Ragflow Admin AI Agent

<div align="center"> <a href="https://github.com/infiniflow/ragflow"> <img src="web/public/logo.svg" width="120" alt="RAGFlow logo"> </a> <h1>RAGFlow Admin</h1> </div> <p align="center"> <a href="./README.md">English</a> | <a href="./README_zh.md">简体中文</a> </p> <p align="center"> <a href="https://github.com/tedhappy/ragflow-admin/releases/latest"> <img src="https://img.shields.io/github/v/release/tedhappy/ragflow-admin?color=blue&label=Latest%20Release" alt="Latest Release"> </a> <a href="https://github.com/infiniflow/ragflow"> <img src="https://img.shields.io/badge/RAGFlow-v0.15+-blue" alt="RAGFlow Version"> </a> <a href="https://github.com/tedhappy/ragflow-admin/blob/main/LICENSE"> <img src="https://img.shields.io/badge/License-Apache%202.0-green" alt="License"> </a> </p> <p align="center"> A standalone administration console for RAGFlow </p>

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🔎 Overview

RAGFlow Admin is a lightweight, standalone administration console for RAGFlow — the leading open-source RAG engine with deep document understanding. It provides a modern web interface for centralized management of datasets, documents, chat assistants, agents, and users.

Why RAGFlow Admin?

RAGFlow is a powerful RAG engine, but its built-in management interface has some limitations for production use:

Pain Point	RAGFlow Admin Solution
Single dataset view	Cross-dataset dashboard for unified management
No batch operations	Bulk upload, parse, stop, and delete across datasets
Hidden task queue	Real-time task monitoring with queue position and progress
Complex user management	Centralized user admin panel with statistics
Limited operational insight	Dashboard with health checks and usage metrics
Steep learning curve	Intuitive UI designed for administrators

✨ Features

Core Management

Feature	Description
📚 Dataset Management	View all datasets across users, create, delete with batch operations
📄 Document Management	Upload, parse, stop, delete documents with real-time progress tracking
📊 Task Queue	Global task monitoring across all datasets with queue position, filtering and batch control

Extended Capabilities

Feature	Description
💬 Chat Management	View and manage chat assistants and conversation sessions
🤖 Agent Management	List and manage AI agents across users
👥 User Management	View RAGFlow users with statistics, manage team relations (requires MySQL access)
👥 Team Relations	View and manage user team memberships - owned teams, joined teams, and pending invites
🔍 System Monitoring	Dashboard with service health checks and usage statistics
🌐 i18n Support	Full internationalization (English & Chinese)

🖼️ Screenshots

Dashboard

<p align="center"> <img src="docs/images/dashboard.jpg" width="800" alt="Dashboard"/> </p>

Task Queue

<p align="center"> <img src="docs/images/tasks.jpg" width="800" alt="Task Queue"/> </p>

Dataset Management

<p align="center"> <img src="docs/images/datasets.jpg" width="800" alt="Datasets"/> </p>

Document Management

<p align="center"> <img src="docs/images/documents.jpg" width="800" alt="Documents"/> </p>

Chat Management

<p align="center"> <img src="docs/images/chats.jpg" width="800" alt="Chats"/> </p>

Team Relations

<p align="center"> <img src="docs/images/teams.png" width="800" alt="teams"/> </p>

User Management

<p align="center"> <img src="docs/images/users.png" width="800" alt="Users"/> </p>

Settings

<p align="center"> <img src="docs/images/settings.jpg" width="800" alt="Settings"/> </p>

🚀 Getting Started

Prerequisites

• A running RAGFlow instance (v0.15+)
• Docker 20.10+ & Docker Compose 2.0+ (for Docker deployment)
• Python 3.10+ & Node.js 18+ (for source deployment)

🐳 Docker Deployment (Recommended)

$ git clone https://github.com/tedhappy/ragflow-admin.git
$ cd ragflow-admin/docker
$ docker compose -f docker-compose.yml up -d

Check server status:

$ docker logs -f ragflow-admin

Open http://localhost:8000, login with admin/admin, and configure MySQL via Settings page.

See docker/README.md for advanced configuration.

🔧 Source Deployment (Development)

1. Clone and Configure

$ git clone https://github.com/tedhappy/ragflow-admin.git
$ cd ragflow-admin
$ cp conf/config.example.yaml conf/config.yaml

2. Start Backend

$ pip install -r requirements.txt
$ python -m api.server

3. Start Frontend

$ cd web
$ npm install
$ npm run dev

Open http://localhost:8000 to access the admin console.

🏗️ Architecture

ragflow-admin/
├── api/                        # Backend (Python/Quart)
│   ├── apps/                   # API route handlers
│   ├── services/               # Business logic
│   └── server.py               # Application entry point
│
├── web/                        # Frontend (React/UmiJS)
│   └── src/
│       ├── pages/              # Page components
│       ├── components/         # Reusable UI components
│       ├── services/           # API client
│       └── locales/            # i18n translations
│
├── docker/                     # Docker configuration
│   ├── docker-compose.yml      # Docker Compose file
│   ├── .env                    # Environment variables
│   ├── entrypoint.sh           # Container entrypoint
│   ├── spa_server.py           # Frontend SPA server
│   └── README.md               # Docker deployment guide
│
├── conf/                       # Configuration files
├── Dockerfile                  # Docker build file
└── docs/                       # Documentation

🛠️ Tech Stack

Layer	Technology
Backend	Python 3.10+ / Quart
RAGFlow Integration	ragflow-sdk
Frontend	React 18 / UmiJS 4 / TypeScript
UI Components	Ant Design 5
Styling	TailwindCSS 4
State Management	React Query / Zustand
i18n	i18next
Database	MySQL

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Related Links

• RAGFlow - The RAG engine this project manages
• RAGFlow Documentation
• RAGFlow Python SDK
• RAGFlow HTTP API

📄 License

This project is licensed under the Apache License 2.0.

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