by Ayanami0730 · Agent Tool · ★ 187
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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.
| Stars | 187 |
| Forks | 23 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 36.75/100 |
| Open Issues | 2 |
| Last Updated | 2026-02-06 |
| Created | 2026-02-03 |
| Platforms | python |
| Est. Tokens | ~172k |
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arag is 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.. It is categorized as a Agent Tool with 187 GitHub stars.
arag is primarily written in Python. It covers topics such as agent, agentic-ai, agenticrag.
You can find installation instructions and usage details in the arag GitHub repository at github.com/Ayanami0730/arag. The project has 187 stars and 23 forks, indicating an active community.
The top alternatives to arag on Agent Skills Hub include argo, Awesome-LLM-Eval, OpenJudge. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.