all-in-rag and rag-guide
These are complementary educational resources that share the same tech stack (FastAPI + LangChain), with the former being a comprehensive theoretical guide and the latter being a practical hands-on handbook for implementing RAG applications end-to-end.
About all-in-rag
datawhalechina/all-in-rag
🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.github.io/all-in-rag/
Covers comprehensive RAG system development from data ingestion through vector embeddings (including multimodal support via image-text retrieval), hybrid search strategies combining dense and sparse retrieval, and advanced techniques like Text2SQL and query rewriting. The curriculum integrates practical implementations using vector databases like Milvus, LLM-based generation, and system evaluation methodologies, culminating in production-ready projects demonstrating Graph RAG architectures and optimization patterns.
About rag-guide
david-zlj/rag-guide
RAG 开发者的一站式手册。以 FastAPI + LangChain 为核心技术栈，助力学习者快速掌握从 0 到 1 搭建 RAG 应用的能力，轻松落地企业知识库等实际项目。
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