with_structured_output() — langchain Function Reference

Source Code

libs/partners/openai/langchain_openai/chat_models/base.py lines 1961–2223

    def with_structured_output(
        self,
        schema: _DictOrPydanticClass | None = None,
        *,
        method: Literal[
            "function_calling", "json_mode", "json_schema"
        ] = "function_calling",
        include_raw: bool = False,
        strict: bool | None = None,
        tools: list | None = None,
        **kwargs: Any,
    ) -> Runnable[LanguageModelInput, _DictOrPydantic]:
        """Model wrapper that returns outputs formatted to match the given schema.

        Args:
            schema: The output schema. Can be passed in as:

                - An OpenAI function/tool schema,
                - A JSON Schema,
                - A `TypedDict` class,
                - Or a Pydantic class.

                If `schema` is a Pydantic class then the model output will be a
                Pydantic instance of that class, and the model-generated fields will be
                validated by the Pydantic class. Otherwise the model output will be a
                dict and will not be validated.

                See `langchain_core.utils.function_calling.convert_to_openai_tool` for
                more on how to properly specify types and descriptions of schema fields
                when specifying a Pydantic or `TypedDict` class.

            method: The method for steering model generation, one of:

                - `'function_calling'`:
                    Uses OpenAI's [tool-calling API](https://platform.openai.com/docs/guides/function-calling)
                    (formerly called function calling)
                - `'json_schema'`:
                    Uses OpenAI's [Structured Output API](https://platform.openai.com/docs/guides/structured-outputs)
                - `'json_mode'`:
                    Uses OpenAI's [JSON mode](https://platform.openai.com/docs/guides/structured-outputs/json-mode).
                    Note that if using JSON mode then you must include instructions for
                    formatting the output into the desired schema into the model call

            include_raw:
                If `False` then only the parsed structured output is returned.

                If an error occurs during model output parsing it will be raised.

                If `True` then both the raw model response (a `BaseMessage`) and the
                parsed model response will be returned.

                If an error occurs during output parsing it will be caught and returned
                as well.

                The final output is always a `dict` with keys `'raw'`, `'parsed'`, and
                `'parsing_error'`.
            strict:

                - `True`:
                    Model output is guaranteed to exactly match the schema.
                    The input schema will also be validated according to the
                    [supported schemas](https://platform.openai.com/docs/guides/structured-outputs/supported-schemas?api-mode=responses#supported-schemas).
                - `False`:
                    Input schema will not be validated and model output will not be
                    validated.
                - `None`:
                    `strict` argument will not be passed to the model.

            tools:
                A list of tool-like objects to bind to the chat model. Requires that:

                - `method` is `'json_schema'` (default).
                - `strict=True`
                - `include_raw=True`

                If a model elects to call a tool, the resulting `AIMessage` in `'raw'`
                will include tool calls.

                ??? example

                    ```python