test_trajectory_eval_chain_no_tools() — langchain Function Reference

Source Code

libs/langchain/tests/unit_tests/evaluation/agents/test_eval_chain.py lines 146–169

def test_trajectory_eval_chain_no_tools(
    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)
    res = chain.evaluate_agent_trajectory(
        input="What is your favorite food?",
        agent_trajectory=intermediate_steps,
        prediction="I like pie.",
    )
    assert res["score"] == 1.0
    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