GitHubPyPI
PageIndex
AI Agent 指数 第 32(共 51) ↓ 下载分享海报
45 综合分
可观测采用度当前有效 · 2026-09-10 24
动量当前有效 · 2026-09-10 53
关注度当前有效 · 2026-09-10 75
信号可信度 依据当前有数据的独立评分维度数量计算。
高3/3 · 2 种数据源
项目介绍
Reasoning-based RAG ◦ No Vector DB, No Chunking ◦ Context-Aware Retrieval ◦ Reads Like a Human
Are you frustrated with vector database retrieval accuracy for long professional documents? Traditional vector-based RAG relies on semantic similarity rather than true relevance. But similarity ≠ relevance — what we truly need in retrieval is relevance, and that requires reasoning. When working with professional documents that demand contextual understanding, domain expertise, and multi-step reasoning, similarity search often falls short — missing what's relevant but not similar, and returning what's similar yet not relevant.
Inspired by AlphaGo, we propose…
各数据源
56.9k 月下载量
- 月下载量 56.9k
- 周下载量 16.0k
- 日下载量 2.7k
35.6k Star
- Star 35.6k
- Fork 3.1k
- 提交 429
- 发布 13