This tree search framework hits 98.7% on documents where vector search fails

Source: VentureBeat

PageIndex tackles long‑document retrieval in RAG

A new open‑source framework called PageIndex solves one of the old problems of retrieval‑augmented generation (RAG): handling very long documents.

The classic RAG workflow (chunk documents, calculate embeddings, store them in a vector database, and retrieve the top matches based on semantic similarity) struggles when documents exceed the token limits of most language models. PageIndex introduces a tree‑search approach that can index and retrieve information from massive texts while keeping the query latency low.