<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>检索增强生成 on 黄文卓 | DevOps Engineer</title><link>https://socake.github.io/tags/%E6%A3%80%E7%B4%A2%E5%A2%9E%E5%BC%BA%E7%94%9F%E6%88%90/</link><description>Recent content in 检索增强生成 on 黄文卓 | DevOps Engineer</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><managingEditor>17691281867@163.com (Wenzhuo Huang)</managingEditor><webMaster>17691281867@163.com (Wenzhuo Huang)</webMaster><copyright>© 2026 Wenzhuo Huang</copyright><lastBuildDate>Tue, 11 Nov 2025 11:41:00 +0800</lastBuildDate><atom:link href="https://socake.github.io/tags/%E6%A3%80%E7%B4%A2%E5%A2%9E%E5%BC%BA%E7%94%9F%E6%88%90/index.xml" rel="self" type="application/rss+xml"/><item><title>RAG 系统设计与实战：检索增强生成完全指南</title><link>https://socake.github.io/posts/rag-system-design-practice/</link><pubDate>Tue, 11 Nov 2025 11:41:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/rag-system-design-practice/</guid><description>RAG（检索增强生成）是目前企业落地 LLM 最主流的方式。本文覆盖 RAG 系统的完整设计：文档处理管线、分块策略、向量检索与关键词混合检索、Rerank 重排序、上下文压缩，以及用 RAGAS 框架评估 RAG 质量，最后分享生产环境踩坑记录。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/rag-system-design-practice/featured.jpg"/></item></channel></rss>