Raptor RAG explained: A full guide to hierarchical retrieval

This post introduces and explains the RAPTOR (Recursive Abstractive Processing for Tree-Organized Retrieval) method for RAG systems. It details the five-step process of chunking, generating embeddings, clustering similar chunks, creating cluster summaries, and building a recursive tree. It also provides Python code examples for each step and discusses limitations such as cost, error chaining, and the need for frequent updates with dynamic data. The post contrasts RAPTOR with other RAG methods like GraphRAG and CRAG.