test_structured_output_optional_param() — langchain Function Reference

Source Code

libs/standard-tests/langchain_tests/integration_tests/chat_models.py lines 2395–2468

    def test_structured_output_optional_param(self, model: BaseChatModel) -> None:
        """Test structured output with optional parameters.

        Test to verify we can generate structured output that includes optional
        parameters.

        This test is optional and should be skipped if the model does not support
        structured output (see configuration below).

        ??? note "Configuration"

            To disable structured output tests, set `has_structured_output` to `False`
            in your test class:

            ```python
            class TestMyChatModelIntegration(ChatModelIntegrationTests):
                @property
                def has_structured_output(self) -> bool:
                    return False
            ```

            By default, `has_structured_output` is True if a model overrides the
            `with_structured_output` or `bind_tools` methods.

        ??? question "Troubleshooting"

            If this test fails, ensure that the model's `bind_tools` method
            properly handles Pydantic V2 models with optional parameters.

            `langchain_core` implements a [utility function](https://reference.langchain.com/python/langchain_core/utils/?h=convert_to_op#langchain_core.utils.function_calling.convert_to_openai_tool).
            that will accommodate most formats.

            See [example implementation](https://github.com/langchain-ai/langchain/blob/master/libs/partners/openai/langchain_openai/chat_models/base.py).
            of `with_structured_output`.

        """
        if not self.has_structured_output:
            pytest.skip("Test requires structured output.")

        # Pydantic
        class Joke(BaseModel):
            """Joke to tell user."""

            setup: str = Field(description="question to set up a joke")
            punchline: str | None = Field(
                default=None, description="answer to resolve the joke"
            )

        chat = model.with_structured_output(Joke, **self.structured_output_kwargs)
        setup_result = chat.invoke(
            "Give me the setup to a joke about cats, no punchline."
        )
        assert isinstance(setup_result, Joke)

        joke_result = chat.invoke("Give me a joke about cats, include the punchline.")
        assert isinstance(joke_result, Joke)

        # Schema
        chat = model.with_structured_output(
            Joke.model_json_schema(), **self.structured_output_kwargs
        )
        result = chat.invoke("Tell me a joke about cats.")
        assert isinstance(result, dict)

        # TypedDict
        class JokeDict(TypedDict):
            """Joke to tell user."""

            setup: Annotated[str, ..., "question to set up a joke"]
            punchline: Annotated[str | None, None, "answer to resolve the joke"]

        chat = model.with_structured_output(JokeDict, **self.structured_output_kwargs)
        result = chat.invoke("Tell me a joke about cats.")
        assert isinstance(result, dict)