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@ -29,14 +29,7 @@ from langchain.callbacks.manager import (
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)
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from langchain.load.serializable import Serializable
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from pydantic import (
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BaseModel,
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Extra,
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Field,
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create_model,
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root_validator,
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validate_arguments,
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)
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from langchain.schema.runnable import (
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Runnable,
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RunnableConfig,
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@ -48,62 +41,9 @@ class SchemaAnnotationError(TypeError):
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"""Raised when 'args_schema' is missing or has an incorrect type annotation."""
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def _create_subset_model(
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name: str, model: BaseModel, field_names: list
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) -> Type[BaseModel]:
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"""Create a pydantic model with only a subset of model's fields."""
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fields = {}
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for field_name in field_names:
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field = model.__fields__[field_name]
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fields[field_name] = (field.outer_type_, field.field_info)
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return create_model(name, **fields) # type: ignore
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def _get_filtered_args(
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inferred_model: Type[BaseModel],
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func: Callable,
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) -> dict:
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"""Get the arguments from a function's signature."""
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schema = inferred_model.schema()["properties"]
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valid_keys = signature(func).parameters
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return {
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k: schema[k]
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for k in valid_keys
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if k not in ("run_manager", "callbacks")
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}
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class _SchemaConfig:
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"""Configuration for the pydantic model."""
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extra: Any = Extra.forbid
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arbitrary_types_allowed: bool = True
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def create_schema_from_function(
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model_name: str,
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func: Callable,
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) -> Type[BaseModel]:
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"""Create a pydantic schema from a function's signature.
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Args:
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model_name: Name to assign to the generated pydandic schema
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func: Function to generate the schema from
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Returns:
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A pydantic model with the same arguments as the function
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"""
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# https://docs.pydantic.dev/latest/usage/validation_decorator/
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validated = validate_arguments(func, config=_SchemaConfig) # type: ignore
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inferred_model = validated.model # type: ignore
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if "run_manager" in inferred_model.__fields__:
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del inferred_model.__fields__["run_manager"]
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if "callbacks" in inferred_model.__fields__:
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del inferred_model.__fields__["callbacks"]
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# Pydantic adds placeholder virtual fields we need to strip
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valid_properties = _get_filtered_args(inferred_model, func)
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return _create_subset_model(
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f"{model_name}Schema", inferred_model, list(valid_properties)
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)
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class ToolException(Exception):
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"""An optional exception that tool throws when execution error occurs.
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@ -131,7 +71,7 @@ class BaseTool(RunnableSerializable[Union[str, Dict], Any]):
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if args_schema_type is not None:
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if (
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args_schema_type is None
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or args_schema_type == BaseModel
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# or args_schema_type == BaseModel
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):
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# Throw errors for common mis-annotations.
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# TODO: Use get_args / get_origin and fully
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@ -168,11 +108,10 @@ class ChildTool(BaseTool):
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verbose: bool = False
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"""Whether to log the tool's progress."""
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callbacks: Callbacks = Field(default=None, exclude=True)
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callbacks: Callbacks = None
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"""Callbacks to be called during tool execution."""
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callback_manager: Optional[BaseCallbackManager] = Field(
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default=None, exclude=True
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)
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# TODO: I don't know how to remove Field here
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callback_manager: Optional[BaseCallbackManager] = None
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"""Deprecated. Please use callbacks instead."""
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tags: Optional[List[str]] = None
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"""Optional list of tags associated with the tool. Defaults to None
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@ -192,9 +131,11 @@ class ChildTool(BaseTool):
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] = False
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"""Handle the content of the ToolException thrown."""
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# TODO[pydantic]: The `Config` class inherits from another class, please create the `model_config` manually.
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# Check https://docs.pydantic.dev/dev-v2/migration/#changes-to-config for more information.
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class Config(Serializable.Config):
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"""Configuration for this pydantic object."""
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model_config = {}
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arbitrary_types_allowed = True
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@property
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@ -214,7 +155,8 @@ class ChildTool(BaseTool):
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# --- Runnable ---
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@property
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def input_schema(self) -> Type[BaseModel]:
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# TODO
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def input_schema(self):
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"""The tool's input schema."""
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if self.args_schema is not None:
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return self.args_schema
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@ -276,7 +218,7 @@ class ChildTool(BaseTool):
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}
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return tool_input
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@root_validator()
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@classmethod
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def raise_deprecation(cls, values: Dict) -> Dict:
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"""Raise deprecation warning if callback_manager is used."""
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if values.get("callback_manager") is not None:
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@ -671,9 +613,7 @@ class StructuredTool(BaseTool):
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"""Tool that can operate on any number of inputs."""
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description: str = ""
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args_schema: Type[BaseModel] = Field(
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..., description="The tool schema."
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)
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"""The input arguments' schema."""
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func: Optional[Callable[..., Any]]
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"""The function to run when the tool is called."""
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Eternal Reclaimer
1 year ago
committed by
GitHub