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用户转发并评论 LangChain 在 Interrupt 大会上宣布的 LangSmith AI Search 功能，认为用自然语言搜索 trace 能大幅节省团队排查 agent 故障的时间。
LangChain introduces Trajectories in LangSmith, a chronological view of agent sessions that simplifies debugging by aggregating messages from humans, AI, and tools in order for easier navigation and analysis.
The paper proposes EvalXRL, a benchmark for evaluating Explainable Reinforcement Learning methods by using an LLM coding agent to diagnose and fix bugs in RL agents.
A developer asks how others debug AI agents that make wrong decisions due to stale information, questioning the effectiveness of current tracing tools like LangSmith, LangFuse, and Phoenix.