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test_trajectory_eval_chain() — langchain Function Reference

Architecture documentation for the test_trajectory_eval_chain() function in test_eval_chain.py from the langchain codebase.

Function python LangChainCore ApiManagement

Entity Profile

Dependency Diagram

graph TD
  551b6ecf_8c9a_0959_c3a5_28ddfc4c4780["test_trajectory_eval_chain()"]
  1ff39fbd_e89b_6287_757b_009d26497b03["test_eval_chain.py"]
  551b6ecf_8c9a_0959_c3a5_28ddfc4c4780 -->|defined in| 1ff39fbd_e89b_6287_757b_009d26497b03
  style 551b6ecf_8c9a_0959_c3a5_28ddfc4c4780 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

libs/langchain/tests/unit_tests/evaluation/agents/test_eval_chain.py lines 118–143

def test_trajectory_eval_chain(
    intermediate_steps: list[tuple[AgentAction, str]],
) -> None:
    llm = _FakeTrajectoryChatModel(
        queries={
            "a": "Trajectory good\nScore: 5",
            "b": "Trajectory not good\nScore: 1",
        },
        sequential_responses=True,
    )
    chain = TrajectoryEvalChain.from_llm(llm=llm, agent_tools=[foo])
    # Test when ref is not provided
    res = chain.evaluate_agent_trajectory(
        input="What is your favorite food?",
        agent_trajectory=intermediate_steps,
        prediction="I like pie.",
    )
    assert res["score"] == 1.0
    # Test when ref is provided
    res = chain.evaluate_agent_trajectory(
        input="What is your favorite food?",
        agent_trajectory=intermediate_steps,
        prediction="I like pie.",
        reference="Paris",
    )
    assert res["score"] == 0.0

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Defined In

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Frequently Asked Questions

What does test_trajectory_eval_chain() do?
test_trajectory_eval_chain() is a function in the langchain codebase, defined in libs/langchain/tests/unit_tests/evaluation/agents/test_eval_chain.py.
Where is test_trajectory_eval_chain() defined?
test_trajectory_eval_chain() is defined in libs/langchain/tests/unit_tests/evaluation/agents/test_eval_chain.py at line 118.

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