RAPTOR Zero-to-Hero: Master Recursive Tree Retrieval for Advanced RAG Systems
Retrieval-Augmented Generation (RAG) revolutionized AI by grounding LLMs in external knowledge, but traditional flat-chunk retrieval struggles with long, complex documents requiring multi-hop reasoning. RAPTOR (Recursive Abstractive Processing for Tree-Organized Retrieval) solves this by building hierarchical trees of clustered summaries, enabling retrieval across abstraction levels for superior context and accuracy.[1][2] In this zero-to-hero tutorial, you’ll learn RAPTOR’s mechanics, why it outperforms standard RAG, and how to implement it step-by-step with code. We’ll cover pitfalls, tuning, and best practices, empowering developers to deploy production-ready pipelines. ...