DataArcTech/RAG-ARC
A modular, high-performance Retrieval-Augmented Generation framework with multi-path retrieval, graph extraction, and fusion ranking
This project helps professionals working with large volumes of documents (like PDFs, PowerPoints, and Excel files) to extract precise answers and generate content. It takes your unstructured documents and questions, then processes them to provide accurate, context-rich responses or summarized information. Knowledge managers, researchers, and content creators who need to quickly retrieve and synthesize information from extensive knowledge bases would find this invaluable.
Use this if you need to build a system that can accurately answer complex questions and generate content from vast collections of diverse, unstructured documents, especially when you need high recall and semantic consistency.
Not ideal if your primary need is simple keyword search or if your data is already highly structured and doesn't require advanced information extraction or reasoning.
Stars
38
Forks
13
Language
Python
License
MIT
Category
Last pushed
Mar 04, 2026
Commits (30d)
0
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