<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>LangChain on Plbear | Cuz Penguin QQ</title><link>https://www.plbear.com/tags/langchain/</link><description>Recent content in LangChain on Plbear | Cuz Penguin QQ</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Wed, 15 Jan 2025 10:00:00 +0800</lastBuildDate><atom:link href="https://www.plbear.com/tags/langchain/index.xml" rel="self" type="application/rss+xml"/><item><title>RAG 检索增强生成实战：从文档切分到向量检索完整方案</title><link>https://www.plbear.com/posts/2025-01-15-rag-practice/</link><pubDate>Wed, 15 Jan 2025 10:00:00 +0800</pubDate><guid>https://www.plbear.com/posts/2025-01-15-rag-practice/</guid><description>RAG（检索增强生成）的完整落地方案，涵盖文档切分策略、向量化、向量检索、重排序、Prompt 工程，以及在招聘场景下的实际应用和踩坑经验。</description></item></channel></rss>