DataArcTech/RAG-ARC

A modular, high-performance Retrieval-Augmented Generation framework with multi-path retrieval, graph extraction, and fusion ranking

50
/ 100
Established

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.

No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 18 / 25

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Stars

38

Forks

13

Language

Python

License

MIT

Last pushed

Mar 04, 2026

Commits (30d)

0

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