mirror of
https://github.com/invoke-ai/InvokeAI.git
synced 2026-04-23 03:00:31 -04:00
feat(nodes): move invocation/output registration to separate class
This commit is contained in:
@@ -100,35 +100,6 @@ class BaseInvocationOutput(BaseModel):
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All invocation outputs must use the `@invocation_output` decorator to provide their unique type.
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"""
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_output_classes: ClassVar[set[BaseInvocationOutput]] = set()
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@classmethod
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def register_output(cls, output: BaseInvocationOutput) -> None:
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"""Registers an invocation output."""
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cls._output_classes.add(output)
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cls.get_typeadapter.cache_clear()
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@classmethod
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def get_outputs(cls) -> Iterable[BaseInvocationOutput]:
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"""Gets all invocation outputs."""
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return cls._output_classes
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@classmethod
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@lru_cache(maxsize=1)
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def get_typeadapter(cls) -> TypeAdapter[Any]:
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"""Gets a pydantic TypeAdapter for the union of all invocation output types.
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This method is cached to avoid rebuilding the TypeAdapter on every access. If the invocation allowlist or
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denylist is changed, the cache should be cleared to ensure the TypeAdapter is updated and validation respects
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the updated allowlist and denylist.
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"""
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return TypeAdapter(Annotated[Union[tuple(cls._output_classes)], Field(discriminator="type")])
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@classmethod
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def get_output_types(cls) -> Iterable[str]:
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"""Gets all invocation output types."""
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return (i.get_type() for i in BaseInvocationOutput.get_outputs())
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@staticmethod
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def json_schema_extra(schema: dict[str, Any], model_class: Type[BaseInvocationOutput]) -> None:
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"""Adds various UI-facing attributes to the invocation output's OpenAPI schema."""
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@@ -171,67 +142,16 @@ class BaseInvocation(ABC, BaseModel):
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All invocations must use the `@invocation` decorator to provide their unique type.
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"""
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_invocation_classes: ClassVar[set[BaseInvocation]] = set()
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@classmethod
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def get_type(cls) -> str:
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"""Gets the invocation's type, as provided by the `@invocation` decorator."""
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return cls.model_fields["type"].default
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@classmethod
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def register_invocation(cls, invocation: BaseInvocation) -> None:
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"""Registers an invocation."""
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cls._invocation_classes.add(invocation)
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cls.get_typeadapter.cache_clear()
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@classmethod
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@lru_cache(maxsize=1)
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def get_typeadapter(cls) -> TypeAdapter[Any]:
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"""Gets a pydantic TypeAdapter for the union of all invocation types.
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This method is cached to avoid rebuilding the TypeAdapter on every access. If the invocation allowlist or
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denylist is changed, the cache should be cleared to ensure the TypeAdapter is updated and validation respects
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the updated allowlist and denylist.
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"""
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return TypeAdapter(Annotated[Union[tuple(cls.get_invocations())], Field(discriminator="type")])
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@classmethod
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def get_invocations(cls) -> Iterable[BaseInvocation]:
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"""Gets all invocations, respecting the allowlist and denylist."""
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app_config = get_config()
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allowed_invocations: set[BaseInvocation] = set()
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for sc in cls._invocation_classes:
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invocation_type = sc.get_type()
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is_in_allowlist = (
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invocation_type in app_config.allow_nodes if isinstance(app_config.allow_nodes, list) else True
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)
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is_in_denylist = (
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invocation_type in app_config.deny_nodes if isinstance(app_config.deny_nodes, list) else False
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)
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if is_in_allowlist and not is_in_denylist:
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allowed_invocations.add(sc)
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return allowed_invocations
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@classmethod
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def get_invocations_map(cls) -> dict[str, BaseInvocation]:
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"""Gets a map of all invocation types to their invocation classes."""
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return {i.get_type(): i for i in BaseInvocation.get_invocations()}
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@classmethod
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def get_invocation_types(cls) -> Iterable[str]:
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"""Gets all invocation types."""
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return (i.get_type() for i in BaseInvocation.get_invocations())
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@classmethod
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def get_output_annotation(cls) -> BaseInvocationOutput:
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"""Gets the invocation's output annotation (i.e. the return annotation of its `invoke()` method)."""
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return signature(cls.invoke).return_annotation
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@classmethod
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def get_invocation_for_type(cls, invocation_type: str) -> BaseInvocation | None:
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"""Gets the invocation class for a given invocation type."""
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return cls.get_invocations_map().get(invocation_type)
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@staticmethod
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def json_schema_extra(schema: dict[str, Any], model_class: Type[BaseInvocation]) -> None:
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"""Adds various UI-facing attributes to the invocation's OpenAPI schema."""
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@@ -329,6 +249,87 @@ class BaseInvocation(ABC, BaseModel):
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TBaseInvocation = TypeVar("TBaseInvocation", bound=BaseInvocation)
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class InvocationRegistry:
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_invocation_classes: ClassVar[set[type[BaseInvocation]]] = set()
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_output_classes: ClassVar[set[type[BaseInvocationOutput]]] = set()
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@classmethod
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def register_invocation(cls, invocation: type[BaseInvocation]) -> None:
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"""Registers an invocation."""
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cls._invocation_classes.add(invocation)
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cls.get_invocation_typeadapter.cache_clear()
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@classmethod
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@lru_cache(maxsize=1)
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def get_invocation_typeadapter(cls) -> TypeAdapter[Any]:
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"""Gets a pydantic TypeAdapter for the union of all invocation types.
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This method is cached to avoid rebuilding the TypeAdapter on every access. If the invocation allowlist or
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denylist is changed, the cache should be cleared to ensure the TypeAdapter is updated and validation respects
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the updated allowlist and denylist.
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"""
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return TypeAdapter(Annotated[Union[tuple(cls.get_invocation_classes())], Field(discriminator="type")])
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@classmethod
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def get_invocation_classes(cls) -> Iterable[type[BaseInvocation]]:
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"""Gets all invocations, respecting the allowlist and denylist."""
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app_config = get_config()
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allowed_invocations: set[type[BaseInvocation]] = set()
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for sc in cls._invocation_classes:
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invocation_type = sc.get_type()
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is_in_allowlist = (
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invocation_type in app_config.allow_nodes if isinstance(app_config.allow_nodes, list) else True
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)
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is_in_denylist = (
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invocation_type in app_config.deny_nodes if isinstance(app_config.deny_nodes, list) else False
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)
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if is_in_allowlist and not is_in_denylist:
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allowed_invocations.add(sc)
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return allowed_invocations
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@classmethod
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def get_invocations_map(cls) -> dict[str, type[BaseInvocation]]:
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"""Gets a map of all invocation types to their invocation classes."""
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return {i.get_type(): i for i in cls.get_invocation_classes()}
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@classmethod
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def get_invocation_types(cls) -> Iterable[str]:
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"""Gets all invocation types."""
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return (i.get_type() for i in cls.get_invocation_classes())
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@classmethod
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def get_invocation_for_type(cls, invocation_type: str) -> type[BaseInvocation] | None:
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"""Gets the invocation class for a given invocation type."""
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return cls.get_invocations_map().get(invocation_type)
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@classmethod
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def register_output(cls, output: "type[TBaseInvocationOutput]") -> None:
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"""Registers an invocation output."""
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cls._output_classes.add(output)
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cls.get_output_typeadapter.cache_clear()
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@classmethod
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def get_output_classes(cls) -> Iterable[type[BaseInvocationOutput]]:
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"""Gets all invocation outputs."""
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return cls._output_classes
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@classmethod
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@lru_cache(maxsize=1)
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def get_output_typeadapter(cls) -> TypeAdapter[Any]:
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"""Gets a pydantic TypeAdapter for the union of all invocation output types.
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This method is cached to avoid rebuilding the TypeAdapter on every access. If the invocation allowlist or
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denylist is changed, the cache should be cleared to ensure the TypeAdapter is updated and validation respects
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the updated allowlist and denylist.
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"""
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return TypeAdapter(Annotated[Union[tuple(cls._output_classes)], Field(discriminator="type")])
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@classmethod
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def get_output_types(cls) -> Iterable[str]:
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"""Gets all invocation output types."""
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return (i.get_type() for i in cls.get_output_classes())
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RESERVED_NODE_ATTRIBUTE_FIELD_NAMES = {
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"id",
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"is_intermediate",
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@@ -442,8 +443,8 @@ def invocation(
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node_pack = cls.__module__.split(".")[0]
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# Handle the case where an existing node is being clobbered by the one we are registering
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if invocation_type in BaseInvocation.get_invocation_types():
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clobbered_invocation = BaseInvocation.get_invocation_for_type(invocation_type)
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if invocation_type in InvocationRegistry.get_invocation_types():
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clobbered_invocation = InvocationRegistry.get_invocation_for_type(invocation_type)
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# This should always be true - we just checked if the invocation type was in the set
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assert clobbered_invocation is not None
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@@ -528,8 +529,7 @@ def invocation(
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)
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cls.__doc__ = docstring
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# TODO: how to type this correctly? it's typed as ModelMetaclass, a private class in pydantic
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BaseInvocation.register_invocation(cls) # type: ignore
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InvocationRegistry.register_invocation(cls)
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return cls
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@@ -554,7 +554,7 @@ def invocation_output(
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if re.compile(r"^\S+$").match(output_type) is None:
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raise ValueError(f'"output_type" must consist of non-whitespace characters, got "{output_type}"')
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if output_type in BaseInvocationOutput.get_output_types():
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if output_type in InvocationRegistry.get_output_types():
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raise ValueError(f'Invocation type "{output_type}" already exists')
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validate_fields(cls.model_fields, output_type)
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@@ -575,7 +575,7 @@ def invocation_output(
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)
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cls.__doc__ = docstring
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BaseInvocationOutput.register_output(cls) # type: ignore # TODO: how to type this correctly?
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InvocationRegistry.register_output(cls)
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return cls
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@@ -21,6 +21,7 @@ from invokeai.app.invocations import * # noqa: F401 F403
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from invokeai.app.invocations.baseinvocation import (
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BaseInvocation,
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BaseInvocationOutput,
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InvocationRegistry,
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invocation,
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invocation_output,
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)
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@@ -283,7 +284,7 @@ class AnyInvocation(BaseInvocation):
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@classmethod
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def __get_pydantic_core_schema__(cls, source_type: Any, handler: GetCoreSchemaHandler) -> core_schema.CoreSchema:
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def validate_invocation(v: Any) -> "AnyInvocation":
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return BaseInvocation.get_typeadapter().validate_python(v)
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return InvocationRegistry.get_invocation_typeadapter().validate_python(v)
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return core_schema.no_info_plain_validator_function(validate_invocation)
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@@ -294,7 +295,7 @@ class AnyInvocation(BaseInvocation):
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# Nodes are too powerful, we have to make our own OpenAPI schema manually
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# No but really, because the schema is dynamic depending on loaded nodes, we need to generate it manually
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oneOf: list[dict[str, str]] = []
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names = [i.__name__ for i in BaseInvocation.get_invocations()]
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names = [i.__name__ for i in InvocationRegistry.get_invocation_classes()]
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for name in sorted(names):
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oneOf.append({"$ref": f"#/components/schemas/{name}"})
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return {"oneOf": oneOf}
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@@ -304,7 +305,7 @@ class AnyInvocationOutput(BaseInvocationOutput):
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@classmethod
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def __get_pydantic_core_schema__(cls, source_type: Any, handler: GetCoreSchemaHandler):
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def validate_invocation_output(v: Any) -> "AnyInvocationOutput":
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return BaseInvocationOutput.get_typeadapter().validate_python(v)
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return InvocationRegistry.get_output_typeadapter().validate_python(v)
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return core_schema.no_info_plain_validator_function(validate_invocation_output)
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@@ -316,7 +317,7 @@ class AnyInvocationOutput(BaseInvocationOutput):
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# No but really, because the schema is dynamic depending on loaded nodes, we need to generate it manually
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oneOf: list[dict[str, str]] = []
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names = [i.__name__ for i in BaseInvocationOutput.get_outputs()]
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names = [i.__name__ for i in InvocationRegistry.get_output_classes()]
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for name in sorted(names):
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oneOf.append({"$ref": f"#/components/schemas/{name}"})
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return {"oneOf": oneOf}
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@@ -4,7 +4,10 @@ from fastapi import FastAPI
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from fastapi.openapi.utils import get_openapi
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from pydantic.json_schema import models_json_schema
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from invokeai.app.invocations.baseinvocation import BaseInvocation, BaseInvocationOutput, UIConfigBase
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from invokeai.app.invocations.baseinvocation import (
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InvocationRegistry,
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UIConfigBase,
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)
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from invokeai.app.invocations.fields import InputFieldJSONSchemaExtra, OutputFieldJSONSchemaExtra
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from invokeai.app.invocations.model import ModelIdentifierField
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from invokeai.app.services.events.events_common import EventBase
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@@ -56,14 +59,14 @@ def get_openapi_func(
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invocation_output_map_required: list[str] = []
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# We need to manually add all outputs to the schema - pydantic doesn't add them because they aren't used directly.
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for output in BaseInvocationOutput.get_outputs():
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for output in InvocationRegistry.get_output_classes():
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json_schema = output.model_json_schema(mode="serialization", ref_template="#/components/schemas/{model}")
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move_defs_to_top_level(openapi_schema, json_schema)
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openapi_schema["components"]["schemas"][output.__name__] = json_schema
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# Technically, invocations are added to the schema by pydantic, but we still need to manually set their output
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# property, so we'll just do it all manually.
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for invocation in BaseInvocation.get_invocations():
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for invocation in InvocationRegistry.get_invocation_classes():
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json_schema = invocation.model_json_schema(
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mode="serialization", ref_template="#/components/schemas/{model}"
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)
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@@ -5,7 +5,7 @@ from typing import Any
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import pytest
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from pydantic import ValidationError
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from invokeai.app.invocations.baseinvocation import BaseInvocation
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from invokeai.app.invocations.baseinvocation import InvocationRegistry
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from invokeai.app.services.config.config_default import (
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DefaultInvokeAIAppConfig,
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InvokeAIAppConfig,
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@@ -274,7 +274,7 @@ def test_deny_nodes(patch_rootdir):
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# We've changed the config, we need to invalidate the typeadapter cache so that the new config is used for
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# subsequent graph validations
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BaseInvocation.get_typeadapter.cache_clear()
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InvocationRegistry.get_invocation_typeadapter.cache_clear()
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# confirm graph validation fails when using denied node
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Graph.model_validate({"nodes": {"1": {"id": "1", "type": "integer"}}})
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@@ -284,7 +284,7 @@ def test_deny_nodes(patch_rootdir):
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Graph.model_validate({"nodes": {"1": {"id": "1", "type": "float"}}})
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# confirm invocations union will not have denied nodes
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all_invocations = BaseInvocation.get_invocations()
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all_invocations = InvocationRegistry.get_invocation_classes()
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has_integer = len([i for i in all_invocations if i.get_type() == "integer"]) == 1
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has_string = len([i for i in all_invocations if i.get_type() == "string"]) == 1
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@@ -296,4 +296,4 @@ def test_deny_nodes(patch_rootdir):
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# Reset the config so that it doesn't affect other tests
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get_config.cache_clear()
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BaseInvocation.get_typeadapter.cache_clear()
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InvocationRegistry.get_invocation_typeadapter.cache_clear()
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