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原始链接: https://news.ycombinator.com/item?id=43459535

Hacker News评论员CharlieDigital批评了qodo.ai一篇关于他们选择使用LangGraph构建编码代理的博文。文章解释了为什么LangGraph比自定义解决方案更受青睐,但未能证明LangGraph优于其他类似框架,例如Mastra。评论员认为文章中提到的优势(大概是灵活性等)也适用于其他替代方案。 他还提到了早期采用的常见问题:文档挑战,强调了由于LangGraph快速发展而导致的文档不完整或过时。他与早期使用微软Semantic Kernel的经验进行了类比,指出大量示例和集成测试的重要性。最后,他提出了一个发人深省的问题:哪家AI初创公司正在利用LLM自动生成高质量的文档、代码示例和库指南?这突出了需要更好的工具来支持开发者应对快速发展的AI框架。


原文
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Why we chose LangGraph to build our coding agent (qodo.ai)
7 points by timbilt 3 hours ago | hide | past | favorite | 1 comment










Article answered "why LangGraph over roll-your-own", but failed to address "why LangGraph" in the broader sense.

All of the points made here are also true for Mastra, for example.

    > One pain point has been documentation. The framework is developing very quickly and the docs are sometimes incomplete or out of date
I also found this to be the case when working with Microsoft's Semantic Kernel in the early days. Thankfully, they had a lot of examples and integration tests demonstrating usage.

Where's the AI startup using LLMs to automatically generate docs, sample code, and guides for libraries?







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