all-in-rag

Why we included this project

If you're learning retrieval-augmented generation, this guide from the Datawhale community is one of the most practical open resources around. It's structured like a real course rather than a reference dump: you start with how embeddings and retrieval work, then build an actual RAG app using LangChain or LlamaIndex, and later see how vector stores like Milvus and graph databases like Neo4j fit into the picture. Because it comes with a runnable example project and a freely hosted online version, it works both as a structured introduction for developers new to RAG and as a refresher for engineers who want to see the whole pipeline in one place. The writing rewards reading alongside a code editor, so plan to follow along rather than skim.