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by Ayanami0730 · Agent Tool · ★ 323
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A-RAG: Scaling Agentic Retrieval-Augmented Generation via Hierarchical Retrieval Interfaces If you find our project helpful, please give us a star ⭐ on GitHub! 🚀 Quick Start bash Install git clone https://github.com/Ayanami0730/arag.git && cd arag uv sync --extra full # or: pip install -e ".[full]" Download benchmark datasets from HuggingFace git clone https://huggingface.co/datasets/Ayanami0730/ragtest data --depth 1 rm -rf data/.git data/README.md Build embedding index We use Qwen3-Embedding-0.6B in our paper (https://huggingface.co/Qwen/Qwen3-Embedding-0.6B) You can also use a local path: --model /path/to/Qwen3-Embedding-0.6B uv run python scripts/buildindex.py \ --chunks data/musique/chunks.json \ --output data/musique/index \ --model Qwen/Qwen3-Embedding-0.6B \ --device cuda:0 Set environment variables e
| Stars | 323 |
| Forks | 49 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 62.8582548304153/100 |
| Open Issues | 5 |
| 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 323 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 323 stars and 49 forks, indicating an active community.
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