controlnet", "segmentanything")
-@category("controlnet")
+@invocation(
+    "segment_anything_processor",
+    title="Segment Anything Processor",
+    tags=["controlnet", "segmentanything"],
+    category="controlnet",
+)
 class SegmentAnythingProcessorInvocation(ImageProcessorInvocation):
     """Applies segment anything processing to image"""
 
-    type: Literal["segment_anything_processor"] = "segment_anything_processor"
-
     def run_processor(self, image):
         # segment_anything_processor = SamDetector.from_pretrained("ybelkada/segment-anything", subfolder="checkpoints")
         segment_anything_processor = SamDetectorReproducibleColors.from_pretrained(
diff --git a/invokeai/app/invocations/cv.py b/invokeai/app/invocations/cv.py
index c03422d95e..40d8867aa1 100644
--- a/invokeai/app/invocations/cv.py
+++ b/invokeai/app/invocations/cv.py
@@ -1,6 +1,5 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Literal
 
 import cv2 as cv
 import numpy
@@ -8,18 +7,18 @@ from PIL import Image, ImageOps
 from invokeai.app.invocations.primitives import ImageField, ImageOutput
 
 from invokeai.app.models.image import ImageCategory, ResourceOrigin
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, category, tags, title
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 
 
-@title("OpenCV Inpaint")
-@tags("opencv", "inpaint")
-@category("inpaint")
+@invocation(
+    "cv_inpaint",
+    title="OpenCV Inpaint",
+    tags=["opencv", "inpaint"],
+    category="inpaint",
+)
 class CvInpaintInvocation(BaseInvocation):
     """Simple inpaint using opencv."""
 
-    type: Literal["cv_inpaint"] = "cv_inpaint"
-
-    # Inputs
     image: ImageField = InputField(description="The image to inpaint")
     mask: ImageField = InputField(description="The mask to use when inpainting")
 
diff --git a/invokeai/app/invocations/image.py b/invokeai/app/invocations/image.py
index 1168751161..5eeead7db2 100644
--- a/invokeai/app/invocations/image.py
+++ b/invokeai/app/invocations/image.py
@@ -13,18 +13,13 @@ from invokeai.backend.image_util.invisible_watermark import InvisibleWatermark
 from invokeai.backend.image_util.safety_checker import SafetyChecker
 
 from ..models.image import ImageCategory, ResourceOrigin
-from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, tags, title
+from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, invocation
 
 
-@title("Show Image")
-@tags("image")
+@invocation("show_image", title="Show Image", tags=["image"], category="image")
 class ShowImageInvocation(BaseInvocation):
-    """Displays a provided image, and passes it forward in the pipeline."""
+    """Displays a provided image using the OS image viewer, and passes it forward in the pipeline."""
 
-    # Metadata
-    type: Literal["show_image"] = "show_image"
-
-    # Inputs
     image: ImageField = InputField(description="The image to show")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
@@ -41,15 +36,10 @@ class ShowImageInvocation(BaseInvocation):
         )
 
 
-@title("Blank Image")
-@tags("image")
+@invocation("blank_image", title="Blank Image", tags=["image"], category="image")
 class BlankImageInvocation(BaseInvocation):
     """Creates a blank image and forwards it to the pipeline"""
 
-    # Metadata
-    type: Literal["blank_image"] = "blank_image"
-
-    # Inputs
     width: int = InputField(default=512, description="The width of the image")
     height: int = InputField(default=512, description="The height of the image")
     mode: Literal["RGB", "RGBA"] = InputField(default="RGB", description="The mode of the image")
@@ -75,15 +65,10 @@ class BlankImageInvocation(BaseInvocation):
         )
 
 
-@title("Crop Image")
-@tags("image", "crop")
+@invocation("img_crop", title="Crop Image", tags=["image", "crop"], category="image")
 class ImageCropInvocation(BaseInvocation):
     """Crops an image to a specified box. The box can be outside of the image."""
 
-    # Metadata
-    type: Literal["img_crop"] = "img_crop"
-
-    # Inputs
     image: ImageField = InputField(description="The image to crop")
     x: int = InputField(default=0, description="The left x coordinate of the crop rectangle")
     y: int = InputField(default=0, description="The top y coordinate of the crop rectangle")
@@ -113,15 +98,10 @@ class ImageCropInvocation(BaseInvocation):
         )
 
 
-@title("Paste Image")
-@tags("image", "paste")
+@invocation("img_paste", title="Paste Image", tags=["image", "paste"], category="image")
 class ImagePasteInvocation(BaseInvocation):
     """Pastes an image into another image."""
 
-    # Metadata
-    type: Literal["img_paste"] = "img_paste"
-
-    # Inputs
     base_image: ImageField = InputField(description="The base image")
     image: ImageField = InputField(description="The image to paste")
     mask: Optional[ImageField] = InputField(
@@ -166,15 +146,10 @@ class ImagePasteInvocation(BaseInvocation):
         )
 
 
-@title("Mask from Alpha")
-@tags("image", "mask")
+@invocation("tomask", title="Mask from Alpha", tags=["image", "mask"], category="image")
 class MaskFromAlphaInvocation(BaseInvocation):
     """Extracts the alpha channel of an image as a mask."""
 
-    # Metadata
-    type: Literal["tomask"] = "tomask"
-
-    # Inputs
     image: ImageField = InputField(description="The image to create the mask from")
     invert: bool = InputField(default=False, description="Whether or not to invert the mask")
 
@@ -202,15 +177,10 @@ class MaskFromAlphaInvocation(BaseInvocation):
         )
 
 
-@title("Multiply Images")
-@tags("image", "multiply")
+@invocation("img_mul", title="Multiply Images", tags=["image", "multiply"], category="image")
 class ImageMultiplyInvocation(BaseInvocation):
     """Multiplies two images together using `PIL.ImageChops.multiply()`."""
 
-    # Metadata
-    type: Literal["img_mul"] = "img_mul"
-
-    # Inputs
     image1: ImageField = InputField(description="The first image to multiply")
     image2: ImageField = InputField(description="The second image to multiply")
 
@@ -240,15 +210,10 @@ class ImageMultiplyInvocation(BaseInvocation):
 IMAGE_CHANNELS = Literal["A", "R", "G", "B"]
 
 
-@title("Extract Image Channel")
-@tags("image", "channel")
+@invocation("img_chan", title="Extract Image Channel", tags=["image", "channel"], category="image")
 class ImageChannelInvocation(BaseInvocation):
     """Gets a channel from an image."""
 
-    # Metadata
-    type: Literal["img_chan"] = "img_chan"
-
-    # Inputs
     image: ImageField = InputField(description="The image to get the channel from")
     channel: IMAGE_CHANNELS = InputField(default="A", description="The channel to get")
 
@@ -277,15 +242,10 @@ class ImageChannelInvocation(BaseInvocation):
 IMAGE_MODES = Literal["L", "RGB", "RGBA", "CMYK", "YCbCr", "LAB", "HSV", "I", "F"]
 
 
-@title("Convert Image Mode")
-@tags("image", "convert")
+@invocation("img_conv", title="Convert Image Mode", tags=["image", "convert"], category="image")
 class ImageConvertInvocation(BaseInvocation):
     """Converts an image to a different mode."""
 
-    # Metadata
-    type: Literal["img_conv"] = "img_conv"
-
-    # Inputs
     image: ImageField = InputField(description="The image to convert")
     mode: IMAGE_MODES = InputField(default="L", description="The mode to convert to")
 
@@ -311,15 +271,10 @@ class ImageConvertInvocation(BaseInvocation):
         )
 
 
-@title("Blur Image")
-@tags("image", "blur")
+@invocation("img_blur", title="Blur Image", tags=["image", "blur"], category="image")
 class ImageBlurInvocation(BaseInvocation):
     """Blurs an image"""
 
-    # Metadata
-    type: Literal["img_blur"] = "img_blur"
-
-    # Inputs
     image: ImageField = InputField(description="The image to blur")
     radius: float = InputField(default=8.0, ge=0, description="The blur radius")
     # Metadata
@@ -370,15 +325,10 @@ PIL_RESAMPLING_MAP = {
 }
 
 
-@title("Resize Image")
-@tags("image", "resize")
+@invocation("img_resize", title="Resize Image", tags=["image", "resize"], category="image")
 class ImageResizeInvocation(BaseInvocation):
     """Resizes an image to specific dimensions"""
 
-    # Metadata
-    type: Literal["img_resize"] = "img_resize"
-
-    # Inputs
     image: ImageField = InputField(description="The image to resize")
     width: int = InputField(default=512, ge=64, multiple_of=8, description="The width to resize to (px)")
     height: int = InputField(default=512, ge=64, multiple_of=8, description="The height to resize to (px)")
@@ -415,15 +365,10 @@ class ImageResizeInvocation(BaseInvocation):
         )
 
 
-@title("Scale Image")
-@tags("image", "scale")
+@invocation("img_scale", title="Scale Image", tags=["image", "scale"], category="image")
 class ImageScaleInvocation(BaseInvocation):
     """Scales an image by a factor"""
 
-    # Metadata
-    type: Literal["img_scale"] = "img_scale"
-
-    # Inputs
     image: ImageField = InputField(description="The image to scale")
     scale_factor: float = InputField(
         default=2.0,
@@ -461,15 +406,10 @@ class ImageScaleInvocation(BaseInvocation):
         )
 
 
-@title("Lerp Image")
-@tags("image", "lerp")
+@invocation("img_lerp", title="Lerp Image", tags=["image", "lerp"], category="image")
 class ImageLerpInvocation(BaseInvocation):
     """Linear interpolation of all pixels of an image"""
 
-    # Metadata
-    type: Literal["img_lerp"] = "img_lerp"
-
-    # Inputs
     image: ImageField = InputField(description="The image to lerp")
     min: int = InputField(default=0, ge=0, le=255, description="The minimum output value")
     max: int = InputField(default=255, ge=0, le=255, description="The maximum output value")
@@ -499,15 +439,10 @@ class ImageLerpInvocation(BaseInvocation):
         )
 
 
-@title("Inverse Lerp Image")
-@tags("image", "ilerp")
+@invocation("img_ilerp", title="Inverse Lerp Image", tags=["image", "ilerp"], category="image")
 class ImageInverseLerpInvocation(BaseInvocation):
     """Inverse linear interpolation of all pixels of an image"""
 
-    # Metadata
-    type: Literal["img_ilerp"] = "img_ilerp"
-
-    # Inputs
     image: ImageField = InputField(description="The image to lerp")
     min: int = InputField(default=0, ge=0, le=255, description="The minimum input value")
     max: int = InputField(default=255, ge=0, le=255, description="The maximum input value")
@@ -537,15 +472,10 @@ class ImageInverseLerpInvocation(BaseInvocation):
         )
 
 
-@title("Blur NSFW Image")
-@tags("image", "nsfw")
+@invocation("img_nsfw", title="Blur NSFW Image", tags=["image", "nsfw"], category="image")
 class ImageNSFWBlurInvocation(BaseInvocation):
     """Add blur to NSFW-flagged images"""
 
-    # Metadata
-    type: Literal["img_nsfw"] = "img_nsfw"
-
-    # Inputs
     image: ImageField = InputField(description="The image to check")
     metadata: Optional[CoreMetadata] = InputField(
         default=None, description=FieldDescriptions.core_metadata, ui_hidden=True
@@ -587,15 +517,10 @@ class ImageNSFWBlurInvocation(BaseInvocation):
         return caution.resize((caution.width // 2, caution.height // 2))
 
 
-@title("Add Invisible Watermark")
-@tags("image", "watermark")
+@invocation("img_watermark", title="Add Invisible Watermark", tags=["image", "watermark"], category="image")
 class ImageWatermarkInvocation(BaseInvocation):
     """Add an invisible watermark to an image"""
 
-    # Metadata
-    type: Literal["img_watermark"] = "img_watermark"
-
-    # Inputs
     image: ImageField = InputField(description="The image to check")
     text: str = InputField(default="InvokeAI", description="Watermark text")
     metadata: Optional[CoreMetadata] = InputField(
@@ -623,14 +548,10 @@ class ImageWatermarkInvocation(BaseInvocation):
         )
 
 
-@title("Mask Edge")
-@tags("image", "mask", "inpaint")
+@invocation("mask_edge", title="Mask Edge", tags=["image", "mask", "inpaint"], category="image")
 class MaskEdgeInvocation(BaseInvocation):
     """Applies an edge mask to an image"""
 
-    type: Literal["mask_edge"] = "mask_edge"
-
-    # Inputs
     image: ImageField = InputField(description="The image to apply the mask to")
     edge_size: int = InputField(description="The size of the edge")
     edge_blur: int = InputField(description="The amount of blur on the edge")
@@ -672,14 +593,10 @@ class MaskEdgeInvocation(BaseInvocation):
         )
 
 
-@title("Combine Mask")
-@tags("image", "mask", "multiply")
+@invocation("mask_combine", title="Combine Masks", tags=["image", "mask", "multiply"], category="image")
 class MaskCombineInvocation(BaseInvocation):
     """Combine two masks together by multiplying them using `PIL.ImageChops.multiply()`."""
 
-    type: Literal["mask_combine"] = "mask_combine"
-
-    # Inputs
     mask1: ImageField = InputField(description="The first mask to combine")
     mask2: ImageField = InputField(description="The second image to combine")
 
@@ -706,17 +623,13 @@ class MaskCombineInvocation(BaseInvocation):
         )
 
 
-@title("Color Correct")
-@tags("image", "color")
+@invocation("color_correct", title="Color Correct", tags=["image", "color"], category="image")
 class ColorCorrectInvocation(BaseInvocation):
     """
     Shifts the colors of a target image to match the reference image, optionally
     using a mask to only color-correct certain regions of the target image.
     """
 
-    type: Literal["color_correct"] = "color_correct"
-
-    # Inputs
     image: ImageField = InputField(description="The image to color-correct")
     reference: ImageField = InputField(description="Reference image for color-correction")
     mask: Optional[ImageField] = InputField(default=None, description="Mask to use when applying color-correction")
@@ -815,14 +728,10 @@ class ColorCorrectInvocation(BaseInvocation):
         )
 
 
-@title("Image Hue Adjustment")
-@tags("image", "hue", "hsl")
+@invocation("img_hue_adjust", title="Adjust Image Hue", tags=["image", "hue"], category="image")
 class ImageHueAdjustmentInvocation(BaseInvocation):
     """Adjusts the Hue of an image."""
 
-    type: Literal["img_hue_adjust"] = "img_hue_adjust"
-
-    # Inputs
     image: ImageField = InputField(description="The image to adjust")
     hue: int = InputField(default=0, description="The degrees by which to rotate the hue, 0-360")
 
@@ -860,14 +769,15 @@ class ImageHueAdjustmentInvocation(BaseInvocation):
         )
 
 
-@title("Image Luminosity Adjustment")
-@tags("image", "luminosity", "hsl")
+@invocation(
+    "img_luminosity_adjust",
+    title="Adjust Image Luminosity",
+    tags=["image", "luminosity", "hsl"],
+    category="image",
+)
 class ImageLuminosityAdjustmentInvocation(BaseInvocation):
     """Adjusts the Luminosity (Value) of an image."""
 
-    type: Literal["img_luminosity_adjust"] = "img_luminosity_adjust"
-
-    # Inputs
     image: ImageField = InputField(description="The image to adjust")
     luminosity: float = InputField(
         default=1.0, ge=0, le=1, description="The factor by which to adjust the luminosity (value)"
@@ -911,14 +821,15 @@ class ImageLuminosityAdjustmentInvocation(BaseInvocation):
         )
 
 
-@title("Image Saturation Adjustment")
-@tags("image", "saturation", "hsl")
+@invocation(
+    "img_saturation_adjust",
+    title="Adjust Image Saturation",
+    tags=["image", "saturation", "hsl"],
+    category="image",
+)
 class ImageSaturationAdjustmentInvocation(BaseInvocation):
     """Adjusts the Saturation of an image."""
 
-    type: Literal["img_saturation_adjust"] = "img_saturation_adjust"
-
-    # Inputs
     image: ImageField = InputField(description="The image to adjust")
     saturation: float = InputField(default=1.0, ge=0, le=1, description="The factor by which to adjust the saturation")
 
diff --git a/invokeai/app/invocations/infill.py b/invokeai/app/invocations/infill.py
index ce6e5457e3..438c56e312 100644
--- a/invokeai/app/invocations/infill.py
+++ b/invokeai/app/invocations/infill.py
@@ -12,7 +12,7 @@ from invokeai.backend.image_util.lama import LaMA
 from invokeai.backend.image_util.patchmatch import PatchMatch
 
 from ..models.image import ImageCategory, ResourceOrigin
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, tags, title
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 
 
 def infill_methods() -> list[str]:
@@ -116,14 +116,10 @@ def tile_fill_missing(im: Image.Image, tile_size: int = 16, seed: Optional[int]
     return si
 
 
-@title("Solid Color Infill")
-@tags("image", "inpaint")
+@invocation("infill_rgba", title="Solid Color Infill", tags=["image", "inpaint"], category="inpaint")
 class InfillColorInvocation(BaseInvocation):
     """Infills transparent areas of an image with a solid color"""
 
-    type: Literal["infill_rgba"] = "infill_rgba"
-
-    # Inputs
     image: ImageField = InputField(description="The image to infill")
     color: ColorField = InputField(
         default=ColorField(r=127, g=127, b=127, a=255),
@@ -155,14 +151,10 @@ class InfillColorInvocation(BaseInvocation):
         )
 
 
-@title("Tile Infill")
-@tags("image", "inpaint")
+@invocation("infill_tile", title="Tile Infill", tags=["image", "inpaint"], category="inpaint")
 class InfillTileInvocation(BaseInvocation):
     """Infills transparent areas of an image with tiles of the image"""
 
-    type: Literal["infill_tile"] = "infill_tile"
-
-    # Input
     image: ImageField = InputField(description="The image to infill")
     tile_size: int = InputField(default=32, ge=1, description="The tile size (px)")
     seed: int = InputField(
@@ -195,14 +187,10 @@ class InfillTileInvocation(BaseInvocation):
         )
 
 
-@title("PatchMatch Infill")
-@tags("image", "inpaint")
+@invocation("infill_patchmatch", title="PatchMatch Infill", tags=["image", "inpaint"], category="inpaint")
 class InfillPatchMatchInvocation(BaseInvocation):
     """Infills transparent areas of an image using the PatchMatch algorithm"""
 
-    type: Literal["infill_patchmatch"] = "infill_patchmatch"
-
-    # Inputs
     image: ImageField = InputField(description="The image to infill")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
@@ -230,14 +218,10 @@ class InfillPatchMatchInvocation(BaseInvocation):
         )
 
 
-@title("LaMa Infill")
-@tags("image", "inpaint")
+@invocation("infill_lama", title="LaMa Infill", tags=["image", "inpaint"], category="inpaint")
 class LaMaInfillInvocation(BaseInvocation):
     """Infills transparent areas of an image using the LaMa model"""
 
-    type: Literal["infill_lama"] = "infill_lama"
-
-    # Inputs
     image: ImageField = InputField(description="The image to infill")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
diff --git a/invokeai/app/invocations/latent.py b/invokeai/app/invocations/latent.py
index 3052904ce0..31dde74a09 100644
--- a/invokeai/app/invocations/latent.py
+++ b/invokeai/app/invocations/latent.py
@@ -47,7 +47,15 @@ from ...backend.stable_diffusion.diffusion.shared_invokeai_diffusion import Post
 from ...backend.stable_diffusion.schedulers import SCHEDULER_MAP
 from ...backend.util.devices import choose_precision, choose_torch_device
 from ..models.image import ImageCategory, ResourceOrigin
-from .baseinvocation import BaseInvocation, FieldDescriptions, Input, InputField, InvocationContext, UIType, tags, title
+from .baseinvocation import (
+    BaseInvocation,
+    FieldDescriptions,
+    Input,
+    InputField,
+    InvocationContext,
+    UIType,
+    invocation,
+)
 from .compel import ConditioningField
 from .controlnet_image_processors import ControlField
 from .model import ModelInfo, UNetField, VaeField
@@ -58,15 +66,10 @@ DEFAULT_PRECISION = choose_precision(choose_torch_device())
 SAMPLER_NAME_VALUES = Literal[tuple(list(SCHEDULER_MAP.keys()))]
 
 
-@title("Create Denoise Mask")
-@tags("mask", "denoise")
+@invocation("create_denoise_mask", title="Create Denoise Mask", tags=["mask", "denoise"], category="latents")
 class CreateDenoiseMaskInvocation(BaseInvocation):
     """Creates mask for denoising model run."""
 
-    # Metadata
-    type: Literal["create_denoise_mask"] = "create_denoise_mask"
-
-    # Inputs
     vae: VaeField = InputField(description=FieldDescriptions.vae, input=Input.Connection, ui_order=0)
     image: Optional[ImageField] = InputField(default=None, description="Image which will be masked", ui_order=1)
     mask: ImageField = InputField(description="The mask to use when pasting", ui_order=2)
@@ -158,14 +161,15 @@ def get_scheduler(
     return scheduler
 
 
-@title("Denoise Latents")
-@tags("latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l")
+@invocation(
+    "denoise_latents",
+    title="Denoise Latents",
+    tags=["latents", "denoise", "txt2img", "t2i", "t2l", "img2img", "i2i", "l2l"],
+    category="latents",
+)
 class DenoiseLatentsInvocation(BaseInvocation):
     """Denoises noisy latents to decodable images"""
 
-    type: Literal["denoise_latents"] = "denoise_latents"
-
-    # Inputs
     positive_conditioning: ConditioningField = InputField(
         description=FieldDescriptions.positive_cond, input=Input.Connection, ui_order=0
     )
@@ -512,14 +516,10 @@ class DenoiseLatentsInvocation(BaseInvocation):
         return build_latents_output(latents_name=name, latents=result_latents, seed=seed)
 
 
-@title("Latents to Image")
-@tags("latents", "image", "vae", "l2i")
+@invocation("l2i", title="Latents to Image", tags=["latents", "image", "vae", "l2i"], category="latents")
 class LatentsToImageInvocation(BaseInvocation):
     """Generates an image from latents."""
 
-    type: Literal["l2i"] = "l2i"
-
-    # Inputs
     latents: LatentsField = InputField(
         description=FieldDescriptions.latents,
         input=Input.Connection,
@@ -613,14 +613,10 @@ class LatentsToImageInvocation(BaseInvocation):
 LATENTS_INTERPOLATION_MODE = Literal["nearest", "linear", "bilinear", "bicubic", "trilinear", "area", "nearest-exact"]
 
 
-@title("Resize Latents")
-@tags("latents", "resize")
+@invocation("lresize", title="Resize Latents", tags=["latents", "resize"], category="latents")
 class ResizeLatentsInvocation(BaseInvocation):
     """Resizes latents to explicit width/height (in pixels). Provided dimensions are floor-divided by 8."""
 
-    type: Literal["lresize"] = "lresize"
-
-    # Inputs
     latents: LatentsField = InputField(
         description=FieldDescriptions.latents,
         input=Input.Connection,
@@ -661,14 +657,10 @@ class ResizeLatentsInvocation(BaseInvocation):
         return build_latents_output(latents_name=name, latents=resized_latents, seed=self.latents.seed)
 
 
-@title("Scale Latents")
-@tags("latents", "resize")
+@invocation("lscale", title="Scale Latents", tags=["latents", "resize"], category="latents")
 class ScaleLatentsInvocation(BaseInvocation):
     """Scales latents by a given factor."""
 
-    type: Literal["lscale"] = "lscale"
-
-    # Inputs
     latents: LatentsField = InputField(
         description=FieldDescriptions.latents,
         input=Input.Connection,
@@ -701,14 +693,10 @@ class ScaleLatentsInvocation(BaseInvocation):
         return build_latents_output(latents_name=name, latents=resized_latents, seed=self.latents.seed)
 
 
-@title("Image to Latents")
-@tags("latents", "image", "vae", "i2l")
+@invocation("i2l", title="Image to Latents", tags=["latents", "image", "vae", "i2l"], category="latents")
 class ImageToLatentsInvocation(BaseInvocation):
     """Encodes an image into latents."""
 
-    type: Literal["i2l"] = "i2l"
-
-    # Inputs
     image: ImageField = InputField(
         description="The image to encode",
     )
@@ -785,14 +773,10 @@ class ImageToLatentsInvocation(BaseInvocation):
         return build_latents_output(latents_name=name, latents=latents, seed=None)
 
 
-@title("Blend Latents")
-@tags("latents", "blend")
+@invocation("lblend", title="Blend Latents", tags=["latents", "blend"], category="latents")
 class BlendLatentsInvocation(BaseInvocation):
     """Blend two latents using a given alpha. Latents must have same size."""
 
-    type: Literal["lblend"] = "lblend"
-
-    # Inputs
     latents_a: LatentsField = InputField(
         description=FieldDescriptions.latents,
         input=Input.Connection,
diff --git a/invokeai/app/invocations/math.py b/invokeai/app/invocations/math.py
index 80cdc09221..2a8dc12b28 100644
--- a/invokeai/app/invocations/math.py
+++ b/invokeai/app/invocations/math.py
@@ -1,22 +1,16 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Literal
-
 import numpy as np
 
 from invokeai.app.invocations.primitives import IntegerOutput
 
-from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, tags, title
+from .baseinvocation import BaseInvocation, FieldDescriptions, InputField, InvocationContext, invocation
 
 
-@title("Add Integers")
-@tags("math")
+@invocation("add", title="Add Integers", tags=["math", "add"], category="math")
 class AddInvocation(BaseInvocation):
     """Adds two numbers"""
 
-    type: Literal["add"] = "add"
-
-    # Inputs
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
@@ -24,14 +18,10 @@ class AddInvocation(BaseInvocation):
         return IntegerOutput(value=self.a + self.b)
 
 
-@title("Subtract Integers")
-@tags("math")
+@invocation("sub", title="Subtract Integers", tags=["math", "subtract"], category="math")
 class SubtractInvocation(BaseInvocation):
     """Subtracts two numbers"""
 
-    type: Literal["sub"] = "sub"
-
-    # Inputs
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
@@ -39,14 +29,10 @@ class SubtractInvocation(BaseInvocation):
         return IntegerOutput(value=self.a - self.b)
 
 
-@title("Multiply Integers")
-@tags("math")
+@invocation("mul", title="Multiply Integers", tags=["math", "multiply"], category="math")
 class MultiplyInvocation(BaseInvocation):
     """Multiplies two numbers"""
 
-    type: Literal["mul"] = "mul"
-
-    # Inputs
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
@@ -54,14 +40,10 @@ class MultiplyInvocation(BaseInvocation):
         return IntegerOutput(value=self.a * self.b)
 
 
-@title("Divide Integers")
-@tags("math")
+@invocation("div", title="Divide Integers", tags=["math", "divide"], category="math")
 class DivideInvocation(BaseInvocation):
     """Divides two numbers"""
 
-    type: Literal["div"] = "div"
-
-    # Inputs
     a: int = InputField(default=0, description=FieldDescriptions.num_1)
     b: int = InputField(default=0, description=FieldDescriptions.num_2)
 
@@ -69,14 +51,10 @@ class DivideInvocation(BaseInvocation):
         return IntegerOutput(value=int(self.a / self.b))
 
 
-@title("Random Integer")
-@tags("math")
+@invocation("rand_int", title="Random Integer", tags=["math", "random"], category="math")
 class RandomIntInvocation(BaseInvocation):
     """Outputs a single random integer."""
 
-    type: Literal["rand_int"] = "rand_int"
-
-    # Inputs
     low: int = InputField(default=0, description="The inclusive low value")
     high: int = InputField(default=np.iinfo(np.int32).max, description="The exclusive high value")
 
diff --git a/invokeai/app/invocations/metadata.py b/invokeai/app/invocations/metadata.py
index a2e34109df..4a968ff3ac 100644
--- a/invokeai/app/invocations/metadata.py
+++ b/invokeai/app/invocations/metadata.py
@@ -1,4 +1,4 @@
-from typing import Literal, Optional
+from typing import Optional
 
 from pydantic import Field
 
@@ -8,8 +8,8 @@ from invokeai.app.invocations.baseinvocation import (
     InputField,
     InvocationContext,
     OutputField,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 from invokeai.app.invocations.controlnet_image_processors import ControlField
 from invokeai.app.invocations.model import LoRAModelField, MainModelField, VAEModelField
@@ -91,21 +91,17 @@ class ImageMetadata(BaseModelExcludeNull):
     graph: Optional[dict] = Field(default=None, description="The graph that created the image")
 
 
+@invocation_output("metadata_accumulator_output")
 class MetadataAccumulatorOutput(BaseInvocationOutput):
     """The output of the MetadataAccumulator node"""
 
-    type: Literal["metadata_accumulator_output"] = "metadata_accumulator_output"
-
     metadata: CoreMetadata = OutputField(description="The core metadata for the image")
 
 
-@title("Metadata Accumulator")
-@tags("metadata")
+@invocation("metadata_accumulator", title="Metadata Accumulator", tags=["metadata"], category="metadata")
 class MetadataAccumulatorInvocation(BaseInvocation):
     """Outputs a Core Metadata Object"""
 
-    type: Literal["metadata_accumulator"] = "metadata_accumulator"
-
     generation_mode: str = InputField(
         description="The generation mode that output this image",
     )
diff --git a/invokeai/app/invocations/model.py b/invokeai/app/invocations/model.py
index 31d04cfd37..c3dde5e725 100644
--- a/invokeai/app/invocations/model.py
+++ b/invokeai/app/invocations/model.py
@@ -1,5 +1,5 @@
 import copy
-from typing import List, Literal, Optional
+from typing import List, Optional
 
 from pydantic import BaseModel, Field
 
@@ -13,8 +13,8 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     UIType,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 
 
@@ -49,11 +49,10 @@ class VaeField(BaseModel):
     seamless_axes: List[str] = Field(default_factory=list, description='Axes("x" and "y") to which apply seamless')
 
 
+@invocation_output("model_loader_output")
 class ModelLoaderOutput(BaseInvocationOutput):
     """Model loader output"""
 
-    type: Literal["model_loader_output"] = "model_loader_output"
-
     unet: UNetField = OutputField(description=FieldDescriptions.unet, title="UNet")
     clip: ClipField = OutputField(description=FieldDescriptions.clip, title="CLIP")
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
@@ -74,14 +73,10 @@ class LoRAModelField(BaseModel):
     base_model: BaseModelType = Field(description="Base model")
 
 
-@title("Main Model")
-@tags("model")
+@invocation("main_model_loader", title="Main Model", tags=["model"], category="model")
 class MainModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
 
-    type: Literal["main_model_loader"] = "main_model_loader"
-
-    # Inputs
     model: MainModelField = InputField(description=FieldDescriptions.main_model, input=Input.Direct)
     # TODO: precision?
 
@@ -170,25 +165,18 @@ class MainModelLoaderInvocation(BaseInvocation):
         )
 
 
+@invocation_output("lora_loader_output")
 class LoraLoaderOutput(BaseInvocationOutput):
     """Model loader output"""
 
-    # fmt: off
-    type: Literal["lora_loader_output"] = "lora_loader_output"
-
     unet: Optional[UNetField] = OutputField(default=None, description=FieldDescriptions.unet, title="UNet")
     clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
-    # fmt: on
 
 
-@title("LoRA")
-@tags("lora", "model")
+@invocation("lora_loader", title="LoRA", tags=["model"], category="model")
 class LoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
-    type: Literal["lora_loader"] = "lora_loader"
-
-    # Inputs
     lora: LoRAModelField = InputField(description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA")
     weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = InputField(
@@ -247,25 +235,19 @@ class LoraLoaderInvocation(BaseInvocation):
         return output
 
 
+@invocation_output("sdxl_lora_loader_output")
 class SDXLLoraLoaderOutput(BaseInvocationOutput):
     """SDXL LoRA Loader Output"""
 
-    # fmt: off
-    type: Literal["sdxl_lora_loader_output"] = "sdxl_lora_loader_output"
-
     unet: Optional[UNetField] = OutputField(default=None, description=FieldDescriptions.unet, title="UNet")
     clip: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP 1")
     clip2: Optional[ClipField] = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP 2")
-    # fmt: on
 
 
-@title("SDXL LoRA")
-@tags("sdxl", "lora", "model")
+@invocation("sdxl_lora_loader", title="SDXL LoRA", tags=["lora", "model"], category="model")
 class SDXLLoraLoaderInvocation(BaseInvocation):
     """Apply selected lora to unet and text_encoder."""
 
-    type: Literal["sdxl_lora_loader"] = "sdxl_lora_loader"
-
     lora: LoRAModelField = InputField(description=FieldDescriptions.lora_model, input=Input.Direct, title="LoRA")
     weight: float = Field(default=0.75, description=FieldDescriptions.lora_weight)
     unet: Optional[UNetField] = Field(
@@ -349,23 +331,17 @@ class VAEModelField(BaseModel):
     base_model: BaseModelType = Field(description="Base model")
 
 
+@invocation_output("vae_loader_output")
 class VaeLoaderOutput(BaseInvocationOutput):
-    """Model loader output"""
+    """VAE output"""
 
-    type: Literal["vae_loader_output"] = "vae_loader_output"
-
-    # Outputs
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@title("VAE")
-@tags("vae", "model")
+@invocation("vae_loader", title="VAE", tags=["vae", "model"], category="model")
 class VaeLoaderInvocation(BaseInvocation):
     """Loads a VAE model, outputting a VaeLoaderOutput"""
 
-    type: Literal["vae_loader"] = "vae_loader"
-
-    # Inputs
     vae_model: VAEModelField = InputField(
         description=FieldDescriptions.vae_model, input=Input.Direct, ui_type=UIType.VaeModel, title="VAE"
     )
@@ -392,24 +368,18 @@ class VaeLoaderInvocation(BaseInvocation):
         )
 
 
+@invocation_output("seamless_output")
 class SeamlessModeOutput(BaseInvocationOutput):
     """Modified Seamless Model output"""
 
-    type: Literal["seamless_output"] = "seamless_output"
-
-    # Outputs
     unet: Optional[UNetField] = OutputField(description=FieldDescriptions.unet, title="UNet")
     vae: Optional[VaeField] = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@title("Seamless")
-@tags("seamless", "model")
+@invocation("seamless", title="Seamless", tags=["seamless", "model"], category="model")
 class SeamlessModeInvocation(BaseInvocation):
     """Applies the seamless transformation to the Model UNet and VAE."""
 
-    type: Literal["seamless"] = "seamless"
-
-    # Inputs
     unet: Optional[UNetField] = InputField(
         default=None, description=FieldDescriptions.unet, input=Input.Connection, title="UNet"
     )
diff --git a/invokeai/app/invocations/noise.py b/invokeai/app/invocations/noise.py
index d1dd320ee8..1f1d9fe3ce 100644
--- a/invokeai/app/invocations/noise.py
+++ b/invokeai/app/invocations/noise.py
@@ -1,6 +1,5 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654) & the InvokeAI Team
 
-from typing import Literal
 
 import torch
 from pydantic import validator
@@ -16,8 +15,8 @@ from .baseinvocation import (
     InputField,
     InvocationContext,
     OutputField,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 
 """
@@ -62,12 +61,10 @@ Nodes
 """
 
 
+@invocation_output("noise_output")
 class NoiseOutput(BaseInvocationOutput):
     """Invocation noise output"""
 
-    type: Literal["noise_output"] = "noise_output"
-
-    # Inputs
     noise: LatentsField = OutputField(default=None, description=FieldDescriptions.noise)
     width: int = OutputField(description=FieldDescriptions.width)
     height: int = OutputField(description=FieldDescriptions.height)
@@ -81,14 +78,10 @@ def build_noise_output(latents_name: str, latents: torch.Tensor, seed: int):
     )
 
 
-@title("Noise")
-@tags("latents", "noise")
+@invocation("noise", title="Noise", tags=["latents", "noise"], category="latents")
 class NoiseInvocation(BaseInvocation):
     """Generates latent noise."""
 
-    type: Literal["noise"] = "noise"
-
-    # Inputs
     seed: int = InputField(
         ge=0,
         le=SEED_MAX,
diff --git a/invokeai/app/invocations/onnx.py b/invokeai/app/invocations/onnx.py
index 504a36a424..b61ea2da99 100644
--- a/invokeai/app/invocations/onnx.py
+++ b/invokeai/app/invocations/onnx.py
@@ -31,8 +31,8 @@ from .baseinvocation import (
     OutputField,
     UIComponent,
     UIType,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 from .controlnet_image_processors import ControlField
 from .latent import SAMPLER_NAME_VALUES, LatentsField, LatentsOutput, build_latents_output, get_scheduler
@@ -56,11 +56,8 @@ ORT_TO_NP_TYPE = {
 PRECISION_VALUES = Literal[tuple(list(ORT_TO_NP_TYPE.keys()))]
 
 
-@title("ONNX Prompt (Raw)")
-@tags("onnx", "prompt")
+@invocation("prompt_onnx", title="ONNX Prompt (Raw)", tags=["prompt", "onnx"], category="conditioning")
 class ONNXPromptInvocation(BaseInvocation):
-    type: Literal["prompt_onnx"] = "prompt_onnx"
-
     prompt: str = InputField(default="", description=FieldDescriptions.raw_prompt, ui_component=UIComponent.Textarea)
     clip: ClipField = InputField(description=FieldDescriptions.clip, input=Input.Connection)
 
@@ -141,14 +138,15 @@ class ONNXPromptInvocation(BaseInvocation):
 
 
 # Text to image
-@title("ONNX Text to Latents")
-@tags("latents", "inference", "txt2img", "onnx")
+@invocation(
+    "t2l_onnx",
+    title="ONNX Text to Latents",
+    tags=["latents", "inference", "txt2img", "onnx"],
+    category="latents",
+)
 class ONNXTextToLatentsInvocation(BaseInvocation):
     """Generates latents from conditionings."""
 
-    type: Literal["t2l_onnx"] = "t2l_onnx"
-
-    # Inputs
     positive_conditioning: ConditioningField = InputField(
         description=FieldDescriptions.positive_cond,
         input=Input.Connection,
@@ -316,14 +314,15 @@ class ONNXTextToLatentsInvocation(BaseInvocation):
 
 
 # Latent to image
-@title("ONNX Latents to Image")
-@tags("latents", "image", "vae", "onnx")
+@invocation(
+    "l2i_onnx",
+    title="ONNX Latents to Image",
+    tags=["latents", "image", "vae", "onnx"],
+    category="image",
+)
 class ONNXLatentsToImageInvocation(BaseInvocation):
     """Generates an image from latents."""
 
-    type: Literal["l2i_onnx"] = "l2i_onnx"
-
-    # Inputs
     latents: LatentsField = InputField(
         description=FieldDescriptions.denoised_latents,
         input=Input.Connection,
@@ -386,17 +385,14 @@ class ONNXLatentsToImageInvocation(BaseInvocation):
         )
 
 
+@invocation_output("model_loader_output_onnx")
 class ONNXModelLoaderOutput(BaseInvocationOutput):
     """Model loader output"""
 
-    # fmt: off
-    type: Literal["model_loader_output_onnx"] = "model_loader_output_onnx"
-
     unet: UNetField = OutputField(default=None, description=FieldDescriptions.unet, title="UNet")
     clip: ClipField = OutputField(default=None, description=FieldDescriptions.clip, title="CLIP")
     vae_decoder: VaeField = OutputField(default=None, description=FieldDescriptions.vae, title="VAE Decoder")
     vae_encoder: VaeField = OutputField(default=None, description=FieldDescriptions.vae, title="VAE Encoder")
-    # fmt: on
 
 
 class OnnxModelField(BaseModel):
@@ -407,14 +403,10 @@ class OnnxModelField(BaseModel):
     model_type: ModelType = Field(description="Model Type")
 
 
-@title("ONNX Main Model")
-@tags("onnx", "model")
+@invocation("onnx_model_loader", title="ONNX Main Model", tags=["onnx", "model"], category="model")
 class OnnxModelLoaderInvocation(BaseInvocation):
     """Loads a main model, outputting its submodels."""
 
-    type: Literal["onnx_model_loader"] = "onnx_model_loader"
-
-    # Inputs
     model: OnnxModelField = InputField(
         description=FieldDescriptions.onnx_main_model, input=Input.Direct, ui_type=UIType.ONNXModel
     )
diff --git a/invokeai/app/invocations/param_easing.py b/invokeai/app/invocations/param_easing.py
index 70baa85817..1b3c0dc09e 100644
--- a/invokeai/app/invocations/param_easing.py
+++ b/invokeai/app/invocations/param_easing.py
@@ -42,17 +42,13 @@ from matplotlib.ticker import MaxNLocator
 
 from invokeai.app.invocations.primitives import FloatCollectionOutput
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, tags, title
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 
 
-@title("Float Range")
-@tags("math", "range")
+@invocation("float_range", title="Float Range", tags=["math", "range"], category="math")
 class FloatLinearRangeInvocation(BaseInvocation):
     """Creates a range"""
 
-    type: Literal["float_range"] = "float_range"
-
-    # Inputs
     start: float = InputField(default=5, description="The first value of the range")
     stop: float = InputField(default=10, description="The last value of the range")
     steps: int = InputField(default=30, description="number of values to interpolate over (including start and stop)")
@@ -100,14 +96,10 @@ EASING_FUNCTION_KEYS = Literal[tuple(list(EASING_FUNCTIONS_MAP.keys()))]
 
 
 # actually I think for now could just use CollectionOutput (which is list[Any]
-@title("Step Param Easing")
-@tags("step", "easing")
+@invocation("step_param_easing", title="Step Param Easing", tags=["step", "easing"], category="step")
 class StepParamEasingInvocation(BaseInvocation):
     """Experimental per-step parameter easing for denoising steps"""
 
-    type: Literal["step_param_easing"] = "step_param_easing"
-
-    # Inputs
     easing: EASING_FUNCTION_KEYS = InputField(default="Linear", description="The easing function to use")
     num_steps: int = InputField(default=20, description="number of denoising steps")
     start_value: float = InputField(default=0.0, description="easing starting value")
diff --git a/invokeai/app/invocations/primitives.py b/invokeai/app/invocations/primitives.py
index 49cd49d189..8089b9d5e2 100644
--- a/invokeai/app/invocations/primitives.py
+++ b/invokeai/app/invocations/primitives.py
@@ -1,6 +1,6 @@
 # Copyright (c) 2023 Kyle Schouviller (https://github.com/kyle0654)
 
-from typing import Literal, Optional, Tuple
+from typing import Optional, Tuple
 
 import torch
 from pydantic import BaseModel, Field
@@ -15,8 +15,8 @@ from .baseinvocation import (
     OutputField,
     UIComponent,
     UIType,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 
 """
@@ -29,44 +29,39 @@ Primitives: Boolean, Integer, Float, String, Image, Latents, Conditioning, Color
 # region Boolean
 
 
+@invocation_output("boolean_output")
 class BooleanOutput(BaseInvocationOutput):
     """Base class for nodes that output a single boolean"""
 
-    type: Literal["boolean_output"] = "boolean_output"
     value: bool = OutputField(description="The output boolean")
 
 
+@invocation_output("boolean_collection_output")
 class BooleanCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of booleans"""
 
-    type: Literal["boolean_collection_output"] = "boolean_collection_output"
-
-    # Outputs
     collection: list[bool] = OutputField(description="The output boolean collection", ui_type=UIType.BooleanCollection)
 
 
-@title("Boolean Primitive")
-@tags("primitives", "boolean")
+@invocation("boolean", title="Boolean Primitive", tags=["primitives", "boolean"], category="primitives")
 class BooleanInvocation(BaseInvocation):
     """A boolean primitive value"""
 
-    type: Literal["boolean"] = "boolean"
-
-    # Inputs
     value: bool = InputField(default=False, description="The boolean value")
 
     def invoke(self, context: InvocationContext) -> BooleanOutput:
         return BooleanOutput(value=self.value)
 
 
-@title("Boolean Primitive Collection")
-@tags("primitives", "boolean", "collection")
+@invocation(
+    "boolean_collection",
+    title="Boolean Collection Primitive",
+    tags=["primitives", "boolean", "collection"],
+    category="primitives",
+)
 class BooleanCollectionInvocation(BaseInvocation):
     """A collection of boolean primitive values"""
 
-    type: Literal["boolean_collection"] = "boolean_collection"
-
-    # Inputs
     collection: list[bool] = InputField(
         default_factory=list, description="The collection of boolean values", ui_type=UIType.BooleanCollection
     )
@@ -80,44 +75,39 @@ class BooleanCollectionInvocation(BaseInvocation):
 # region Integer
 
 
+@invocation_output("integer_output")
 class IntegerOutput(BaseInvocationOutput):
     """Base class for nodes that output a single integer"""
 
-    type: Literal["integer_output"] = "integer_output"
     value: int = OutputField(description="The output integer")
 
 
+@invocation_output("integer_collection_output")
 class IntegerCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of integers"""
 
-    type: Literal["integer_collection_output"] = "integer_collection_output"
-
-    # Outputs
     collection: list[int] = OutputField(description="The int collection", ui_type=UIType.IntegerCollection)
 
 
-@title("Integer Primitive")
-@tags("primitives", "integer")
+@invocation("integer", title="Integer Primitive", tags=["primitives", "integer"], category="primitives")
 class IntegerInvocation(BaseInvocation):
     """An integer primitive value"""
 
-    type: Literal["integer"] = "integer"
-
-    # Inputs
     value: int = InputField(default=0, description="The integer value")
 
     def invoke(self, context: InvocationContext) -> IntegerOutput:
         return IntegerOutput(value=self.value)
 
 
-@title("Integer Primitive Collection")
-@tags("primitives", "integer", "collection")
+@invocation(
+    "integer_collection",
+    title="Integer Collection Primitive",
+    tags=["primitives", "integer", "collection"],
+    category="primitives",
+)
 class IntegerCollectionInvocation(BaseInvocation):
     """A collection of integer primitive values"""
 
-    type: Literal["integer_collection"] = "integer_collection"
-
-    # Inputs
     collection: list[int] = InputField(
         default=0, description="The collection of integer values", ui_type=UIType.IntegerCollection
     )
@@ -131,44 +121,39 @@ class IntegerCollectionInvocation(BaseInvocation):
 # region Float
 
 
+@invocation_output("float_output")
 class FloatOutput(BaseInvocationOutput):
     """Base class for nodes that output a single float"""
 
-    type: Literal["float_output"] = "float_output"
     value: float = OutputField(description="The output float")
 
 
+@invocation_output("float_collection_output")
 class FloatCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of floats"""
 
-    type: Literal["float_collection_output"] = "float_collection_output"
-
-    # Outputs
     collection: list[float] = OutputField(description="The float collection", ui_type=UIType.FloatCollection)
 
 
-@title("Float Primitive")
-@tags("primitives", "float")
+@invocation("float", title="Float Primitive", tags=["primitives", "float"], category="primitives")
 class FloatInvocation(BaseInvocation):
     """A float primitive value"""
 
-    type: Literal["float"] = "float"
-
-    # Inputs
     value: float = InputField(default=0.0, description="The float value")
 
     def invoke(self, context: InvocationContext) -> FloatOutput:
         return FloatOutput(value=self.value)
 
 
-@title("Float Primitive Collection")
-@tags("primitives", "float", "collection")
+@invocation(
+    "float_collection",
+    title="Float Collection Primitive",
+    tags=["primitives", "float", "collection"],
+    category="primitives",
+)
 class FloatCollectionInvocation(BaseInvocation):
     """A collection of float primitive values"""
 
-    type: Literal["float_collection"] = "float_collection"
-
-    # Inputs
     collection: list[float] = InputField(
         default_factory=list, description="The collection of float values", ui_type=UIType.FloatCollection
     )
@@ -182,44 +167,39 @@ class FloatCollectionInvocation(BaseInvocation):
 # region String
 
 
+@invocation_output("string_output")
 class StringOutput(BaseInvocationOutput):
     """Base class for nodes that output a single string"""
 
-    type: Literal["string_output"] = "string_output"
     value: str = OutputField(description="The output string")
 
 
+@invocation_output("string_collection_output")
 class StringCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of strings"""
 
-    type: Literal["string_collection_output"] = "string_collection_output"
-
-    # Outputs
     collection: list[str] = OutputField(description="The output strings", ui_type=UIType.StringCollection)
 
 
-@title("String Primitive")
-@tags("primitives", "string")
+@invocation("string", title="String Primitive", tags=["primitives", "string"], category="primitives")
 class StringInvocation(BaseInvocation):
     """A string primitive value"""
 
-    type: Literal["string"] = "string"
-
-    # Inputs
     value: str = InputField(default="", description="The string value", ui_component=UIComponent.Textarea)
 
     def invoke(self, context: InvocationContext) -> StringOutput:
         return StringOutput(value=self.value)
 
 
-@title("String Primitive Collection")
-@tags("primitives", "string", "collection")
+@invocation(
+    "string_collection",
+    title="String Collection Primitive",
+    tags=["primitives", "string", "collection"],
+    category="primitives",
+)
 class StringCollectionInvocation(BaseInvocation):
     """A collection of string primitive values"""
 
-    type: Literal["string_collection"] = "string_collection"
-
-    # Inputs
     collection: list[str] = InputField(
         default_factory=list, description="The collection of string values", ui_type=UIType.StringCollection
     )
@@ -239,33 +219,26 @@ class ImageField(BaseModel):
     image_name: str = Field(description="The name of the image")
 
 
+@invocation_output("image_output")
 class ImageOutput(BaseInvocationOutput):
     """Base class for nodes that output a single image"""
 
-    type: Literal["image_output"] = "image_output"
     image: ImageField = OutputField(description="The output image")
     width: int = OutputField(description="The width of the image in pixels")
     height: int = OutputField(description="The height of the image in pixels")
 
 
+@invocation_output("image_collection_output")
 class ImageCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of images"""
 
-    type: Literal["image_collection_output"] = "image_collection_output"
-
-    # Outputs
     collection: list[ImageField] = OutputField(description="The output images", ui_type=UIType.ImageCollection)
 
 
-@title("Image Primitive")
-@tags("primitives", "image")
+@invocation("image", title="Image Primitive", tags=["primitives", "image"], category="primitives")
 class ImageInvocation(BaseInvocation):
     """An image primitive value"""
 
-    # Metadata
-    type: Literal["image"] = "image"
-
-    # Inputs
     image: ImageField = InputField(description="The image to load")
 
     def invoke(self, context: InvocationContext) -> ImageOutput:
@@ -278,14 +251,15 @@ class ImageInvocation(BaseInvocation):
         )
 
 
-@title("Image Primitive Collection")
-@tags("primitives", "image", "collection")
+@invocation(
+    "image_collection",
+    title="Image Collection Primitive",
+    tags=["primitives", "image", "collection"],
+    category="primitives",
+)
 class ImageCollectionInvocation(BaseInvocation):
     """A collection of image primitive values"""
 
-    type: Literal["image_collection"] = "image_collection"
-
-    # Inputs
     collection: list[ImageField] = InputField(
         default=0, description="The collection of image values", ui_type=UIType.ImageCollection
     )
@@ -306,10 +280,10 @@ class DenoiseMaskField(BaseModel):
     masked_latents_name: Optional[str] = Field(description="The name of the masked image latents")
 
 
+@invocation_output("denoise_mask_output")
 class DenoiseMaskOutput(BaseInvocationOutput):
     """Base class for nodes that output a single image"""
 
-    type: Literal["denoise_mask_output"] = "denoise_mask_output"
     denoise_mask: DenoiseMaskField = OutputField(description="Mask for denoise model run")
 
 
@@ -325,11 +299,10 @@ class LatentsField(BaseModel):
     seed: Optional[int] = Field(default=None, description="Seed used to generate this latents")
 
 
+@invocation_output("latents_output")
 class LatentsOutput(BaseInvocationOutput):
     """Base class for nodes that output a single latents tensor"""
 
-    type: Literal["latents_output"] = "latents_output"
-
     latents: LatentsField = OutputField(
         description=FieldDescriptions.latents,
     )
@@ -337,25 +310,20 @@ class LatentsOutput(BaseInvocationOutput):
     height: int = OutputField(description=FieldDescriptions.height)
 
 
+@invocation_output("latents_collection_output")
 class LatentsCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of latents tensors"""
 
-    type: Literal["latents_collection_output"] = "latents_collection_output"
-
     collection: list[LatentsField] = OutputField(
         description=FieldDescriptions.latents,
         ui_type=UIType.LatentsCollection,
     )
 
 
-@title("Latents Primitive")
-@tags("primitives", "latents")
+@invocation("latents", title="Latents Primitive", tags=["primitives", "latents"], category="primitives")
 class LatentsInvocation(BaseInvocation):
     """A latents tensor primitive value"""
 
-    type: Literal["latents"] = "latents"
-
-    # Inputs
     latents: LatentsField = InputField(description="The latents tensor", input=Input.Connection)
 
     def invoke(self, context: InvocationContext) -> LatentsOutput:
@@ -364,14 +332,15 @@ class LatentsInvocation(BaseInvocation):
         return build_latents_output(self.latents.latents_name, latents)
 
 
-@title("Latents Primitive Collection")
-@tags("primitives", "latents", "collection")
+@invocation(
+    "latents_collection",
+    title="Latents Collection Primitive",
+    tags=["primitives", "latents", "collection"],
+    category="primitives",
+)
 class LatentsCollectionInvocation(BaseInvocation):
     """A collection of latents tensor primitive values"""
 
-    type: Literal["latents_collection"] = "latents_collection"
-
-    # Inputs
     collection: list[LatentsField] = InputField(
         description="The collection of latents tensors", ui_type=UIType.LatentsCollection
     )
@@ -405,30 +374,24 @@ class ColorField(BaseModel):
         return (self.r, self.g, self.b, self.a)
 
 
+@invocation_output("color_output")
 class ColorOutput(BaseInvocationOutput):
     """Base class for nodes that output a single color"""
 
-    type: Literal["color_output"] = "color_output"
     color: ColorField = OutputField(description="The output color")
 
 
+@invocation_output("color_collection_output")
 class ColorCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of colors"""
 
-    type: Literal["color_collection_output"] = "color_collection_output"
-
-    # Outputs
     collection: list[ColorField] = OutputField(description="The output colors", ui_type=UIType.ColorCollection)
 
 
-@title("Color Primitive")
-@tags("primitives", "color")
+@invocation("color", title="Color Primitive", tags=["primitives", "color"], category="primitives")
 class ColorInvocation(BaseInvocation):
     """A color primitive value"""
 
-    type: Literal["color"] = "color"
-
-    # Inputs
     color: ColorField = InputField(default=ColorField(r=0, g=0, b=0, a=255), description="The color value")
 
     def invoke(self, context: InvocationContext) -> ColorOutput:
@@ -446,47 +409,47 @@ class ConditioningField(BaseModel):
     conditioning_name: str = Field(description="The name of conditioning tensor")
 
 
+@invocation_output("conditioning_output")
 class ConditioningOutput(BaseInvocationOutput):
     """Base class for nodes that output a single conditioning tensor"""
 
-    type: Literal["conditioning_output"] = "conditioning_output"
-
     conditioning: ConditioningField = OutputField(description=FieldDescriptions.cond)
 
 
+@invocation_output("conditioning_collection_output")
 class ConditioningCollectionOutput(BaseInvocationOutput):
     """Base class for nodes that output a collection of conditioning tensors"""
 
-    type: Literal["conditioning_collection_output"] = "conditioning_collection_output"
-
-    # Outputs
     collection: list[ConditioningField] = OutputField(
         description="The output conditioning tensors",
         ui_type=UIType.ConditioningCollection,
     )
 
 
-@title("Conditioning Primitive")
-@tags("primitives", "conditioning")
+@invocation(
+    "conditioning",
+    title="Conditioning Primitive",
+    tags=["primitives", "conditioning"],
+    category="primitives",
+)
 class ConditioningInvocation(BaseInvocation):
     """A conditioning tensor primitive value"""
 
-    type: Literal["conditioning"] = "conditioning"
-
     conditioning: ConditioningField = InputField(description=FieldDescriptions.cond, input=Input.Connection)
 
     def invoke(self, context: InvocationContext) -> ConditioningOutput:
         return ConditioningOutput(conditioning=self.conditioning)
 
 
-@title("Conditioning Primitive Collection")
-@tags("primitives", "conditioning", "collection")
+@invocation(
+    "conditioning_collection",
+    title="Conditioning Collection Primitive",
+    tags=["primitives", "conditioning", "collection"],
+    category="primitives",
+)
 class ConditioningCollectionInvocation(BaseInvocation):
     """A collection of conditioning tensor primitive values"""
 
-    type: Literal["conditioning_collection"] = "conditioning_collection"
-
-    # Inputs
     collection: list[ConditioningField] = InputField(
         default=0, description="The collection of conditioning tensors", ui_type=UIType.ConditioningCollection
     )
diff --git a/invokeai/app/invocations/prompt.py b/invokeai/app/invocations/prompt.py
index cc49e33f4c..c42deeaa2c 100644
--- a/invokeai/app/invocations/prompt.py
+++ b/invokeai/app/invocations/prompt.py
@@ -1,5 +1,5 @@
 from os.path import exists
-from typing import Literal, Optional, Union
+from typing import Optional, Union
 
 import numpy as np
 from dynamicprompts.generators import CombinatorialPromptGenerator, RandomPromptGenerator
@@ -7,17 +7,13 @@ from pydantic import validator
 
 from invokeai.app.invocations.primitives import StringCollectionOutput
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, UIComponent, tags, title
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, UIComponent, invocation
 
 
-@title("Dynamic Prompt")
-@tags("prompt", "collection")
+@invocation("dynamic_prompt", title="Dynamic Prompt", tags=["prompt", "collection"], category="prompt")
 class DynamicPromptInvocation(BaseInvocation):
     """Parses a prompt using adieyal/dynamicprompts' random or combinatorial generator"""
 
-    type: Literal["dynamic_prompt"] = "dynamic_prompt"
-
-    # Inputs
     prompt: str = InputField(description="The prompt to parse with dynamicprompts", ui_component=UIComponent.Textarea)
     max_prompts: int = InputField(default=1, description="The number of prompts to generate")
     combinatorial: bool = InputField(default=False, description="Whether to use the combinatorial generator")
@@ -33,14 +29,10 @@ class DynamicPromptInvocation(BaseInvocation):
         return StringCollectionOutput(collection=prompts)
 
 
-@title("Prompts from File")
-@tags("prompt", "file")
+@invocation("prompt_from_file", title="Prompts from File", tags=["prompt", "file"], category="prompt")
 class PromptsFromFileInvocation(BaseInvocation):
     """Loads prompts from a text file"""
 
-    type: Literal["prompt_from_file"] = "prompt_from_file"
-
-    # Inputs
     file_path: str = InputField(description="Path to prompt text file")
     pre_prompt: Optional[str] = InputField(
         default=None, description="String to prepend to each prompt", ui_component=UIComponent.Textarea
diff --git a/invokeai/app/invocations/sdxl.py b/invokeai/app/invocations/sdxl.py
index fc224db14d..288858a173 100644
--- a/invokeai/app/invocations/sdxl.py
+++ b/invokeai/app/invocations/sdxl.py
@@ -1,5 +1,3 @@
-from typing import Literal
-
 from ...backend.model_management import ModelType, SubModelType
 from .baseinvocation import (
     BaseInvocation,
@@ -10,41 +8,35 @@ from .baseinvocation import (
     InvocationContext,
     OutputField,
     UIType,
-    tags,
-    title,
+    invocation,
+    invocation_output,
 )
 from .model import ClipField, MainModelField, ModelInfo, UNetField, VaeField
 
 
+@invocation_output("sdxl_model_loader_output")
 class SDXLModelLoaderOutput(BaseInvocationOutput):
     """SDXL base model loader output"""
 
-    type: Literal["sdxl_model_loader_output"] = "sdxl_model_loader_output"
-
     unet: UNetField = OutputField(description=FieldDescriptions.unet, title="UNet")
     clip: ClipField = OutputField(description=FieldDescriptions.clip, title="CLIP 1")
     clip2: ClipField = OutputField(description=FieldDescriptions.clip, title="CLIP 2")
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
+@invocation_output("sdxl_refiner_model_loader_output")
 class SDXLRefinerModelLoaderOutput(BaseInvocationOutput):
     """SDXL refiner model loader output"""
 
-    type: Literal["sdxl_refiner_model_loader_output"] = "sdxl_refiner_model_loader_output"
-
     unet: UNetField = OutputField(description=FieldDescriptions.unet, title="UNet")
     clip2: ClipField = OutputField(description=FieldDescriptions.clip, title="CLIP 2")
     vae: VaeField = OutputField(description=FieldDescriptions.vae, title="VAE")
 
 
-@title("SDXL Main Model")
-@tags("model", "sdxl")
+@invocation("sdxl_model_loader", title="SDXL Main Model", tags=["model", "sdxl"], category="model")
 class SDXLModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl base model, outputting its submodels."""
 
-    type: Literal["sdxl_model_loader"] = "sdxl_model_loader"
-
-    # Inputs
     model: MainModelField = InputField(
         description=FieldDescriptions.sdxl_main_model, input=Input.Direct, ui_type=UIType.SDXLMainModel
     )
@@ -122,14 +114,15 @@ class SDXLModelLoaderInvocation(BaseInvocation):
         )
 
 
-@title("SDXL Refiner Model")
-@tags("model", "sdxl", "refiner")
+@invocation(
+    "sdxl_refiner_model_loader",
+    title="SDXL Refiner Model",
+    tags=["model", "sdxl", "refiner"],
+    category="model",
+)
 class SDXLRefinerModelLoaderInvocation(BaseInvocation):
     """Loads an sdxl refiner model, outputting its submodels."""
 
-    type: Literal["sdxl_refiner_model_loader"] = "sdxl_refiner_model_loader"
-
-    # Inputs
     model: MainModelField = InputField(
         description=FieldDescriptions.sdxl_refiner_model,
         input=Input.Direct,
diff --git a/invokeai/app/invocations/upscale.py b/invokeai/app/invocations/upscale.py
index bf68cc6c06..e9fb3f9963 100644
--- a/invokeai/app/invocations/upscale.py
+++ b/invokeai/app/invocations/upscale.py
@@ -11,7 +11,7 @@ from invokeai.app.invocations.primitives import ImageField, ImageOutput
 
 from invokeai.app.models.image import ImageCategory, ResourceOrigin
 
-from .baseinvocation import BaseInvocation, InputField, InvocationContext, title, tags
+from .baseinvocation import BaseInvocation, InputField, InvocationContext, invocation
 
 # TODO: Populate this from disk?
 # TODO: Use model manager to load?
@@ -23,14 +23,10 @@ ESRGAN_MODELS = Literal[
 ]
 
 
-@title("Upscale (RealESRGAN)")
-@tags("esrgan", "upscale")
+@invocation("esrgan", title="Upscale (RealESRGAN)", tags=["esrgan", "upscale"], category="esrgan")
 class ESRGANInvocation(BaseInvocation):
     """Upscales an image using RealESRGAN."""
 
-    type: Literal["esrgan"] = "esrgan"
-
-    # Inputs
     image: ImageField = InputField(description="The input image")
     model_name: ESRGAN_MODELS = InputField(default="RealESRGAN_x4plus.pth", description="The Real-ESRGAN model to use")
 
diff --git a/invokeai/app/services/graph.py b/invokeai/app/services/graph.py
index 51cc8a30ae..18c99fafc1 100644
--- a/invokeai/app/services/graph.py
+++ b/invokeai/app/services/graph.py
@@ -3,7 +3,7 @@
 import copy
 import itertools
 import uuid
-from typing import Annotated, Any, Literal, Optional, Union, get_args, get_origin, get_type_hints
+from typing import Annotated, Any, Optional, Union, get_args, get_origin, get_type_hints
 
 import networkx as nx
 from pydantic import BaseModel, root_validator, validator
@@ -14,11 +14,13 @@ from ..invocations import *  # noqa: F401 F403
 from ..invocations.baseinvocation import (
     BaseInvocation,
     BaseInvocationOutput,
+    invocation,
     Input,
     InputField,
     InvocationContext,
     OutputField,
     UIType,
+    invocation_output,
 )
 
 # in 3.10 this would be "from types import NoneType"
@@ -148,24 +150,16 @@ class NodeAlreadyExecutedError(Exception):
 
 
 # TODO: Create and use an Empty output?
+@invocation_output("graph_output")
 class GraphInvocationOutput(BaseInvocationOutput):
-    type: Literal["graph_output"] = "graph_output"
-
-    class Config:
-        schema_extra = {
-            "required": [
-                "type",
-                "image",
-            ]
-        }
+    pass
 
 
 # TODO: Fill this out and move to invocations
+@invocation("graph")
 class GraphInvocation(BaseInvocation):
     """Execute a graph"""
 
-    type: Literal["graph"] = "graph"
-
     # TODO: figure out how to create a default here
     graph: "Graph" = Field(description="The graph to run", default=None)
 
@@ -174,22 +168,20 @@ class GraphInvocation(BaseInvocation):
         return GraphInvocationOutput()
 
 
+@invocation_output("iterate_output")
 class IterateInvocationOutput(BaseInvocationOutput):
     """Used to connect iteration outputs. Will be expanded to a specific output."""
 
-    type: Literal["iterate_output"] = "iterate_output"
-
     item: Any = OutputField(
         description="The item being iterated over", title="Collection Item", ui_type=UIType.CollectionItem
     )
 
 
 # TODO: Fill this out and move to invocations
+@invocation("iterate")
 class IterateInvocation(BaseInvocation):
     """Iterates over a list of items"""
 
-    type: Literal["iterate"] = "iterate"
-
     collection: list[Any] = InputField(
         description="The list of items to iterate over", default_factory=list, ui_type=UIType.Collection
     )
@@ -200,19 +192,17 @@ class IterateInvocation(BaseInvocation):
         return IterateInvocationOutput(item=self.collection[self.index])
 
 
+@invocation_output("collect_output")
 class CollectInvocationOutput(BaseInvocationOutput):
-    type: Literal["collect_output"] = "collect_output"
-
     collection: list[Any] = OutputField(
         description="The collection of input items", title="Collection", ui_type=UIType.Collection
     )
 
 
+@invocation("collect")
 class CollectInvocation(BaseInvocation):
     """Collects values into a collection"""
 
-    type: Literal["collect"] = "collect"
-
     item: Any = InputField(
         description="The item to collect (all inputs must be of the same type)",
         ui_type=UIType.CollectionItem,
diff --git a/invokeai/frontend/web/src/features/nodes/types/types.ts b/invokeai/frontend/web/src/features/nodes/types/types.ts
index 394351c720..a6a36715d4 100644
--- a/invokeai/frontend/web/src/features/nodes/types/types.ts
+++ b/invokeai/frontend/web/src/features/nodes/types/types.ts
@@ -678,6 +678,7 @@ export type TypeHints = {
 export type InvocationSchemaExtra = {
   output: OpenAPIV3.ReferenceObject; // the output of the invocation
   title: string;
+  category?: string;
   tags?: string[];
   properties: Omit<
     NonNullable<OpenAPIV3.SchemaObject['properties']> &
diff --git a/invokeai/frontend/web/src/services/api/schema.d.ts b/invokeai/frontend/web/src/services/api/schema.d.ts
index a64952efa0..85470183c1 100644
--- a/invokeai/frontend/web/src/services/api/schema.d.ts
+++ b/invokeai/frontend/web/src/services/api/schema.d.ts
@@ -326,12 +326,12 @@ export type components = {
     AddInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -340,12 +340,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default add
-       * @enum {string}
-       */
-      type: "add";
       /**
        * A
        * @description The first number
@@ -358,6 +352,12 @@ export type components = {
        * @default 0
        */
       b?: number;
+      /**
+       * Type
+       * @default add
+       * @enum {string}
+       */
+      type: "add";
     };
     /**
      * AppConfig
@@ -409,12 +409,12 @@ export type components = {
     BlankImageInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -423,12 +423,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default blank_image
-       * @enum {string}
-       */
-      type: "blank_image";
       /**
        * Width
        * @description The width of the image
@@ -459,6 +453,12 @@ export type components = {
        * }
        */
       color?: components["schemas"]["ColorField"];
+      /**
+       * Type
+       * @default blank_image
+       * @enum {string}
+       */
+      type: "blank_image";
     };
     /**
      * Blend Latents
@@ -467,12 +467,12 @@ export type components = {
     BlendLatentsInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -481,12 +481,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default lblend
-       * @enum {string}
-       */
-      type: "lblend";
       /**
        * Latents A
        * @description Latents tensor
@@ -503,6 +497,12 @@ export type components = {
        * @default 0.5
        */
       alpha?: number;
+      /**
+       * Type
+       * @default lblend
+       * @enum {string}
+       */
+      type: "lblend";
     };
     /** BoardChanges */
     BoardChanges: {
@@ -680,18 +680,18 @@ export type components = {
       file: Blob;
     };
     /**
-     * Boolean Primitive Collection
+     * Boolean Collection Primitive
      * @description A collection of boolean primitive values
      */
     BooleanCollectionInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -700,34 +700,34 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Collection
+       * @description The collection of boolean values
+       */
+      collection?: boolean[];
       /**
        * Type
        * @default boolean_collection
        * @enum {string}
        */
       type: "boolean_collection";
-      /**
-       * Collection
-       * @description The collection of boolean values
-       */
-      collection?: boolean[];
     };
     /**
      * BooleanCollectionOutput
      * @description Base class for nodes that output a collection of booleans
      */
     BooleanCollectionOutput: {
+      /**
+       * Collection
+       * @description The output boolean collection
+       */
+      collection: boolean[];
       /**
        * Type
        * @default boolean_collection_output
        * @enum {string}
        */
       type: "boolean_collection_output";
-      /**
-       * Collection
-       * @description The output boolean collection
-       */
-      collection: boolean[];
     };
     /**
      * Boolean Primitive
@@ -736,12 +736,12 @@ export type components = {
     BooleanInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -750,35 +750,35 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default boolean
-       * @enum {string}
-       */
-      type: "boolean";
       /**
        * Value
        * @description The boolean value
        * @default false
        */
       value?: boolean;
+      /**
+       * Type
+       * @default boolean
+       * @enum {string}
+       */
+      type: "boolean";
     };
     /**
      * BooleanOutput
      * @description Base class for nodes that output a single boolean
      */
     BooleanOutput: {
+      /**
+       * Value
+       * @description The output boolean
+       */
+      value: boolean;
       /**
        * Type
        * @default boolean_output
        * @enum {string}
        */
       type: "boolean_output";
-      /**
-       * Value
-       * @description The output boolean
-       */
-      value: boolean;
     };
     /**
      * Canny Processor
@@ -787,12 +787,12 @@ export type components = {
     CannyImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -801,17 +801,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default canny_image_processor
        * @enum {string}
        */
       type: "canny_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Low Threshold
        * @description The low threshold of the Canny pixel gradient (0-255)
@@ -855,12 +855,12 @@ export type components = {
     ClipSkipInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -869,12 +869,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default clip_skip
-       * @enum {string}
-       */
-      type: "clip_skip";
       /**
        * CLIP
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
@@ -886,23 +880,29 @@ export type components = {
        * @default 0
        */
       skipped_layers?: number;
+      /**
+       * Type
+       * @default clip_skip
+       * @enum {string}
+       */
+      type: "clip_skip";
     };
     /**
      * ClipSkipInvocationOutput
      * @description Clip skip node output
      */
     ClipSkipInvocationOutput: {
+      /**
+       * CLIP
+       * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
+       */
+      clip?: components["schemas"]["ClipField"];
       /**
        * Type
        * @default clip_skip_output
        * @enum {string}
        */
       type: "clip_skip_output";
-      /**
-       * CLIP
-       * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
-       */
-      clip?: components["schemas"]["ClipField"];
     };
     /**
      * CollectInvocation
@@ -911,12 +911,12 @@ export type components = {
     CollectInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -925,12 +925,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default collect
-       * @enum {string}
-       */
-      type: "collect";
       /**
        * Collection Item
        * @description The item to collect (all inputs must be of the same type)
@@ -941,40 +935,48 @@ export type components = {
        * @description The collection, will be provided on execution
        */
       collection?: unknown[];
+      /**
+       * Type
+       * @default collect
+       * @enum {string}
+       */
+      type: "collect";
     };
     /**
      * CollectInvocationOutput
-     * @description Base class for all invocation outputs
+     * @description Base class for all invocation outputs.
+     *
+     * All invocation outputs must use the `@invocation_output` decorator to provide their unique type.
      */
     CollectInvocationOutput: {
+      /**
+       * Collection
+       * @description The collection of input items
+       */
+      collection: unknown[];
       /**
        * Type
        * @default collect_output
        * @enum {string}
        */
       type: "collect_output";
-      /**
-       * Collection
-       * @description The collection of input items
-       */
-      collection: unknown[];
     };
     /**
      * ColorCollectionOutput
      * @description Base class for nodes that output a collection of colors
      */
     ColorCollectionOutput: {
+      /**
+       * Collection
+       * @description The output colors
+       */
+      collection: components["schemas"]["ColorField"][];
       /**
        * Type
        * @default color_collection_output
        * @enum {string}
        */
       type: "color_collection_output";
-      /**
-       * Collection
-       * @description The output colors
-       */
-      collection: components["schemas"]["ColorField"][];
     };
     /**
      * Color Correct
@@ -984,12 +986,12 @@ export type components = {
     ColorCorrectInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -998,12 +1000,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default color_correct
-       * @enum {string}
-       */
-      type: "color_correct";
       /**
        * Image
        * @description The image to color-correct
@@ -1025,6 +1021,12 @@ export type components = {
        * @default 8
        */
       mask_blur_radius?: number;
+      /**
+       * Type
+       * @default color_correct
+       * @enum {string}
+       */
+      type: "color_correct";
     };
     /**
      * ColorField
@@ -1059,12 +1061,12 @@ export type components = {
     ColorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1073,12 +1075,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default color
-       * @enum {string}
-       */
-      type: "color";
       /**
        * Color
        * @description The color value
@@ -1090,37 +1086,43 @@ export type components = {
        * }
        */
       color?: components["schemas"]["ColorField"];
+      /**
+       * Type
+       * @default color
+       * @enum {string}
+       */
+      type: "color";
     };
     /**
      * ColorOutput
      * @description Base class for nodes that output a single color
      */
     ColorOutput: {
+      /**
+       * Color
+       * @description The output color
+       */
+      color: components["schemas"]["ColorField"];
       /**
        * Type
        * @default color_output
        * @enum {string}
        */
       type: "color_output";
-      /**
-       * Color
-       * @description The output color
-       */
-      color: components["schemas"]["ColorField"];
     };
     /**
-     * Compel Prompt
+     * Prompt
      * @description Parse prompt using compel package to conditioning.
      */
     CompelInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1129,18 +1131,18 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default compel
-       * @enum {string}
-       */
-      type: "compel";
       /**
        * Prompt
        * @description Prompt to be parsed by Compel to create a conditioning tensor
        * @default
        */
       prompt?: string;
+      /**
+       * Type
+       * @default compel
+       * @enum {string}
+       */
+      type: "compel";
       /**
        * CLIP
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
@@ -1148,18 +1150,18 @@ export type components = {
       clip?: components["schemas"]["ClipField"];
     };
     /**
-     * Conditioning Primitive Collection
+     * Conditioning Collection Primitive
      * @description A collection of conditioning tensor primitive values
      */
     ConditioningCollectionInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1168,35 +1170,35 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default conditioning_collection
-       * @enum {string}
-       */
-      type: "conditioning_collection";
       /**
        * Collection
        * @description The collection of conditioning tensors
        * @default 0
        */
       collection?: components["schemas"]["ConditioningField"][];
+      /**
+       * Type
+       * @default conditioning_collection
+       * @enum {string}
+       */
+      type: "conditioning_collection";
     };
     /**
      * ConditioningCollectionOutput
      * @description Base class for nodes that output a collection of conditioning tensors
      */
     ConditioningCollectionOutput: {
+      /**
+       * Collection
+       * @description The output conditioning tensors
+       */
+      collection: components["schemas"]["ConditioningField"][];
       /**
        * Type
        * @default conditioning_collection_output
        * @enum {string}
        */
       type: "conditioning_collection_output";
-      /**
-       * Collection
-       * @description The output conditioning tensors
-       */
-      collection: components["schemas"]["ConditioningField"][];
     };
     /**
      * ConditioningField
@@ -1216,12 +1218,12 @@ export type components = {
     ConditioningInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1230,34 +1232,34 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Conditioning
+       * @description Conditioning tensor
+       */
+      conditioning?: components["schemas"]["ConditioningField"];
       /**
        * Type
        * @default conditioning
        * @enum {string}
        */
       type: "conditioning";
-      /**
-       * Conditioning
-       * @description Conditioning tensor
-       */
-      conditioning?: components["schemas"]["ConditioningField"];
     };
     /**
      * ConditioningOutput
      * @description Base class for nodes that output a single conditioning tensor
      */
     ConditioningOutput: {
+      /**
+       * Conditioning
+       * @description Conditioning tensor
+       */
+      conditioning: components["schemas"]["ConditioningField"];
       /**
        * Type
        * @default conditioning_output
        * @enum {string}
        */
       type: "conditioning_output";
-      /**
-       * Conditioning
-       * @description Conditioning tensor
-       */
-      conditioning: components["schemas"]["ConditioningField"];
     };
     /**
      * Content Shuffle Processor
@@ -1266,12 +1268,12 @@ export type components = {
     ContentShuffleImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1280,17 +1282,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default content_shuffle_image_processor
        * @enum {string}
        */
       type: "content_shuffle_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Detect Resolution
        * @description Pixel resolution for detection
@@ -1374,12 +1376,12 @@ export type components = {
     ControlNetInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1388,12 +1390,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default controlnet
-       * @enum {string}
-       */
-      type: "controlnet";
       /**
        * Image
        * @description The control image
@@ -1437,6 +1433,12 @@ export type components = {
        * @enum {string}
        */
       resize_mode?: "just_resize" | "crop_resize" | "fill_resize" | "just_resize_simple";
+      /**
+       * Type
+       * @default controlnet
+       * @enum {string}
+       */
+      type: "controlnet";
     };
     /** ControlNetModelCheckpointConfig */
     ControlNetModelCheckpointConfig: {
@@ -1500,17 +1502,17 @@ export type components = {
      * @description node output for ControlNet info
      */
     ControlOutput: {
+      /**
+       * Control
+       * @description ControlNet(s) to apply
+       */
+      control: components["schemas"]["ControlField"];
       /**
        * Type
        * @default control_output
        * @enum {string}
        */
       type: "control_output";
-      /**
-       * Control
-       * @description ControlNet(s) to apply
-       */
-      control: components["schemas"]["ControlField"];
     };
     /**
      * CoreMetadata
@@ -1666,12 +1668,12 @@ export type components = {
     CreateDenoiseMaskInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1680,12 +1682,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default create_denoise_mask
-       * @enum {string}
-       */
-      type: "create_denoise_mask";
       /**
        * Vae
        * @description VAE
@@ -1713,6 +1709,12 @@ export type components = {
        * @default false
        */
       fp32?: boolean;
+      /**
+       * Type
+       * @default create_denoise_mask
+       * @enum {string}
+       */
+      type: "create_denoise_mask";
     };
     /**
      * OpenCV Inpaint
@@ -1721,12 +1723,12 @@ export type components = {
     CvInpaintInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1735,12 +1737,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default cv_inpaint
-       * @enum {string}
-       */
-      type: "cv_inpaint";
       /**
        * Image
        * @description The image to inpaint
@@ -1751,6 +1747,12 @@ export type components = {
        * @description The mask to use when inpainting
        */
       mask?: components["schemas"]["ImageField"];
+      /**
+       * Type
+       * @default cv_inpaint
+       * @enum {string}
+       */
+      type: "cv_inpaint";
     };
     /** DeleteBoardResult */
     DeleteBoardResult: {
@@ -1782,12 +1784,12 @@ export type components = {
     DenoiseLatentsInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1796,12 +1798,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default denoise_latents
-       * @enum {string}
-       */
-      type: "denoise_latents";
       /**
        * Noise
        * @description Noise tensor
@@ -1853,6 +1849,12 @@ export type components = {
        * @description The mask to use for the operation
        */
       denoise_mask?: components["schemas"]["DenoiseMaskField"];
+      /**
+       * Type
+       * @default denoise_latents
+       * @enum {string}
+       */
+      type: "denoise_latents";
       /**
        * Positive Conditioning
        * @description Positive conditioning tensor
@@ -1890,17 +1892,17 @@ export type components = {
      * @description Base class for nodes that output a single image
      */
     DenoiseMaskOutput: {
+      /**
+       * Denoise Mask
+       * @description Mask for denoise model run
+       */
+      denoise_mask: components["schemas"]["DenoiseMaskField"];
       /**
        * Type
        * @default denoise_mask_output
        * @enum {string}
        */
       type: "denoise_mask_output";
-      /**
-       * Denoise Mask
-       * @description Mask for denoise model run
-       */
-      denoise_mask: components["schemas"]["DenoiseMaskField"];
     };
     /**
      * Divide Integers
@@ -1909,12 +1911,12 @@ export type components = {
     DivideInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1923,12 +1925,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default div
-       * @enum {string}
-       */
-      type: "div";
       /**
        * A
        * @description The first number
@@ -1941,6 +1937,12 @@ export type components = {
        * @default 0
        */
       b?: number;
+      /**
+       * Type
+       * @default div
+       * @enum {string}
+       */
+      type: "div";
     };
     /**
      * Dynamic Prompt
@@ -1949,12 +1951,12 @@ export type components = {
     DynamicPromptInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -1963,12 +1965,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default dynamic_prompt
-       * @enum {string}
-       */
-      type: "dynamic_prompt";
       /**
        * Prompt
        * @description The prompt to parse with dynamicprompts
@@ -1986,6 +1982,12 @@ export type components = {
        * @default false
        */
       combinatorial?: boolean;
+      /**
+       * Type
+       * @default dynamic_prompt
+       * @enum {string}
+       */
+      type: "dynamic_prompt";
     };
     /**
      * Upscale (RealESRGAN)
@@ -1994,12 +1996,12 @@ export type components = {
     ESRGANInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2008,12 +2010,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default esrgan
-       * @enum {string}
-       */
-      type: "esrgan";
       /**
        * Image
        * @description The input image
@@ -2026,6 +2022,12 @@ export type components = {
        * @enum {string}
        */
       model_name?: "RealESRGAN_x4plus.pth" | "RealESRGAN_x4plus_anime_6B.pth" | "ESRGAN_SRx4_DF2KOST_official-ff704c30.pth" | "RealESRGAN_x2plus.pth";
+      /**
+       * Type
+       * @default esrgan
+       * @enum {string}
+       */
+      type: "esrgan";
     };
     /** Edge */
     Edge: {
@@ -2054,18 +2056,18 @@ export type components = {
       field: string;
     };
     /**
-     * Float Primitive Collection
+     * Float Collection Primitive
      * @description A collection of float primitive values
      */
     FloatCollectionInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2074,34 +2076,34 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Collection
+       * @description The collection of float values
+       */
+      collection?: number[];
       /**
        * Type
        * @default float_collection
        * @enum {string}
        */
       type: "float_collection";
-      /**
-       * Collection
-       * @description The collection of float values
-       */
-      collection?: number[];
     };
     /**
      * FloatCollectionOutput
      * @description Base class for nodes that output a collection of floats
      */
     FloatCollectionOutput: {
+      /**
+       * Collection
+       * @description The float collection
+       */
+      collection: number[];
       /**
        * Type
        * @default float_collection_output
        * @enum {string}
        */
       type: "float_collection_output";
-      /**
-       * Collection
-       * @description The float collection
-       */
-      collection: number[];
     };
     /**
      * Float Primitive
@@ -2110,12 +2112,12 @@ export type components = {
     FloatInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2124,18 +2126,18 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default float
-       * @enum {string}
-       */
-      type: "float";
       /**
        * Value
        * @description The float value
        * @default 0
        */
       value?: number;
+      /**
+       * Type
+       * @default float
+       * @enum {string}
+       */
+      type: "float";
     };
     /**
      * Float Range
@@ -2144,12 +2146,12 @@ export type components = {
     FloatLinearRangeInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2158,12 +2160,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default float_range
-       * @enum {string}
-       */
-      type: "float_range";
       /**
        * Start
        * @description The first value of the range
@@ -2182,23 +2178,29 @@ export type components = {
        * @default 30
        */
       steps?: number;
+      /**
+       * Type
+       * @default float_range
+       * @enum {string}
+       */
+      type: "float_range";
     };
     /**
      * FloatOutput
      * @description Base class for nodes that output a single float
      */
     FloatOutput: {
+      /**
+       * Value
+       * @description The output float
+       */
+      value: number;
       /**
        * Type
        * @default float_output
        * @enum {string}
        */
       type: "float_output";
-      /**
-       * Value
-       * @description The output float
-       */
-      value: number;
     };
     /** Graph */
     Graph: {
@@ -2212,7 +2214,7 @@ export type components = {
        * @description The nodes in this graph
        */
       nodes?: {
-        [key: string]: components["schemas"]["BooleanInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageLuminosityAdjustmentInvocation"] | components["schemas"]["ImageSaturationAdjustmentInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ONNXPromptInvocation"] | components["schemas"]["ONNXTextToLatentsInvocation"] | components["schemas"]["ONNXLatentsToImageInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"];
+        [key: string]: components["schemas"]["BooleanInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["ONNXPromptInvocation"] | components["schemas"]["ONNXTextToLatentsInvocation"] | components["schemas"]["ONNXLatentsToImageInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageLuminosityAdjustmentInvocation"] | components["schemas"]["ImageSaturationAdjustmentInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"];
       };
       /**
        * Edges
@@ -2255,7 +2257,7 @@ export type components = {
        * @description The results of node executions
        */
       results: {
-        [key: string]: components["schemas"]["BooleanOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["VaeLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["MetadataAccumulatorOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["ONNXModelLoaderOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["CollectInvocationOutput"];
+        [key: string]: components["schemas"]["BooleanOutput"] | components["schemas"]["BooleanCollectionOutput"] | components["schemas"]["IntegerOutput"] | components["schemas"]["IntegerCollectionOutput"] | components["schemas"]["FloatOutput"] | components["schemas"]["FloatCollectionOutput"] | components["schemas"]["StringOutput"] | components["schemas"]["StringCollectionOutput"] | components["schemas"]["ImageOutput"] | components["schemas"]["ImageCollectionOutput"] | components["schemas"]["DenoiseMaskOutput"] | components["schemas"]["LatentsOutput"] | components["schemas"]["LatentsCollectionOutput"] | components["schemas"]["ColorOutput"] | components["schemas"]["ColorCollectionOutput"] | components["schemas"]["ConditioningOutput"] | components["schemas"]["ConditioningCollectionOutput"] | components["schemas"]["ControlOutput"] | components["schemas"]["ModelLoaderOutput"] | components["schemas"]["LoraLoaderOutput"] | components["schemas"]["SDXLLoraLoaderOutput"] | components["schemas"]["VaeLoaderOutput"] | components["schemas"]["SeamlessModeOutput"] | components["schemas"]["MetadataAccumulatorOutput"] | components["schemas"]["SDXLModelLoaderOutput"] | components["schemas"]["SDXLRefinerModelLoaderOutput"] | components["schemas"]["ClipSkipInvocationOutput"] | components["schemas"]["ONNXModelLoaderOutput"] | components["schemas"]["NoiseOutput"] | components["schemas"]["GraphInvocationOutput"] | components["schemas"]["IterateInvocationOutput"] | components["schemas"]["CollectInvocationOutput"];
       };
       /**
        * Errors
@@ -2286,12 +2288,12 @@ export type components = {
     GraphInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2300,21 +2302,23 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Graph
+       * @description The graph to run
+       */
+      graph?: components["schemas"]["Graph"];
       /**
        * Type
        * @default graph
        * @enum {string}
        */
       type: "graph";
-      /**
-       * Graph
-       * @description The graph to run
-       */
-      graph?: components["schemas"]["Graph"];
     };
     /**
      * GraphInvocationOutput
-     * @description Base class for all invocation outputs
+     * @description Base class for all invocation outputs.
+     *
+     * All invocation outputs must use the `@invocation_output` decorator to provide their unique type.
      */
     GraphInvocationOutput: {
       /**
@@ -2336,12 +2340,12 @@ export type components = {
     HedImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2350,17 +2354,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default hed_image_processor
        * @enum {string}
        */
       type: "hed_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Detect Resolution
        * @description Pixel resolution for detection
@@ -2387,12 +2391,12 @@ export type components = {
     ImageBlurInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2401,12 +2405,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_blur
-       * @enum {string}
-       */
-      type: "img_blur";
       /**
        * Image
        * @description The image to blur
@@ -2425,6 +2423,12 @@ export type components = {
        * @enum {string}
        */
       blur_type?: "gaussian" | "box";
+      /**
+       * Type
+       * @default img_blur
+       * @enum {string}
+       */
+      type: "img_blur";
     };
     /**
      * ImageCategory
@@ -2445,12 +2449,12 @@ export type components = {
     ImageChannelInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2459,12 +2463,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_chan
-       * @enum {string}
-       */
-      type: "img_chan";
       /**
        * Image
        * @description The image to get the channel from
@@ -2477,20 +2475,26 @@ export type components = {
        * @enum {string}
        */
       channel?: "A" | "R" | "G" | "B";
+      /**
+       * Type
+       * @default img_chan
+       * @enum {string}
+       */
+      type: "img_chan";
     };
     /**
-     * Image Primitive Collection
+     * Image Collection Primitive
      * @description A collection of image primitive values
      */
     ImageCollectionInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2499,35 +2503,35 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default image_collection
-       * @enum {string}
-       */
-      type: "image_collection";
       /**
        * Collection
        * @description The collection of image values
        * @default 0
        */
       collection?: components["schemas"]["ImageField"][];
+      /**
+       * Type
+       * @default image_collection
+       * @enum {string}
+       */
+      type: "image_collection";
     };
     /**
      * ImageCollectionOutput
      * @description Base class for nodes that output a collection of images
      */
     ImageCollectionOutput: {
+      /**
+       * Collection
+       * @description The output images
+       */
+      collection: components["schemas"]["ImageField"][];
       /**
        * Type
        * @default image_collection_output
        * @enum {string}
        */
       type: "image_collection_output";
-      /**
-       * Collection
-       * @description The output images
-       */
-      collection: components["schemas"]["ImageField"][];
     };
     /**
      * Convert Image Mode
@@ -2536,12 +2540,12 @@ export type components = {
     ImageConvertInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2550,12 +2554,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_conv
-       * @enum {string}
-       */
-      type: "img_conv";
       /**
        * Image
        * @description The image to convert
@@ -2568,6 +2566,12 @@ export type components = {
        * @enum {string}
        */
       mode?: "L" | "RGB" | "RGBA" | "CMYK" | "YCbCr" | "LAB" | "HSV" | "I" | "F";
+      /**
+       * Type
+       * @default img_conv
+       * @enum {string}
+       */
+      type: "img_conv";
     };
     /**
      * Crop Image
@@ -2576,12 +2580,12 @@ export type components = {
     ImageCropInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2590,12 +2594,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_crop
-       * @enum {string}
-       */
-      type: "img_crop";
       /**
        * Image
        * @description The image to crop
@@ -2625,6 +2623,12 @@ export type components = {
        * @default 512
        */
       height?: number;
+      /**
+       * Type
+       * @default img_crop
+       * @enum {string}
+       */
+      type: "img_crop";
     };
     /**
      * ImageDTO
@@ -2713,18 +2717,18 @@ export type components = {
       image_name: string;
     };
     /**
-     * Image Hue Adjustment
+     * Adjust Image Hue
      * @description Adjusts the Hue of an image.
      */
     ImageHueAdjustmentInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2733,12 +2737,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_hue_adjust
-       * @enum {string}
-       */
-      type: "img_hue_adjust";
       /**
        * Image
        * @description The image to adjust
@@ -2750,6 +2748,12 @@ export type components = {
        * @default 0
        */
       hue?: number;
+      /**
+       * Type
+       * @default img_hue_adjust
+       * @enum {string}
+       */
+      type: "img_hue_adjust";
     };
     /**
      * Inverse Lerp Image
@@ -2758,12 +2762,12 @@ export type components = {
     ImageInverseLerpInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2772,12 +2776,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_ilerp
-       * @enum {string}
-       */
-      type: "img_ilerp";
       /**
        * Image
        * @description The image to lerp
@@ -2795,6 +2793,12 @@ export type components = {
        * @default 255
        */
       max?: number;
+      /**
+       * Type
+       * @default img_ilerp
+       * @enum {string}
+       */
+      type: "img_ilerp";
     };
     /**
      * Image Primitive
@@ -2803,12 +2807,12 @@ export type components = {
     ImageInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2817,17 +2821,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to load
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default image
        * @enum {string}
        */
       type: "image";
-      /**
-       * Image
-       * @description The image to load
-       */
-      image?: components["schemas"]["ImageField"];
     };
     /**
      * Lerp Image
@@ -2836,12 +2840,12 @@ export type components = {
     ImageLerpInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2850,12 +2854,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_lerp
-       * @enum {string}
-       */
-      type: "img_lerp";
       /**
        * Image
        * @description The image to lerp
@@ -2873,20 +2871,26 @@ export type components = {
        * @default 255
        */
       max?: number;
+      /**
+       * Type
+       * @default img_lerp
+       * @enum {string}
+       */
+      type: "img_lerp";
     };
     /**
-     * Image Luminosity Adjustment
+     * Adjust Image Luminosity
      * @description Adjusts the Luminosity (Value) of an image.
      */
     ImageLuminosityAdjustmentInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2895,12 +2899,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_luminosity_adjust
-       * @enum {string}
-       */
-      type: "img_luminosity_adjust";
       /**
        * Image
        * @description The image to adjust
@@ -2912,6 +2910,12 @@ export type components = {
        * @default 1
        */
       luminosity?: number;
+      /**
+       * Type
+       * @default img_luminosity_adjust
+       * @enum {string}
+       */
+      type: "img_luminosity_adjust";
     };
     /**
      * ImageMetadata
@@ -2936,12 +2940,12 @@ export type components = {
     ImageMultiplyInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2950,12 +2954,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_mul
-       * @enum {string}
-       */
-      type: "img_mul";
       /**
        * Image1
        * @description The first image to multiply
@@ -2966,6 +2964,12 @@ export type components = {
        * @description The second image to multiply
        */
       image2?: components["schemas"]["ImageField"];
+      /**
+       * Type
+       * @default img_mul
+       * @enum {string}
+       */
+      type: "img_mul";
     };
     /**
      * Blur NSFW Image
@@ -2974,12 +2978,12 @@ export type components = {
     ImageNSFWBlurInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -2988,17 +2992,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Metadata
+       * @description Optional core metadata to be written to image
+       */
+      metadata?: components["schemas"]["CoreMetadata"];
       /**
        * Type
        * @default img_nsfw
        * @enum {string}
        */
       type: "img_nsfw";
-      /**
-       * Metadata
-       * @description Optional core metadata to be written to image
-       */
-      metadata?: components["schemas"]["CoreMetadata"];
       /**
        * Image
        * @description The image to check
@@ -3010,12 +3014,6 @@ export type components = {
      * @description Base class for nodes that output a single image
      */
     ImageOutput: {
-      /**
-       * Type
-       * @default image_output
-       * @enum {string}
-       */
-      type: "image_output";
       /**
        * Image
        * @description The output image
@@ -3031,6 +3029,12 @@ export type components = {
        * @description The height of the image in pixels
        */
       height: number;
+      /**
+       * Type
+       * @default image_output
+       * @enum {string}
+       */
+      type: "image_output";
     };
     /**
      * Paste Image
@@ -3039,12 +3043,12 @@ export type components = {
     ImagePasteInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3053,12 +3057,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_paste
-       * @enum {string}
-       */
-      type: "img_paste";
       /**
        * Base Image
        * @description The base image
@@ -3086,20 +3084,26 @@ export type components = {
        * @default 0
        */
       y?: number;
+      /**
+       * Type
+       * @default img_paste
+       * @enum {string}
+       */
+      type: "img_paste";
     };
     /**
-     * ImageProcessorInvocation
+     * Base Image Processor
      * @description Base class for invocations that preprocess images for ControlNet
      */
     ImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3108,17 +3112,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default image_processor
        * @enum {string}
        */
       type: "image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
     };
     /**
      * ImageRecordChanges
@@ -3156,12 +3160,12 @@ export type components = {
     ImageResizeInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3170,12 +3174,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_resize
-       * @enum {string}
-       */
-      type: "img_resize";
       /**
        * Image
        * @description The image to resize
@@ -3205,20 +3203,26 @@ export type components = {
        * @description Optional core metadata to be written to image
        */
       metadata?: components["schemas"]["CoreMetadata"];
+      /**
+       * Type
+       * @default img_resize
+       * @enum {string}
+       */
+      type: "img_resize";
     };
     /**
-     * Image Saturation Adjustment
+     * Adjust Image Saturation
      * @description Adjusts the Saturation of an image.
      */
     ImageSaturationAdjustmentInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3227,12 +3231,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_saturation_adjust
-       * @enum {string}
-       */
-      type: "img_saturation_adjust";
       /**
        * Image
        * @description The image to adjust
@@ -3244,6 +3242,12 @@ export type components = {
        * @default 1
        */
       saturation?: number;
+      /**
+       * Type
+       * @default img_saturation_adjust
+       * @enum {string}
+       */
+      type: "img_saturation_adjust";
     };
     /**
      * Scale Image
@@ -3252,12 +3256,12 @@ export type components = {
     ImageScaleInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3266,12 +3270,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_scale
-       * @enum {string}
-       */
-      type: "img_scale";
       /**
        * Image
        * @description The image to scale
@@ -3290,6 +3288,12 @@ export type components = {
        * @enum {string}
        */
       resample_mode?: "nearest" | "box" | "bilinear" | "hamming" | "bicubic" | "lanczos";
+      /**
+       * Type
+       * @default img_scale
+       * @enum {string}
+       */
+      type: "img_scale";
     };
     /**
      * Image to Latents
@@ -3298,12 +3302,12 @@ export type components = {
     ImageToLatentsInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3312,12 +3316,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default i2l
-       * @enum {string}
-       */
-      type: "i2l";
       /**
        * Image
        * @description The image to encode
@@ -3340,6 +3338,12 @@ export type components = {
        * @default false
        */
       fp32?: boolean;
+      /**
+       * Type
+       * @default i2l
+       * @enum {string}
+       */
+      type: "i2l";
     };
     /**
      * ImageUrlsDTO
@@ -3369,12 +3373,12 @@ export type components = {
     ImageWatermarkInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3383,12 +3387,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default img_watermark
-       * @enum {string}
-       */
-      type: "img_watermark";
       /**
        * Image
        * @description The image to check
@@ -3405,6 +3403,12 @@ export type components = {
        * @description Optional core metadata to be written to image
        */
       metadata?: components["schemas"]["CoreMetadata"];
+      /**
+       * Type
+       * @default img_watermark
+       * @enum {string}
+       */
+      type: "img_watermark";
     };
     /** ImagesUpdatedFromListResult */
     ImagesUpdatedFromListResult: {
@@ -3421,12 +3425,12 @@ export type components = {
     InfillColorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3435,12 +3439,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default infill_rgba
-       * @enum {string}
-       */
-      type: "infill_rgba";
       /**
        * Image
        * @description The image to infill
@@ -3457,6 +3455,12 @@ export type components = {
        * }
        */
       color?: components["schemas"]["ColorField"];
+      /**
+       * Type
+       * @default infill_rgba
+       * @enum {string}
+       */
+      type: "infill_rgba";
     };
     /**
      * PatchMatch Infill
@@ -3465,12 +3469,12 @@ export type components = {
     InfillPatchMatchInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3479,17 +3483,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to infill
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default infill_patchmatch
        * @enum {string}
        */
       type: "infill_patchmatch";
-      /**
-       * Image
-       * @description The image to infill
-       */
-      image?: components["schemas"]["ImageField"];
     };
     /**
      * Tile Infill
@@ -3498,12 +3502,12 @@ export type components = {
     InfillTileInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3512,12 +3516,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default infill_tile
-       * @enum {string}
-       */
-      type: "infill_tile";
       /**
        * Image
        * @description The image to infill
@@ -3534,20 +3532,26 @@ export type components = {
        * @description The seed to use for tile generation (omit for random)
        */
       seed?: number;
+      /**
+       * Type
+       * @default infill_tile
+       * @enum {string}
+       */
+      type: "infill_tile";
     };
     /**
-     * Integer Primitive Collection
+     * Integer Collection Primitive
      * @description A collection of integer primitive values
      */
     IntegerCollectionInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3556,35 +3560,35 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default integer_collection
-       * @enum {string}
-       */
-      type: "integer_collection";
       /**
        * Collection
        * @description The collection of integer values
        * @default 0
        */
       collection?: number[];
+      /**
+       * Type
+       * @default integer_collection
+       * @enum {string}
+       */
+      type: "integer_collection";
     };
     /**
      * IntegerCollectionOutput
      * @description Base class for nodes that output a collection of integers
      */
     IntegerCollectionOutput: {
+      /**
+       * Collection
+       * @description The int collection
+       */
+      collection: number[];
       /**
        * Type
        * @default integer_collection_output
        * @enum {string}
        */
       type: "integer_collection_output";
-      /**
-       * Collection
-       * @description The int collection
-       */
-      collection: number[];
     };
     /**
      * Integer Primitive
@@ -3593,12 +3597,12 @@ export type components = {
     IntegerInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3607,35 +3611,35 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default integer
-       * @enum {string}
-       */
-      type: "integer";
       /**
        * Value
        * @description The integer value
        * @default 0
        */
       value?: number;
+      /**
+       * Type
+       * @default integer
+       * @enum {string}
+       */
+      type: "integer";
     };
     /**
      * IntegerOutput
      * @description Base class for nodes that output a single integer
      */
     IntegerOutput: {
+      /**
+       * Value
+       * @description The output integer
+       */
+      value: number;
       /**
        * Type
        * @default integer_output
        * @enum {string}
        */
       type: "integer_output";
-      /**
-       * Value
-       * @description The output integer
-       */
-      value: number;
     };
     /**
      * IterateInvocation
@@ -3644,12 +3648,12 @@ export type components = {
     IterateInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3658,12 +3662,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default iterate
-       * @enum {string}
-       */
-      type: "iterate";
       /**
        * Collection
        * @description The list of items to iterate over
@@ -3675,23 +3673,29 @@ export type components = {
        * @default 0
        */
       index?: number;
+      /**
+       * Type
+       * @default iterate
+       * @enum {string}
+       */
+      type: "iterate";
     };
     /**
      * IterateInvocationOutput
      * @description Used to connect iteration outputs. Will be expanded to a specific output.
      */
     IterateInvocationOutput: {
+      /**
+       * Collection Item
+       * @description The item being iterated over
+       */
+      item?: unknown;
       /**
        * Type
        * @default iterate_output
        * @enum {string}
        */
       type: "iterate_output";
-      /**
-       * Collection Item
-       * @description The item being iterated over
-       */
-      item?: unknown;
     };
     /**
      * LaMa Infill
@@ -3700,12 +3704,12 @@ export type components = {
     LaMaInfillInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3714,31 +3718,31 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to infill
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default infill_lama
        * @enum {string}
        */
       type: "infill_lama";
-      /**
-       * Image
-       * @description The image to infill
-       */
-      image?: components["schemas"]["ImageField"];
     };
     /**
-     * Latents Primitive Collection
+     * Latents Collection Primitive
      * @description A collection of latents tensor primitive values
      */
     LatentsCollectionInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3747,34 +3751,34 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Collection
+       * @description The collection of latents tensors
+       */
+      collection?: components["schemas"]["LatentsField"][];
       /**
        * Type
        * @default latents_collection
        * @enum {string}
        */
       type: "latents_collection";
-      /**
-       * Collection
-       * @description The collection of latents tensors
-       */
-      collection?: components["schemas"]["LatentsField"][];
     };
     /**
      * LatentsCollectionOutput
      * @description Base class for nodes that output a collection of latents tensors
      */
     LatentsCollectionOutput: {
+      /**
+       * Collection
+       * @description Latents tensor
+       */
+      collection: components["schemas"]["LatentsField"][];
       /**
        * Type
        * @default latents_collection_output
        * @enum {string}
        */
       type: "latents_collection_output";
-      /**
-       * Collection
-       * @description Latents tensor
-       */
-      collection: components["schemas"]["LatentsField"][];
     };
     /**
      * LatentsField
@@ -3799,12 +3803,12 @@ export type components = {
     LatentsInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3813,29 +3817,23 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Latents
+       * @description The latents tensor
+       */
+      latents?: components["schemas"]["LatentsField"];
       /**
        * Type
        * @default latents
        * @enum {string}
        */
       type: "latents";
-      /**
-       * Latents
-       * @description The latents tensor
-       */
-      latents?: components["schemas"]["LatentsField"];
     };
     /**
      * LatentsOutput
      * @description Base class for nodes that output a single latents tensor
      */
     LatentsOutput: {
-      /**
-       * Type
-       * @default latents_output
-       * @enum {string}
-       */
-      type: "latents_output";
       /**
        * Latents
        * @description Latents tensor
@@ -3851,6 +3849,12 @@ export type components = {
        * @description Height of output (px)
        */
       height: number;
+      /**
+       * Type
+       * @default latents_output
+       * @enum {string}
+       */
+      type: "latents_output";
     };
     /**
      * Latents to Image
@@ -3859,12 +3863,12 @@ export type components = {
     LatentsToImageInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3873,12 +3877,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default l2i
-       * @enum {string}
-       */
-      type: "l2i";
       /**
        * Tiled
        * @description Processing using overlapping tiles (reduce memory consumption)
@@ -3896,6 +3894,12 @@ export type components = {
        * @description Optional core metadata to be written to image
        */
       metadata?: components["schemas"]["CoreMetadata"];
+      /**
+       * Type
+       * @default l2i
+       * @enum {string}
+       */
+      type: "l2i";
       /**
        * Latents
        * @description Latents tensor
@@ -3914,12 +3918,12 @@ export type components = {
     LeresImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3928,17 +3932,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default leres_image_processor
        * @enum {string}
        */
       type: "leres_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Thr A
        * @description Leres parameter `thr_a`
@@ -3977,12 +3981,12 @@ export type components = {
     LineartAnimeImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -3991,17 +3995,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default lineart_anime_image_processor
        * @enum {string}
        */
       type: "lineart_anime_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Detect Resolution
        * @description Pixel resolution for detection
@@ -4022,12 +4026,12 @@ export type components = {
     LineartImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4036,17 +4040,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default lineart_image_processor
        * @enum {string}
        */
       type: "lineart_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Detect Resolution
        * @description Pixel resolution for detection
@@ -4150,12 +4154,12 @@ export type components = {
     LoraLoaderInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4164,12 +4168,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default lora_loader
-       * @enum {string}
-       */
-      type: "lora_loader";
       /**
        * LoRA
        * @description LoRA model to load
@@ -4191,18 +4189,18 @@ export type components = {
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
        */
       clip?: components["schemas"]["ClipField"];
+      /**
+       * Type
+       * @default lora_loader
+       * @enum {string}
+       */
+      type: "lora_loader";
     };
     /**
      * LoraLoaderOutput
      * @description Model loader output
      */
     LoraLoaderOutput: {
-      /**
-       * Type
-       * @default lora_loader_output
-       * @enum {string}
-       */
-      type: "lora_loader_output";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -4213,6 +4211,12 @@ export type components = {
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
        */
       clip?: components["schemas"]["ClipField"];
+      /**
+       * Type
+       * @default lora_loader_output
+       * @enum {string}
+       */
+      type: "lora_loader_output";
     };
     /**
      * MainModelField
@@ -4236,12 +4240,12 @@ export type components = {
     MainModelLoaderInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4250,31 +4254,31 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Model
+       * @description Main model (UNet, VAE, CLIP) to load
+       */
+      model: components["schemas"]["MainModelField"];
       /**
        * Type
        * @default main_model_loader
        * @enum {string}
        */
       type: "main_model_loader";
-      /**
-       * Model
-       * @description Main model (UNet, VAE, CLIP) to load
-       */
-      model: components["schemas"]["MainModelField"];
     };
     /**
-     * Combine Mask
+     * Combine Masks
      * @description Combine two masks together by multiplying them using `PIL.ImageChops.multiply()`.
      */
     MaskCombineInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4283,12 +4287,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default mask_combine
-       * @enum {string}
-       */
-      type: "mask_combine";
       /**
        * Mask1
        * @description The first mask to combine
@@ -4299,6 +4297,12 @@ export type components = {
        * @description The second image to combine
        */
       mask2?: components["schemas"]["ImageField"];
+      /**
+       * Type
+       * @default mask_combine
+       * @enum {string}
+       */
+      type: "mask_combine";
     };
     /**
      * Mask Edge
@@ -4307,12 +4311,12 @@ export type components = {
     MaskEdgeInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4321,12 +4325,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default mask_edge
-       * @enum {string}
-       */
-      type: "mask_edge";
       /**
        * Image
        * @description The image to apply the mask to
@@ -4352,6 +4350,12 @@ export type components = {
        * @description Second threshold for the hysteresis procedure in Canny edge detection
        */
       high_threshold?: number;
+      /**
+       * Type
+       * @default mask_edge
+       * @enum {string}
+       */
+      type: "mask_edge";
     };
     /**
      * Mask from Alpha
@@ -4360,12 +4364,12 @@ export type components = {
     MaskFromAlphaInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4374,12 +4378,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default tomask
-       * @enum {string}
-       */
-      type: "tomask";
       /**
        * Image
        * @description The image to create the mask from
@@ -4391,6 +4389,12 @@ export type components = {
        * @default false
        */
       invert?: boolean;
+      /**
+       * Type
+       * @default tomask
+       * @enum {string}
+       */
+      type: "tomask";
     };
     /**
      * Mediapipe Face Processor
@@ -4399,12 +4403,12 @@ export type components = {
     MediapipeFaceProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4413,17 +4417,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default mediapipe_face_processor
        * @enum {string}
        */
       type: "mediapipe_face_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Max Faces
        * @description Maximum number of faces to detect
@@ -4450,12 +4454,12 @@ export type components = {
     MetadataAccumulatorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4464,12 +4468,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default metadata_accumulator
-       * @enum {string}
-       */
-      type: "metadata_accumulator";
       /**
        * Generation Mode
        * @description The generation mode that output this image
@@ -4600,37 +4598,43 @@ export type components = {
        * @description The start value used for refiner denoising
        */
       refiner_start?: number;
+      /**
+       * Type
+       * @default metadata_accumulator
+       * @enum {string}
+       */
+      type: "metadata_accumulator";
     };
     /**
      * MetadataAccumulatorOutput
      * @description The output of the MetadataAccumulator node
      */
     MetadataAccumulatorOutput: {
+      /**
+       * Metadata
+       * @description The core metadata for the image
+       */
+      metadata: components["schemas"]["CoreMetadata"];
       /**
        * Type
        * @default metadata_accumulator_output
        * @enum {string}
        */
       type: "metadata_accumulator_output";
-      /**
-       * Metadata
-       * @description The core metadata for the image
-       */
-      metadata: components["schemas"]["CoreMetadata"];
     };
     /**
-     * Midas (Depth) Processor
+     * Midas Depth Processor
      * @description Applies Midas depth processing to image
      */
     MidasDepthImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4639,17 +4643,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default midas_depth_image_processor
        * @enum {string}
        */
       type: "midas_depth_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * A Mult
        * @description Midas parameter `a_mult` (a = a_mult * PI)
@@ -4670,12 +4674,12 @@ export type components = {
     MlsdImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4684,17 +4688,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default mlsd_image_processor
        * @enum {string}
        */
       type: "mlsd_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Detect Resolution
        * @description Pixel resolution for detection
@@ -4745,12 +4749,6 @@ export type components = {
      * @description Model loader output
      */
     ModelLoaderOutput: {
-      /**
-       * Type
-       * @default model_loader_output
-       * @enum {string}
-       */
-      type: "model_loader_output";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -4766,6 +4764,12 @@ export type components = {
        * @description VAE
        */
       vae: components["schemas"]["VaeField"];
+      /**
+       * Type
+       * @default model_loader_output
+       * @enum {string}
+       */
+      type: "model_loader_output";
     };
     /**
      * ModelType
@@ -4791,12 +4795,12 @@ export type components = {
     MultiplyInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4805,12 +4809,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default mul
-       * @enum {string}
-       */
-      type: "mul";
       /**
        * A
        * @description The first number
@@ -4823,6 +4821,12 @@ export type components = {
        * @default 0
        */
       b?: number;
+      /**
+       * Type
+       * @default mul
+       * @enum {string}
+       */
+      type: "mul";
     };
     /**
      * Noise
@@ -4831,12 +4835,12 @@ export type components = {
     NoiseInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4845,12 +4849,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default noise
-       * @enum {string}
-       */
-      type: "noise";
       /**
        * Seed
        * @description Seed for random number generation
@@ -4874,18 +4872,18 @@ export type components = {
        * @default true
        */
       use_cpu?: boolean;
+      /**
+       * Type
+       * @default noise
+       * @enum {string}
+       */
+      type: "noise";
     };
     /**
      * NoiseOutput
      * @description Invocation noise output
      */
     NoiseOutput: {
-      /**
-       * Type
-       * @default noise_output
-       * @enum {string}
-       */
-      type: "noise_output";
       /**
        * Noise
        * @description Noise tensor
@@ -4901,6 +4899,12 @@ export type components = {
        * @description Height of output (px)
        */
       height: number;
+      /**
+       * Type
+       * @default noise_output
+       * @enum {string}
+       */
+      type: "noise_output";
     };
     /**
      * Normal BAE Processor
@@ -4909,12 +4913,12 @@ export type components = {
     NormalbaeImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4923,17 +4927,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default normalbae_image_processor
        * @enum {string}
        */
       type: "normalbae_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Detect Resolution
        * @description Pixel resolution for detection
@@ -4954,12 +4958,12 @@ export type components = {
     ONNXLatentsToImageInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -4968,12 +4972,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default l2i_onnx
-       * @enum {string}
-       */
-      type: "l2i_onnx";
       /**
        * Latents
        * @description Denoised latents tensor
@@ -4989,18 +4987,18 @@ export type components = {
        * @description Optional core metadata to be written to image
        */
       metadata?: components["schemas"]["CoreMetadata"];
+      /**
+       * Type
+       * @default l2i_onnx
+       * @enum {string}
+       */
+      type: "l2i_onnx";
     };
     /**
      * ONNXModelLoaderOutput
      * @description Model loader output
      */
     ONNXModelLoaderOutput: {
-      /**
-       * Type
-       * @default model_loader_output_onnx
-       * @enum {string}
-       */
-      type: "model_loader_output_onnx";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -5021,21 +5019,29 @@ export type components = {
        * @description VAE
        */
       vae_encoder?: components["schemas"]["VaeField"];
+      /**
+       * Type
+       * @default model_loader_output_onnx
+       * @enum {string}
+       */
+      type: "model_loader_output_onnx";
     };
     /**
      * ONNX Prompt (Raw)
      * @description A node to process inputs and produce outputs.
      * May use dependency injection in __init__ to receive providers.
+     *
+     * All invocations must use the `@invocation` decorator to provide their unique type.
      */
     ONNXPromptInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5044,12 +5050,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default prompt_onnx
-       * @enum {string}
-       */
-      type: "prompt_onnx";
       /**
        * Prompt
        * @description Raw prompt text (no parsing)
@@ -5061,6 +5061,12 @@ export type components = {
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
        */
       clip?: components["schemas"]["ClipField"];
+      /**
+       * Type
+       * @default prompt_onnx
+       * @enum {string}
+       */
+      type: "prompt_onnx";
     };
     /** ONNXStableDiffusion1ModelConfig */
     ONNXStableDiffusion1ModelConfig: {
@@ -5116,12 +5122,12 @@ export type components = {
     ONNXTextToLatentsInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5130,12 +5136,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default t2l_onnx
-       * @enum {string}
-       */
-      type: "t2l_onnx";
       /**
        * Positive Conditioning
        * @description Positive conditioning tensor
@@ -5187,6 +5187,12 @@ export type components = {
        * @description ControlNet(s) to apply
        */
       control?: components["schemas"]["ControlField"] | components["schemas"]["ControlField"][];
+      /**
+       * Type
+       * @default t2l_onnx
+       * @enum {string}
+       */
+      type: "t2l_onnx";
     };
     /**
      * OffsetPaginatedResults[BoardDTO]
@@ -5262,12 +5268,12 @@ export type components = {
     OnnxModelLoaderInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5276,17 +5282,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Model
+       * @description ONNX Main model (UNet, VAE, CLIP) to load
+       */
+      model: components["schemas"]["OnnxModelField"];
       /**
        * Type
        * @default onnx_model_loader
        * @enum {string}
        */
       type: "onnx_model_loader";
-      /**
-       * Model
-       * @description ONNX Main model (UNet, VAE, CLIP) to load
-       */
-      model: components["schemas"]["OnnxModelField"];
     };
     /**
      * Openpose Processor
@@ -5295,12 +5301,12 @@ export type components = {
     OpenposeImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5309,17 +5315,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default openpose_image_processor
        * @enum {string}
        */
       type: "openpose_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Hand And Face
        * @description Whether to use hands and face mode
@@ -5377,12 +5383,12 @@ export type components = {
     PidiImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5391,17 +5397,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default pidi_image_processor
        * @enum {string}
        */
       type: "pidi_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Detect Resolution
        * @description Pixel resolution for detection
@@ -5434,12 +5440,12 @@ export type components = {
     PromptsFromFileInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5448,12 +5454,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default prompt_from_file
-       * @enum {string}
-       */
-      type: "prompt_from_file";
       /**
        * File Path
        * @description Path to prompt text file
@@ -5481,6 +5481,12 @@ export type components = {
        * @default 1
        */
       max_prompts?: number;
+      /**
+       * Type
+       * @default prompt_from_file
+       * @enum {string}
+       */
+      type: "prompt_from_file";
     };
     /**
      * Random Integer
@@ -5489,12 +5495,12 @@ export type components = {
     RandomIntInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5503,12 +5509,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default rand_int
-       * @enum {string}
-       */
-      type: "rand_int";
       /**
        * Low
        * @description The inclusive low value
@@ -5521,6 +5521,12 @@ export type components = {
        * @default 2147483647
        */
       high?: number;
+      /**
+       * Type
+       * @default rand_int
+       * @enum {string}
+       */
+      type: "rand_int";
     };
     /**
      * Random Range
@@ -5529,12 +5535,12 @@ export type components = {
     RandomRangeInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5543,12 +5549,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default random_range
-       * @enum {string}
-       */
-      type: "random_range";
       /**
        * Low
        * @description The inclusive low value
@@ -5572,6 +5572,12 @@ export type components = {
        * @description The seed for the RNG (omit for random)
        */
       seed?: number;
+      /**
+       * Type
+       * @default random_range
+       * @enum {string}
+       */
+      type: "random_range";
     };
     /**
      * Integer Range
@@ -5580,12 +5586,12 @@ export type components = {
     RangeInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5594,12 +5600,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default range
-       * @enum {string}
-       */
-      type: "range";
       /**
        * Start
        * @description The start of the range
@@ -5618,6 +5618,12 @@ export type components = {
        * @default 1
        */
       step?: number;
+      /**
+       * Type
+       * @default range
+       * @enum {string}
+       */
+      type: "range";
     };
     /**
      * Integer Range of Size
@@ -5626,12 +5632,12 @@ export type components = {
     RangeOfSizeInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5640,12 +5646,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default range_of_size
-       * @enum {string}
-       */
-      type: "range_of_size";
       /**
        * Start
        * @description The start of the range
@@ -5664,6 +5664,12 @@ export type components = {
        * @default 1
        */
       step?: number;
+      /**
+       * Type
+       * @default range_of_size
+       * @enum {string}
+       */
+      type: "range_of_size";
     };
     /** RemoveImagesFromBoardResult */
     RemoveImagesFromBoardResult: {
@@ -5680,12 +5686,12 @@ export type components = {
     ResizeLatentsInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5694,12 +5700,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default lresize
-       * @enum {string}
-       */
-      type: "lresize";
       /**
        * Latents
        * @description Latents tensor
@@ -5728,6 +5728,12 @@ export type components = {
        * @default false
        */
       antialias?: boolean;
+      /**
+       * Type
+       * @default lresize
+       * @enum {string}
+       */
+      type: "lresize";
     };
     /**
      * ResourceOrigin
@@ -5740,18 +5746,18 @@ export type components = {
      */
     ResourceOrigin: "internal" | "external";
     /**
-     * SDXL Compel Prompt
+     * SDXL Prompt
      * @description Parse prompt using compel package to conditioning.
      */
     SDXLCompelPromptInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5760,12 +5766,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default sdxl_compel_prompt
-       * @enum {string}
-       */
-      type: "sdxl_compel_prompt";
       /**
        * Prompt
        * @description Prompt to be parsed by Compel to create a conditioning tensor
@@ -5818,6 +5818,12 @@ export type components = {
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
        */
       clip2?: components["schemas"]["ClipField"];
+      /**
+       * Type
+       * @default sdxl_compel_prompt
+       * @enum {string}
+       */
+      type: "sdxl_compel_prompt";
     };
     /**
      * SDXL LoRA
@@ -5826,12 +5832,12 @@ export type components = {
     SDXLLoraLoaderInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5840,12 +5846,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default sdxl_lora_loader
-       * @enum {string}
-       */
-      type: "sdxl_lora_loader";
       /**
        * LoRA
        * @description LoRA model to load
@@ -5872,18 +5872,18 @@ export type components = {
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
        */
       clip2?: components["schemas"]["ClipField"];
+      /**
+       * Type
+       * @default sdxl_lora_loader
+       * @enum {string}
+       */
+      type: "sdxl_lora_loader";
     };
     /**
      * SDXLLoraLoaderOutput
      * @description SDXL LoRA Loader Output
      */
     SDXLLoraLoaderOutput: {
-      /**
-       * Type
-       * @default sdxl_lora_loader_output
-       * @enum {string}
-       */
-      type: "sdxl_lora_loader_output";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -5899,6 +5899,12 @@ export type components = {
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
        */
       clip2?: components["schemas"]["ClipField"];
+      /**
+       * Type
+       * @default sdxl_lora_loader_output
+       * @enum {string}
+       */
+      type: "sdxl_lora_loader_output";
     };
     /**
      * SDXL Main Model
@@ -5907,12 +5913,12 @@ export type components = {
     SDXLModelLoaderInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5921,29 +5927,23 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Model
+       * @description SDXL Main model (UNet, VAE, CLIP1, CLIP2) to load
+       */
+      model: components["schemas"]["MainModelField"];
       /**
        * Type
        * @default sdxl_model_loader
        * @enum {string}
        */
       type: "sdxl_model_loader";
-      /**
-       * Model
-       * @description SDXL Main model (UNet, VAE, CLIP1, CLIP2) to load
-       */
-      model: components["schemas"]["MainModelField"];
     };
     /**
      * SDXLModelLoaderOutput
      * @description SDXL base model loader output
      */
     SDXLModelLoaderOutput: {
-      /**
-       * Type
-       * @default sdxl_model_loader_output
-       * @enum {string}
-       */
-      type: "sdxl_model_loader_output";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -5964,20 +5964,26 @@ export type components = {
        * @description VAE
        */
       vae: components["schemas"]["VaeField"];
+      /**
+       * Type
+       * @default sdxl_model_loader_output
+       * @enum {string}
+       */
+      type: "sdxl_model_loader_output";
     };
     /**
-     * SDXL Refiner Compel Prompt
+     * SDXL Refiner Prompt
      * @description Parse prompt using compel package to conditioning.
      */
     SDXLRefinerCompelPromptInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -5986,12 +5992,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default sdxl_refiner_compel_prompt
-       * @enum {string}
-       */
-      type: "sdxl_refiner_compel_prompt";
       /**
        * Style
        * @description Prompt to be parsed by Compel to create a conditioning tensor
@@ -6029,6 +6029,12 @@ export type components = {
        * @description CLIP (tokenizer, text encoder, LoRAs) and skipped layer count
        */
       clip2?: components["schemas"]["ClipField"];
+      /**
+       * Type
+       * @default sdxl_refiner_compel_prompt
+       * @enum {string}
+       */
+      type: "sdxl_refiner_compel_prompt";
     };
     /**
      * SDXL Refiner Model
@@ -6037,12 +6043,12 @@ export type components = {
     SDXLRefinerModelLoaderInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6051,29 +6057,23 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Model
+       * @description SDXL Refiner Main Modde (UNet, VAE, CLIP2) to load
+       */
+      model: components["schemas"]["MainModelField"];
       /**
        * Type
        * @default sdxl_refiner_model_loader
        * @enum {string}
        */
       type: "sdxl_refiner_model_loader";
-      /**
-       * Model
-       * @description SDXL Refiner Main Modde (UNet, VAE, CLIP2) to load
-       */
-      model: components["schemas"]["MainModelField"];
     };
     /**
      * SDXLRefinerModelLoaderOutput
      * @description SDXL refiner model loader output
      */
     SDXLRefinerModelLoaderOutput: {
-      /**
-       * Type
-       * @default sdxl_refiner_model_loader_output
-       * @enum {string}
-       */
-      type: "sdxl_refiner_model_loader_output";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -6089,6 +6089,12 @@ export type components = {
        * @description VAE
        */
       vae: components["schemas"]["VaeField"];
+      /**
+       * Type
+       * @default sdxl_refiner_model_loader_output
+       * @enum {string}
+       */
+      type: "sdxl_refiner_model_loader_output";
     };
     /**
      * Scale Latents
@@ -6097,12 +6103,12 @@ export type components = {
     ScaleLatentsInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6111,12 +6117,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default lscale
-       * @enum {string}
-       */
-      type: "lscale";
       /**
        * Latents
        * @description Latents tensor
@@ -6140,6 +6140,12 @@ export type components = {
        * @default false
        */
       antialias?: boolean;
+      /**
+       * Type
+       * @default lscale
+       * @enum {string}
+       */
+      type: "lscale";
     };
     /**
      * SchedulerPredictionType
@@ -6154,12 +6160,12 @@ export type components = {
     SeamlessModeInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6168,12 +6174,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default seamless
-       * @enum {string}
-       */
-      type: "seamless";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -6196,18 +6196,18 @@ export type components = {
        * @default true
        */
       seamless_x?: boolean;
+      /**
+       * Type
+       * @default seamless
+       * @enum {string}
+       */
+      type: "seamless";
     };
     /**
      * SeamlessModeOutput
      * @description Modified Seamless Model output
      */
     SeamlessModeOutput: {
-      /**
-       * Type
-       * @default seamless_output
-       * @enum {string}
-       */
-      type: "seamless_output";
       /**
        * UNet
        * @description UNet (scheduler, LoRAs)
@@ -6218,6 +6218,12 @@ export type components = {
        * @description VAE
        */
       vae?: components["schemas"]["VaeField"];
+      /**
+       * Type
+       * @default seamless_output
+       * @enum {string}
+       */
+      type: "seamless_output";
     };
     /**
      * Segment Anything Processor
@@ -6226,12 +6232,12 @@ export type components = {
     SegmentAnythingProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6240,31 +6246,31 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default segment_anything_processor
        * @enum {string}
        */
       type: "segment_anything_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
     };
     /**
      * Show Image
-     * @description Displays a provided image, and passes it forward in the pipeline.
+     * @description Displays a provided image using the OS image viewer, and passes it forward in the pipeline.
      */
     ShowImageInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6273,17 +6279,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to show
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default show_image
        * @enum {string}
        */
       type: "show_image";
-      /**
-       * Image
-       * @description The image to show
-       */
-      image?: components["schemas"]["ImageField"];
     };
     /** StableDiffusion1ModelCheckpointConfig */
     StableDiffusion1ModelCheckpointConfig: {
@@ -6442,12 +6448,12 @@ export type components = {
     StepParamEasingInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6456,12 +6462,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default step_param_easing
-       * @enum {string}
-       */
-      type: "step_param_easing";
       /**
        * Easing
        * @description The easing function to use
@@ -6521,20 +6521,26 @@ export type components = {
        * @default false
        */
       show_easing_plot?: boolean;
+      /**
+       * Type
+       * @default step_param_easing
+       * @enum {string}
+       */
+      type: "step_param_easing";
     };
     /**
-     * String Primitive Collection
+     * String Collection Primitive
      * @description A collection of string primitive values
      */
     StringCollectionInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6543,34 +6549,34 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Collection
+       * @description The collection of string values
+       */
+      collection?: string[];
       /**
        * Type
        * @default string_collection
        * @enum {string}
        */
       type: "string_collection";
-      /**
-       * Collection
-       * @description The collection of string values
-       */
-      collection?: string[];
     };
     /**
      * StringCollectionOutput
      * @description Base class for nodes that output a collection of strings
      */
     StringCollectionOutput: {
+      /**
+       * Collection
+       * @description The output strings
+       */
+      collection: string[];
       /**
        * Type
        * @default string_collection_output
        * @enum {string}
        */
       type: "string_collection_output";
-      /**
-       * Collection
-       * @description The output strings
-       */
-      collection: string[];
     };
     /**
      * String Primitive
@@ -6579,12 +6585,12 @@ export type components = {
     StringInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6593,35 +6599,35 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default string
-       * @enum {string}
-       */
-      type: "string";
       /**
        * Value
        * @description The string value
        * @default
        */
       value?: string;
+      /**
+       * Type
+       * @default string
+       * @enum {string}
+       */
+      type: "string";
     };
     /**
      * StringOutput
      * @description Base class for nodes that output a single string
      */
     StringOutput: {
+      /**
+       * Value
+       * @description The output string
+       */
+      value: string;
       /**
        * Type
        * @default string_output
        * @enum {string}
        */
       type: "string_output";
-      /**
-       * Value
-       * @description The output string
-       */
-      value: string;
     };
     /**
      * SubModelType
@@ -6636,12 +6642,12 @@ export type components = {
     SubtractInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6650,12 +6656,6 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
-      /**
-       * Type
-       * @default sub
-       * @enum {string}
-       */
-      type: "sub";
       /**
        * A
        * @description The first number
@@ -6668,6 +6668,12 @@ export type components = {
        * @default 0
        */
       b?: number;
+      /**
+       * Type
+       * @default sub
+       * @enum {string}
+       */
+      type: "sub";
     };
     /** TextualInversionModelConfig */
     TextualInversionModelConfig: {
@@ -6694,12 +6700,12 @@ export type components = {
     TileResamplerProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6708,17 +6714,17 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default tile_image_processor
        * @enum {string}
        */
       type: "tile_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
       /**
        * Down Sampling Rate
        * @description Down sampling rate
@@ -6795,12 +6801,12 @@ export type components = {
     VaeLoaderInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6809,34 +6815,34 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * VAE
+       * @description VAE model to load
+       */
+      vae_model: components["schemas"]["VAEModelField"];
       /**
        * Type
        * @default vae_loader
        * @enum {string}
        */
       type: "vae_loader";
-      /**
-       * VAE
-       * @description VAE model to load
-       */
-      vae_model: components["schemas"]["VAEModelField"];
     };
     /**
      * VaeLoaderOutput
-     * @description Model loader output
+     * @description VAE output
      */
     VaeLoaderOutput: {
+      /**
+       * VAE
+       * @description VAE
+       */
+      vae: components["schemas"]["VaeField"];
       /**
        * Type
        * @default vae_loader_output
        * @enum {string}
        */
       type: "vae_loader_output";
-      /**
-       * VAE
-       * @description VAE
-       */
-      vae: components["schemas"]["VaeField"];
     };
     /** VaeModelConfig */
     VaeModelConfig: {
@@ -6877,12 +6883,12 @@ export type components = {
     ZoeDepthImageProcessorInvocation: {
       /**
        * Id
-       * @description The id of this node. Must be unique among all nodes.
+       * @description The id of this instance of an invocation. Must be unique among all instances of invocations.
        */
       id: string;
       /**
        * Is Intermediate
-       * @description Whether or not this node is an intermediate node.
+       * @description Whether or not this is an intermediate invocation.
        * @default false
        */
       is_intermediate?: boolean;
@@ -6891,35 +6897,39 @@ export type components = {
        * @description The workflow to save with the image
        */
       workflow?: string;
+      /**
+       * Image
+       * @description The image to process
+       */
+      image?: components["schemas"]["ImageField"];
       /**
        * Type
        * @default zoe_depth_image_processor
        * @enum {string}
        */
       type: "zoe_depth_image_processor";
-      /**
-       * Image
-       * @description The image to process
-       */
-      image?: components["schemas"]["ImageField"];
     };
     /**
      * UIConfigBase
      * @description Provides additional node configuration to the UI.
-     * This is used internally by the @tags and @title decorator logic. You probably want to use those
-     * decorators, though you may add this class to a node definition to specify the title and tags.
+     * This is used internally by the @invocation decorator logic. Do not use this directly.
      */
     UIConfigBase: {
       /**
        * Tags
-       * @description The tags to display in the UI
+       * @description The node's tags
        */
       tags?: string[];
       /**
        * Title
-       * @description The display name of the node
+       * @description The node's display name
        */
       title?: string;
+      /**
+       * Category
+       * @description The node's category
+       */
+      category?: string;
     };
     /**
      * Input
@@ -6974,23 +6984,17 @@ export type components = {
       ui_order?: number;
     };
     /**
-     * StableDiffusion2ModelFormat
+     * StableDiffusion1ModelFormat
      * @description An enumeration.
      * @enum {string}
      */
-    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
+    StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
     /**
      * ControlNetModelFormat
      * @description An enumeration.
      * @enum {string}
      */
     ControlNetModelFormat: "checkpoint" | "diffusers";
-    /**
-     * StableDiffusion1ModelFormat
-     * @description An enumeration.
-     * @enum {string}
-     */
-    StableDiffusion1ModelFormat: "checkpoint" | "diffusers";
     /**
      * StableDiffusionOnnxModelFormat
      * @description An enumeration.
@@ -7003,6 +7007,12 @@ export type components = {
      * @enum {string}
      */
     StableDiffusionXLModelFormat: "checkpoint" | "diffusers";
+    /**
+     * StableDiffusion2ModelFormat
+     * @description An enumeration.
+     * @enum {string}
+     */
+    StableDiffusion2ModelFormat: "checkpoint" | "diffusers";
   };
   responses: never;
   parameters: never;
@@ -7119,7 +7129,7 @@ export type operations = {
     };
     requestBody: {
       content: {
-        "application/json": components["schemas"]["BooleanInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageLuminosityAdjustmentInvocation"] | components["schemas"]["ImageSaturationAdjustmentInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ONNXPromptInvocation"] | components["schemas"]["ONNXTextToLatentsInvocation"] | components["schemas"]["ONNXLatentsToImageInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"];
+        "application/json": components["schemas"]["BooleanInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["ONNXPromptInvocation"] | components["schemas"]["ONNXTextToLatentsInvocation"] | components["schemas"]["ONNXLatentsToImageInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageLuminosityAdjustmentInvocation"] | components["schemas"]["ImageSaturationAdjustmentInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"];
       };
     };
     responses: {
@@ -7160,7 +7170,7 @@ export type operations = {
     };
     requestBody: {
       content: {
-        "application/json": components["schemas"]["BooleanInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageLuminosityAdjustmentInvocation"] | components["schemas"]["ImageSaturationAdjustmentInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["ONNXPromptInvocation"] | components["schemas"]["ONNXTextToLatentsInvocation"] | components["schemas"]["ONNXLatentsToImageInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"];
+        "application/json": components["schemas"]["BooleanInvocation"] | components["schemas"]["BooleanCollectionInvocation"] | components["schemas"]["IntegerInvocation"] | components["schemas"]["IntegerCollectionInvocation"] | components["schemas"]["FloatInvocation"] | components["schemas"]["FloatCollectionInvocation"] | components["schemas"]["StringInvocation"] | components["schemas"]["StringCollectionInvocation"] | components["schemas"]["ImageInvocation"] | components["schemas"]["ImageCollectionInvocation"] | components["schemas"]["LatentsInvocation"] | components["schemas"]["LatentsCollectionInvocation"] | components["schemas"]["ColorInvocation"] | components["schemas"]["ConditioningInvocation"] | components["schemas"]["ConditioningCollectionInvocation"] | components["schemas"]["ControlNetInvocation"] | components["schemas"]["ImageProcessorInvocation"] | components["schemas"]["MainModelLoaderInvocation"] | components["schemas"]["LoraLoaderInvocation"] | components["schemas"]["SDXLLoraLoaderInvocation"] | components["schemas"]["VaeLoaderInvocation"] | components["schemas"]["SeamlessModeInvocation"] | components["schemas"]["MetadataAccumulatorInvocation"] | components["schemas"]["SDXLModelLoaderInvocation"] | components["schemas"]["SDXLRefinerModelLoaderInvocation"] | components["schemas"]["CompelInvocation"] | components["schemas"]["SDXLCompelPromptInvocation"] | components["schemas"]["SDXLRefinerCompelPromptInvocation"] | components["schemas"]["ClipSkipInvocation"] | components["schemas"]["CreateDenoiseMaskInvocation"] | components["schemas"]["DenoiseLatentsInvocation"] | components["schemas"]["LatentsToImageInvocation"] | components["schemas"]["ResizeLatentsInvocation"] | components["schemas"]["ScaleLatentsInvocation"] | components["schemas"]["ImageToLatentsInvocation"] | components["schemas"]["BlendLatentsInvocation"] | components["schemas"]["ONNXPromptInvocation"] | components["schemas"]["ONNXTextToLatentsInvocation"] | components["schemas"]["ONNXLatentsToImageInvocation"] | components["schemas"]["OnnxModelLoaderInvocation"] | components["schemas"]["ShowImageInvocation"] | components["schemas"]["BlankImageInvocation"] | components["schemas"]["ImageCropInvocation"] | components["schemas"]["ImagePasteInvocation"] | components["schemas"]["MaskFromAlphaInvocation"] | components["schemas"]["ImageMultiplyInvocation"] | components["schemas"]["ImageChannelInvocation"] | components["schemas"]["ImageConvertInvocation"] | components["schemas"]["ImageBlurInvocation"] | components["schemas"]["ImageResizeInvocation"] | components["schemas"]["ImageScaleInvocation"] | components["schemas"]["ImageLerpInvocation"] | components["schemas"]["ImageInverseLerpInvocation"] | components["schemas"]["ImageNSFWBlurInvocation"] | components["schemas"]["ImageWatermarkInvocation"] | components["schemas"]["MaskEdgeInvocation"] | components["schemas"]["MaskCombineInvocation"] | components["schemas"]["ColorCorrectInvocation"] | components["schemas"]["ImageHueAdjustmentInvocation"] | components["schemas"]["ImageLuminosityAdjustmentInvocation"] | components["schemas"]["ImageSaturationAdjustmentInvocation"] | components["schemas"]["DynamicPromptInvocation"] | components["schemas"]["PromptsFromFileInvocation"] | components["schemas"]["CvInpaintInvocation"] | components["schemas"]["FloatLinearRangeInvocation"] | components["schemas"]["StepParamEasingInvocation"] | components["schemas"]["AddInvocation"] | components["schemas"]["SubtractInvocation"] | components["schemas"]["MultiplyInvocation"] | components["schemas"]["DivideInvocation"] | components["schemas"]["RandomIntInvocation"] | components["schemas"]["NoiseInvocation"] | components["schemas"]["RangeInvocation"] | components["schemas"]["RangeOfSizeInvocation"] | components["schemas"]["RandomRangeInvocation"] | components["schemas"]["ESRGANInvocation"] | components["schemas"]["InfillColorInvocation"] | components["schemas"]["InfillTileInvocation"] | components["schemas"]["InfillPatchMatchInvocation"] | components["schemas"]["LaMaInfillInvocation"] | components["schemas"]["GraphInvocation"] | components["schemas"]["IterateInvocation"] | components["schemas"]["CollectInvocation"] | components["schemas"]["CannyImageProcessorInvocation"] | components["schemas"]["HedImageProcessorInvocation"] | components["schemas"]["LineartImageProcessorInvocation"] | components["schemas"]["LineartAnimeImageProcessorInvocation"] | components["schemas"]["OpenposeImageProcessorInvocation"] | components["schemas"]["MidasDepthImageProcessorInvocation"] | components["schemas"]["NormalbaeImageProcessorInvocation"] | components["schemas"]["MlsdImageProcessorInvocation"] | components["schemas"]["PidiImageProcessorInvocation"] | components["schemas"]["ContentShuffleImageProcessorInvocation"] | components["schemas"]["ZoeDepthImageProcessorInvocation"] | components["schemas"]["MediapipeFaceProcessorInvocation"] | components["schemas"]["LeresImageProcessorInvocation"] | components["schemas"]["TileResamplerProcessorInvocation"] | components["schemas"]["SegmentAnythingProcessorInvocation"];
       };
     };
     responses: {
diff --git a/tests/nodes/test_nodes.py b/tests/nodes/test_nodes.py
index 92faa6a0ba..26b8b2b565 100644
--- a/tests/nodes/test_nodes.py
+++ b/tests/nodes/test_nodes.py
@@ -1,65 +1,63 @@
-from typing import Any, Callable, Literal, Union
+from typing import Any, Callable, Union
 from pydantic import Field
-from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
+from invokeai.app.invocations.baseinvocation import (
+    BaseInvocation,
+    BaseInvocationOutput,
+    InvocationContext,
+    invocation,
+    invocation_output,
+)
 from invokeai.app.invocations.image import ImageField
 
 
 # Define test invocations before importing anything that uses invocations
+@invocation_output("test_list_output")
 class ListPassThroughInvocationOutput(BaseInvocationOutput):
-    type: Literal["test_list_output"] = "test_list_output"
-
     collection: list[ImageField] = Field(default_factory=list)
 
 
+@invocation("test_list")
 class ListPassThroughInvocation(BaseInvocation):
-    type: Literal["test_list"] = "test_list"
-
     collection: list[ImageField] = Field(default_factory=list)
 
     def invoke(self, context: InvocationContext) -> ListPassThroughInvocationOutput:
         return ListPassThroughInvocationOutput(collection=self.collection)
 
 
+@invocation_output("test_prompt_output")
 class PromptTestInvocationOutput(BaseInvocationOutput):
-    type: Literal["test_prompt_output"] = "test_prompt_output"
-
     prompt: str = Field(default="")
 
 
+@invocation("test_prompt")
 class PromptTestInvocation(BaseInvocation):
-    type: Literal["test_prompt"] = "test_prompt"
-
     prompt: str = Field(default="")
 
     def invoke(self, context: InvocationContext) -> PromptTestInvocationOutput:
         return PromptTestInvocationOutput(prompt=self.prompt)
 
 
+@invocation("test_error")
 class ErrorInvocation(BaseInvocation):
-    type: Literal["test_error"] = "test_error"
-
     def invoke(self, context: InvocationContext) -> PromptTestInvocationOutput:
         raise Exception("This invocation is supposed to fail")
 
 
+@invocation_output("test_image_output")
 class ImageTestInvocationOutput(BaseInvocationOutput):
-    type: Literal["test_image_output"] = "test_image_output"
-
     image: ImageField = Field()
 
 
+@invocation("test_text_to_image")
 class TextToImageTestInvocation(BaseInvocation):
-    type: Literal["test_text_to_image"] = "test_text_to_image"
-
     prompt: str = Field(default="")
 
     def invoke(self, context: InvocationContext) -> ImageTestInvocationOutput:
         return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
 
 
+@invocation("test_image_to_image")
 class ImageToImageTestInvocation(BaseInvocation):
-    type: Literal["test_image_to_image"] = "test_image_to_image"
-
     prompt: str = Field(default="")
     image: Union[ImageField, None] = Field(default=None)
 
@@ -67,13 +65,13 @@ class ImageToImageTestInvocation(BaseInvocation):
         return ImageTestInvocationOutput(image=ImageField(image_name=self.id))
 
 
+@invocation_output("test_prompt_collection_output")
 class PromptCollectionTestInvocationOutput(BaseInvocationOutput):
-    type: Literal["test_prompt_collection_output"] = "test_prompt_collection_output"
     collection: list[str] = Field(default_factory=list)
 
 
+@invocation("test_prompt_collection")
 class PromptCollectionTestInvocation(BaseInvocation):
-    type: Literal["test_prompt_collection"] = "test_prompt_collection"
     collection: list[str] = Field()
 
     def invoke(self, context: InvocationContext) -> PromptCollectionTestInvocationOutput: