本项目是一套完整的检索增强生成（Retrieval-Augmented Generation, RAG）技术实现方案，包含21个专题笔记本，覆盖从基础实现到高级优化的全技术栈。通过模块化设计，开发者可以系统性地掌握**RAG核心组件及其进阶技巧**，包括**多粒度分块策略（语义/命题/上下文分块）、混合检索引擎（向量+关键词融合）、动态上下文管理（压缩/扩展/重组）、智能查询理解（重写/退步/分解）、假设文档嵌入（HyDE）技术、自适应检索路由（问题类型感知）、自优化反馈循环（Self-RAG）、实时纠错机制（CRAG）、强化学习调优（RL RAG）、多模态处理（文本+图像联合检索）、知识图谱增强（Graph RAG）、分层索引优化（十亿级文档支持）等核心技术亮点
☆16Oct 23, 2025Updated last year
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