做智能体或自动化流程的开发者，LangSmith Engine 解决了自优化循环的落地难题——反馈自动处理、评估不退化，值得直接集成到你的工作流中。
LangChain 发布 LangSmith Engine，旨在加速软件和智能体的自优化循环。该系统通过观察自身输出、评估并利用信号持续改进，而 LLM 的可靠性使评估步骤终于可行。LangSmith Engine 集成了自动分类反馈、在线评估器防止回归、离线评估加入测试套件，以及根据用户偏好持续调优等功能。该工具已获得大量采用，并随着使用时间增加而效果更好。
LangSmith Engine makes your self-optimizing loops spin faster and faster ⤵️
LangSmith Engine makes your self-optimizing loops spin faster and faster ⤵️ Palash Shah @palashshah everyone is talking about self-optimizing loops in software & agents. but what does that actually mean? in my mind, it's a system that observes it's own outputs, evaluates them, and uses that signal to improve itself in the future. the reason why it has become so popular now, is because the evaluation step is finally reliable with llms. this wasn't really the case a year ago. this is why i'm so bullish on langsmith engine. we've incorporated a ton of different concepts that allow developers to invest in this self-optimizing loop that makes the improvement flywheel spin faster & faster. some examples of this include > feedback you leave on traces are automatically triaged > every fix that we suggest has an online evaluator, so you never regress > we create offline evals that you can add to your test suite > we continually learn on your preferences, and tune our evaluation & fix step based on this and we're seeing crazy adoption, and lots of growth across our customers. it is truly something that just gets better the more time you spend on it. 🔗 View Quoted Tweet 💬 1 🔄 0 ❤️ 7 👀 1841 📊 2 ⚡