create_schema_from_function#

langchain_core.tools.base.create_schema_from_function(model_name: str, func: Callable, *, filter_args: Sequence[str] | None = None, parse_docstring: bool = False, error_on_invalid_docstring: bool = False, include_injected: bool = True) → Type[BaseModel][source]#

Create a pydantic schema from a function’s signature.

Parameters:

model_name (str) – Name to assign to the generated pydantic schema.
func (Callable) – Function to generate the schema from.
filter_args (Sequence[str] | None) – Optional list of arguments to exclude from the schema. Defaults to FILTERED_ARGS.
parse_docstring (bool) – Whether to parse the function’s docstring for descriptions for each argument. Defaults to False.
error_on_invalid_docstring (bool) – if parse_docstring is provided, configure whether to raise ValueError on invalid Google Style docstrings. Defaults to False.
include_injected (bool) – Whether to include injected arguments in the schema. Defaults to True, since we want to include them in the schema when validating tool inputs.

Returns:

A pydantic model with the same arguments as the function.

Return type:

Type[BaseModel]