test_json_mode() — langchain Function Reference

Architecture documentation for the test_json_mode() function in chat_models.py from the langchain codebase.

Function python LangChainCore LanguageModelBase

Entity Profile

LangChainCore→ LanguageModelBase→ test_json_mode() — langchain Function Reference

Dependency Diagram

graph TD
  0b8351cf_f050_ff00_4076_b11f0db67172["test_json_mode()"]
  971e928f_9c9b_ce7a_b93d_e762f2f5aa54["ChatModelIntegrationTests"]
  0b8351cf_f050_ff00_4076_b11f0db67172 -->|defined in| 971e928f_9c9b_ce7a_b93d_e762f2f5aa54
  style 0b8351cf_f050_ff00_4076_b11f0db67172 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/standard-tests/langchain_tests/integration_tests/chat_models.py lines 2470–2531

    def test_json_mode(self, model: BaseChatModel) -> None:
        """Test [structured output]((https://docs.langchain.com/oss/python/langchain/structured-output)) via JSON mode.

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

        ??? note "Configuration"

            To disable this test, set `supports_json_mode` to `False` in your
            test class:

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

        ??? question "Troubleshooting"

            See example implementation of `with_structured_output` here: https://python.langchain.com/api_reference/_modules/langchain_openai/chat_models/base.html#BaseChatOpenAI.with_structured_output

        """  # noqa: E501
        if not self.supports_json_mode:
            pytest.skip("Test requires json mode support.")

        from pydantic import BaseModel as BaseModelProper  # noqa: PLC0415
        from pydantic import Field as FieldProper  # noqa: PLC0415

        class Joke(BaseModelProper):
            """Joke to tell user."""

            setup: str = FieldProper(description="question to set up a joke")
            punchline: str = FieldProper(description="answer to resolve the joke")

        # Pydantic class
        chat = model.with_structured_output(Joke, method="json_mode")
        msg = (
            "Tell me a joke about cats. Return the result as a JSON with 'setup' and "
            "'punchline' keys. Return nothing other than JSON."
        )
        result = chat.invoke(msg)
        assert isinstance(result, Joke)

        chunk = None
        for chunk in chat.stream(msg):
            assert isinstance(chunk, Joke)
        assert chunk is not None, "Stream returned no chunks - possible API issue"

        # Schema
        chat = model.with_structured_output(
            Joke.model_json_schema(), method="json_mode"
        )
        result = chat.invoke(msg)
        assert isinstance(result, dict)
        assert set(result.keys()) == {"setup", "punchline"}

        chunk = None
        for chunk in chat.stream(msg):
            assert isinstance(chunk, dict)
        assert chunk is not None, "Stream returned no chunks - possible API issue"
        assert set(chunk.keys()) == {"setup", "punchline"}