test_correct_get_tracer_project() — langchain Function Reference

Architecture documentation for the test_correct_get_tracer_project() function in test_langchain.py from the langchain codebase.

Function python LangChainCore MessageInterface

Entity Profile

LangChainCore→ MessageInterface→ test_correct_get_tracer_project() — langchain Function Reference

Dependency Diagram

graph TD
  88c5bbd4_69f1_90ac_9622_590b435111e9["test_correct_get_tracer_project()"]
  6ee6ed10_3ff3_3d50_08bc_311ea99250db["test_langchain.py"]
  88c5bbd4_69f1_90ac_9622_590b435111e9 -->|defined in| 6ee6ed10_3ff3_3d50_08bc_311ea99250db
  style 88c5bbd4_69f1_90ac_9622_590b435111e9 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/core/tests/unit_tests/tracers/test_langchain.py lines 124–151

def test_correct_get_tracer_project(
    envvars: dict[str, str], expected_project_name: str
) -> None:
    if hasattr(get_env_var, "cache_clear"):
        get_env_var.cache_clear()  # type: ignore[attr-defined]
    if hasattr(get_tracer_project, "cache_clear"):
        get_tracer_project.cache_clear()
    with pytest.MonkeyPatch.context() as mp:
        for k, v in envvars.items():
            mp.setenv(k, v)

        client = unittest.mock.MagicMock(spec=Client)
        tracer = LangChainTracer(client=client)
        projects = []

        def mock_create_run(**kwargs: Any) -> Any:
            projects.append(kwargs.get("session_name"))
            return unittest.mock.MagicMock()

        client.create_run = mock_create_run

        tracer.on_llm_start(
            {"name": "example_1"},
            ["foo"],
            run_id=UUID("9d878ab3-e5ca-4218-aef6-44cbdc90160a"),
        )
        tracer.wait_for_futures()
        assert projects == [expected_project_name]