DataArcTech/RAG-ARC
A modular, high-performance Retrieval-Augmented Generation framework with multi-path retrieval, graph extraction, and fusion ranking
Supports multi-format document parsing (PDF, DOCX, PPT, Excel) with OCR and layout-aware strategies, combining sparse (BM25), dense (FAISS-GPU), and full-text search via Reciprocal Rank Fusion. Built on FastAPI with PostgreSQL, Redis, and Neo4j integration, enabling incremental knowledge graph updates and GraphRAG with subgraph PPR for efficient reasoning.
Stars
38
Forks
13
Language
Python
License
MIT
Category
Last pushed
Mar 04, 2026
Commits (30d)
0
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