incidentfox/OpenRag
Multi-strategy RAG system achieving 74% Recall@10 on MultiHop-RAG. Combines RAPTOR hierarchical retrieval, knowledge graphs, HyDE, BM25, and Cohere neural reranking.
Implements a FastAPI server with pluggable retrieval strategies (semantic search, HyDE query expansion, BM25 hybrid matching, multi-hop decomposition) that run in parallel before Cohere neural reranking, with built-in persistence for RAPTOR hierarchies and a comprehensive benchmark suite supporting MultiHop-RAG and CRAG datasets. Ablation studies show the neural reranker alone contributes +9.3% recall improvement, while local cross-encoder alternatives are available for privacy-sensitive deployments.
Stars
36
Forks
5
Language
Python
License
MIT
Category
Last pushed
Feb 03, 2026
Commits (30d)
0
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