Ayanami0730/arag
A-RAG: Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces. State-of-the-art RAG framework with keyword, semantic, and chunk read tools for multi-hop QA.
This project helps knowledge workers who need accurate answers from large document collections. It takes your questions and your extensive documents (like research papers or company knowledge bases) as input. It then intelligently searches and synthesizes information to provide precise answers, much like a highly skilled research assistant.
192 stars.
Use this if you need to extract precise information and generate accurate answers from complex, extensive document sets, especially for multi-step questions.
Not ideal if your queries are simple keyword lookups or if you only need short, direct answers without much reasoning.
Stars
192
Forks
23
Language
Python
License
—
Category
Last pushed
Feb 06, 2026
Commits (30d)
0
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