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FLASHRAG
A Python toolkit for efficient RAG research
MIT
ABOUT
RAG researchers and developers face high friction reproducing SOTA methods, benchmarking new ideas, and assembling pipelines from scratch. FlashRAG standardizes datasets, components, and evaluation in one modular toolkit, dramatically accelerating RAG experimentation and reproducibility.
INSTALL
pip install flashrag-dev --preINTEGRATION GUIDE
1. Reproduce and benchmark 23+ SOTA RAG algorithms on 36+ datasets
2. Assemble custom RAG pipelines from modular retrievers, generators, and refiners
3. Evaluate reasoning-based RAG on complex multi-hop QA tasks
4. Rapidly prototype RAG systems via the included visual UI (FlashRAG-UI)
TAGS
RAGbenchmarkretrieval-augmented-generationdatasetsLLMevaluationframeworkPython