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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Youtu-RAG: Next-Generation Agentic Intelligent Retrieval-Augmented Generation System
| Date | Stars |
|---|---|
| 2026-07-31 | 273 |
| 2026-08-01 | 273 |
| 2026-08-06 | 273 |
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growth rate 0.00%/day
<div align="center">
<a href="https://youtu-rag-docs.vercel.app" target="_blank">
<img src="docs/assets/Youtu-RAG-title.png" alt="Youtu-RAG" width="800">
</a>
</div>
<div align="center">
[]()
[](LICENSE)
[](https://youtu-rag-docs.vercel.app)
[]()
English | [简体中文](README_ZH.md)
</div>
<p align="center">
<a href="#key-features">✨ Key Features</a> •
<a href="#usage-examples">📖 Usage Examples</a> •
<a href="#quick-start">🚀 Quick Start</a> •
<a href="#benchmarks">📊 Benchmarks</a>
</p>
---
**[Youtu-RAG](https://youtu-rag-docs.vercel.app)** is a next-generation agentic retrieval-augmented generation system built on the **"Local Deployment · Autonomous Decision · Memory-Driven"** paradigm. With autonomous decision-making and memory learning capabilities, it represents best practices for personal local knowledge base management and Q&A systems.
**Core Concepts**:
- **Local Deployment**: All components support local deployment with data staying within domain. Integrated with MinIO object storage for large-scale file local management.
- **Autonomous Decision**: Agents autonomously determine whether to retrieve, how to retrieve, and when to call memory, selecting optimal strategies based on question types and historical experience.
- **Memory-Driven**: Dual-layer memory mechanism (short-term conversational memory + long-term knowledge accumulation) enables continuous learning and self-evolution of Q&A experience.
Traditional RAG systems follow a fixed pipeline of "offline chunking - vector retrieval - concatenation generation," facing core bottlenecks such as **privacy risks, memory loss, and rigid retrieval**. Youtu-RAG aims to upgrade the system from a passive retrieval tool to an **intelligent retrieval-augmented generation system with autonomous decision and memory learning capabilities**.
<p align="center" style="margin-top: 40px;">
<img src="docs/assets/Youtu-RAG.png" alt="Youtu-RAG Architecture" width="100%">
</p>
<a id="key-features"></a>
## ✨ Key Features
<table>
<tr>
<td width="50%" valign="top">
### 📁 File-Centric Architecture
File-based knowledge organization, supporting multi-source heterogeneous data including PDF, Excel, Images, and Databases
**Supported Formats**: `PDF/Word/MD` `Excel` `IMAGE` `Database` `+12 formats`
</td>
<td width="50%" valign="top">
### 🎯 Adaptive Retrieval Engine
Autonomous decision-making on the optimal retrieval strategy, supporting a variety of tool calls such as web search, vector retrieval, metadata filtering, database queries, and code execution
**Retrieval Modes**: `Autonomous Decision` `Tool Call` `Diversified Data Sources`
</td>
</tr>
<tr>
<td width="50%" valign="top">
### 🧠 Dual-Layer Memory
Short-term conversational memory + long-term cross-session knowledge accumulation, achieving Q&A experience learning
**Memory Types**: `Short-Term Memory` `Long-Term Memory` `Q&A Learning`
</td>
<td width="50%" valign="top">
### 🤖 Ready-to-Use Agents
From simple conversations to complex orchestrations, covering a wide range of application-level scenarios. Supports over 8 AI agents including Web Search, KB Search, Meta Retrieval, Excel Agent, and Text2SQL
**Application Scenarios**: `Ready-to-Use` `Diverse Scenarios` `Complex Task Collaboration`
</td>
</tr>
<tr>
<td width="50%" valign="top">
### 🎨 Lightweight WebUI
Pure native HTML + CSS + JavaScript implementation, framework-free. Supports file upload, knowledge base management, AI dialogue, document preview, and complete functionality
**Technical Features**: `Zero Dependencies` `Streaming Response` `Easy Operation`
</td>
<td width="50%" valign="top">
### 🔐 Security & Control
All related components support local deployment, dataExcerpt of 38,558 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:5584891a2094f479, desc:retrieval-augmented generation, desc:retrieval augmented