AutoRAG
FreeOpen source AutoML tool for RAG. Optimize the RAG answer quality automatically. From generation evaluation datset to deploying optimized RAG pipeline.
About AutoRAG
AutoRAG is a self-evolving librarian agent that transforms document search from raw file listings to curated, actionable knowledge. It uses a two-tier agent workflow where a parent orchestrator delegates exploration to specialized explorer agents, searching PDFs, wikis, notes, research papers, and knowledge bases. Results are returned as clean, numbered knowledge units with page references, eliminating the need to manually open and read multiple files. A built-in self-evolving memory system learns from usage patterns and feedback, improving retrieval strategies over time. AutoRAG is fully open-source and free to use, designed as a customized Pi agent configured for document retrieval.
Key Features
Pros & Cons
- Delivers curated answers with citations instead of raw file matches
- Learns and adapts retrieval strategies over time based on usage
- Handles multiple document types with a single interface
- Fully open-source and free to use