Orange 用 LangSmith 评估企业级 Agent:从 RAG 到生产监控
Orange 公开了评估企业 Agent 的完整清单:RAG 召回、工具选择、线上延迟成本,照着搭就行。
OrangeBusiness 在企业 AI 平台中用 LangSmith 完成 Agent 评估,覆盖 RAG 质量、Agent 行为与生产表现三层。RAG 层用 golden datasets 衡量检索召回率和答案忠实度。Agent 行为层测试工具选择准确性和 prompt injection 鲁棒性。生产层追踪延迟、成本、失败运行和人工反馈,所有改动上线前先跑回归评估。框架选用 LangChain 是为了保证模型中立与可移植性。
How @OrangeBusiness evaluate agents in their enterprise AI platform: ✅ RAG quality: golden datasets, retrieval recall, answer faithfulness ✅ Agent behavior: tool selection accuracy, prompt injection robustness ✅ Production traces: latency, cost, failed runs, human feedback All in LangSmith, with regression evals before changes reach production, and LangChain for model neutrality & portability langchain.com/blog/how-orang… ? 💬 5 🔄 1 ❤️ 8 👀 1968 📊 5 ⚡