_aevaluate_agent_trajectory() — langchain Function Reference
Architecture documentation for the _aevaluate_agent_trajectory() function in schema.py from the langchain codebase.
Entity Profile
Dependency Diagram
graph TD a6be454e_d689_fe5e_3358_4c8b8a8a2fa6["_aevaluate_agent_trajectory()"] 942e26b5_86b7_44c9_5c6d_e12c17d223b8["AgentTrajectoryEvaluator"] a6be454e_d689_fe5e_3358_4c8b8a8a2fa6 -->|defined in| 942e26b5_86b7_44c9_5c6d_e12c17d223b8 b659b7f6_5fb9_1be0_d430_ab613252fe80["aevaluate_agent_trajectory()"] b659b7f6_5fb9_1be0_d430_ab613252fe80 -->|calls| a6be454e_d689_fe5e_3358_4c8b8a8a2fa6 style a6be454e_d689_fe5e_3358_4c8b8a8a2fa6 fill:#6366f1,stroke:#818cf8,color:#fff
Relationship Graph
Source Code
libs/langchain/langchain_classic/evaluation/schema.py lines 415–445
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.
"""
return await run_in_executor(
None,
self._evaluate_agent_trajectory,
prediction=prediction,
agent_trajectory=agent_trajectory,
reference=reference,
input=input,
**kwargs,
)
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Source
Frequently Asked Questions
What does _aevaluate_agent_trajectory() do?
_aevaluate_agent_trajectory() is a function in the langchain codebase, defined in libs/langchain/langchain_classic/evaluation/schema.py.
Where is _aevaluate_agent_trajectory() defined?
_aevaluate_agent_trajectory() is defined in libs/langchain/langchain_classic/evaluation/schema.py at line 415.
What calls _aevaluate_agent_trajectory()?
_aevaluate_agent_trajectory() is called by 1 function(s): aevaluate_agent_trajectory.
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