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PageIndex
📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG
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agent-appagentic-aicontext-engineeringagentsaiinformation-retrievalretrievalragpythonllmreasoningPythonretrieval-augmented-generationai-agentsvector-database
PageIndex is a Python tool from VectifyAI that builds document indexes for vectorless, reasoning-based RAG. Instead of embedding-based retrieval, it structures documents so an LLM can reason over an index to locate relevant content, and it ships a Claude directory (.claude) for agent use.
Reach for it when you want retrieval-augmented generation without maintaining a vector database, letting reasoning replace embeddings for document lookup.
Use it to
- Index documents for reasoning-based RAG pipelines
- Replace vector database retrieval with LLM reasoning
- Integrate document indexing into Claude-based agents
- Experiment with context engineering for retrieval
For Developers building RAG pipelines and agentic AI applications
- Role
- agent-app
- Language
- Python
- Licence
- MIT
- Forks
- 3,144
- Open issues
- 34
- Last push
- 2026-09-15
- Latest release
- v0.3.0.dev2 · 2026-07-08
topicsragretrievalreasoningllmagentic-aicontext-engineering