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docs(nodes): update INVOCATIONS.md (#3511)
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@ -19,31 +19,56 @@ An invocation looks like this:
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```py
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class UpscaleInvocation(BaseInvocation):
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"""Upscales an image."""
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type: Literal['upscale'] = 'upscale'
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# fmt: off
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type: Literal["upscale"] = "upscale"
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# Inputs
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image: Union[ImageField,None] = Field(description="The input image")
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strength: float = Field(default=0.75, gt=0, le=1, description="The strength")
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level: Literal[2,4] = Field(default=2, description = "The upscale level")
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image: Union[ImageField, None] = Field(description="The input image", default=None)
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strength: float = Field(default=0.75, gt=0, le=1, description="The strength")
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level: Literal[2, 4] = Field(default=2, description="The upscale level")
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# fmt: on
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# Schema customisation
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class Config(InvocationConfig):
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schema_extra = {
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"ui": {
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"tags": ["upscaling", "image"],
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},
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}
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get(self.image.image_type, self.image.image_name)
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results = context.services.generate.upscale_and_reconstruct(
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image_list = [[image, 0]],
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upscale = (self.level, self.strength),
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strength = 0.0, # GFPGAN strength
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save_original = False,
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image_callback = None,
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image = context.services.images.get_pil_image(
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self.image.image_origin, self.image.image_name
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)
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results = context.services.restoration.upscale_and_reconstruct(
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image_list=[[image, 0]],
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upscale=(self.level, self.strength),
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strength=0.0, # GFPGAN strength
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save_original=False,
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image_callback=None,
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)
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# Results are image and seed, unwrap for now
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# TODO: can this return multiple results?
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image_type = ImageType.RESULT
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image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
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context.services.images.save(image_type, image_name, results[0][0])
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return ImageOutput(
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image = ImageField(image_type = image_type, image_name = image_name)
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image_dto = context.services.images.create(
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image=results[0][0],
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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session_id=context.graph_execution_state_id,
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is_intermediate=self.is_intermediate,
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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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image_origin=image_dto.image_origin,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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```
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Each portion is important to implement correctly.
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@ -95,25 +120,67 @@ Finally, note that for all linking, the `type` of the linked fields must match.
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If the `name` also matches, then the field can be **automatically linked** to a
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previous invocation by name and matching.
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### Config
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```py
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# Schema customisation
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class Config(InvocationConfig):
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schema_extra = {
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"ui": {
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"tags": ["upscaling", "image"],
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},
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}
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```
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This is an optional configuration for the invocation. It inherits from
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pydantic's model `Config` class, and it used primarily to customize the
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autogenerated OpenAPI schema.
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The UI relies on the OpenAPI schema in two ways:
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- An API client & Typescript types are generated from it. This happens at build
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time.
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- The node editor parses the schema into a template used by the UI to create the
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node editor UI. This parsing happens at runtime.
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In this example, a `ui` key has been added to the `schema_extra` dict to provide
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some tags for the UI, to facilitate filtering nodes.
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See the Schema Generation section below for more information.
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### Invoke Function
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```py
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get(self.image.image_type, self.image.image_name)
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results = context.services.generate.upscale_and_reconstruct(
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image_list = [[image, 0]],
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upscale = (self.level, self.strength),
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strength = 0.0, # GFPGAN strength
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save_original = False,
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image_callback = None,
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image = context.services.images.get_pil_image(
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self.image.image_origin, self.image.image_name
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)
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results = context.services.restoration.upscale_and_reconstruct(
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image_list=[[image, 0]],
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upscale=(self.level, self.strength),
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strength=0.0, # GFPGAN strength
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save_original=False,
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image_callback=None,
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)
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# Results are image and seed, unwrap for now
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image_type = ImageType.RESULT
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image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
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context.services.images.save(image_type, image_name, results[0][0])
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# TODO: can this return multiple results?
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image_dto = context.services.images.create(
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image=results[0][0],
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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session_id=context.graph_execution_state_id,
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is_intermediate=self.is_intermediate,
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)
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return ImageOutput(
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image = ImageField(image_type = image_type, image_name = image_name)
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image=ImageField(
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image_name=image_dto.image_name,
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image_origin=image_dto.image_origin,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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```
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@ -135,9 +202,16 @@ scenarios. If you need functionality, please provide it as a service in the
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```py
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class ImageOutput(BaseInvocationOutput):
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"""Base class for invocations that output an image"""
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type: Literal['image'] = 'image'
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image: ImageField = Field(default=None, description="The output image")
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# fmt: off
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type: Literal["image_output"] = "image_output"
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image: ImageField = Field(default=None, description="The output image")
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width: int = Field(description="The width of the image in pixels")
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height: int = Field(description="The height of the image in pixels")
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# fmt: on
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class Config:
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schema_extra = {"required": ["type", "image", "width", "height"]}
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```
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Output classes look like an invocation class without the invoke method. Prefer
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@ -168,35 +242,36 @@ Here's that `ImageOutput` class, without the needed schema customisation:
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class ImageOutput(BaseInvocationOutput):
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"""Base class for invocations that output an image"""
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type: Literal["image"] = "image"
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# fmt: off
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type: Literal["image_output"] = "image_output"
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image: ImageField = Field(default=None, description="The output image")
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width: int = Field(description="The width of the image in pixels")
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height: int = Field(description="The height of the image in pixels")
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# fmt: on
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```
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The generated OpenAPI schema, and all clients/types generated from it, will have
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the `type` and `image` properties marked as optional, even though we know they
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will always have a value by the time we can interact with them via the API.
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Here's the same class, but with the schema customisation added:
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The OpenAPI schema that results from this `ImageOutput` will have the `type`,
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`image`, `width` and `height` properties marked as optional, even though we know
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they will always have a value.
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```python
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class ImageOutput(BaseInvocationOutput):
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"""Base class for invocations that output an image"""
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type: Literal["image"] = "image"
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# fmt: off
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type: Literal["image_output"] = "image_output"
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image: ImageField = Field(default=None, description="The output image")
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width: int = Field(description="The width of the image in pixels")
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height: int = Field(description="The height of the image in pixels")
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# fmt: on
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# Add schema customization
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class Config:
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schema_extra = {
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'required': [
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'type',
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'image',
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]
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}
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schema_extra = {"required": ["type", "image", "width", "height"]}
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```
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The resultant schema (and any API client or types generated from it) will now
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have see `type` as string literal `"image"` and `image` as an `ImageField`
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object.
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With the customization in place, the schema will now show these properties as
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required, obviating the need for extensive null checks in client code.
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See this `pydantic` issue for discussion on this solution:
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<https://github.com/pydantic/pydantic/discussions/4577>
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