aevaluate_agent_trajectory() — langchain Function Reference

Source Code

libs/langchain/langchain_classic/evaluation/schema.py lines 478–507

    async def aevaluate_agent_trajectory(
        self,
        *,
        prediction: str,
        agent_trajectory: Sequence[tuple[AgentAction, str]],
        input: str,  # noqa: A002
        reference: str | None = None,
        **kwargs: Any,
    ) -> dict:
        """Asynchronously evaluate a trajectory.

        Args:
            prediction: The final predicted response.
            agent_trajectory:
                The intermediate steps forming the agent trajectory.
            input: The input to the agent.
            reference: The reference answer.
            **kwargs: Additional keyword arguments.

        Returns:
            The evaluation result.
        """
        self._check_evaluation_args(reference=reference, input_=input)
        return await self._aevaluate_agent_trajectory(
            prediction=prediction,
            input=input,
            agent_trajectory=agent_trajectory,
            reference=reference,
            **kwargs,
        )