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PageIndex

RAG & Retrieval

A vectorless, reasoning‑based RAG engine that retrieves information from long documents by simulating human navigation through hierarchical tree indexing, providing traceable and context‑aware results without needing a vector database or chunking.

Python Latest v0.3.0.dev3 · 17d ago Security brief →

Features

  • No Vector DB: Uses document structure and LLM reasoning instead of semantic similarity search
  • No Chunking: Organizes documents into natural sections rather than artificial chunks
  • Traceable & Explainable Retrieval: Provides explicit page/section references for every result
  • Context‑Aware Retrieval: Incorporates full conversation history and domain knowledge

Recent releases

View all 2 releases →
Review required
v0.3.0.dev3 Mixed
Dependencies

TOC fix + litellm integration

No immediate action
v0.3.0.dev2 New feature

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Community & Support

Alternative to

vector‑based RAG traditional vector database retrieval

Beta — feedback welcome: [email protected]