RAG Web UI : Intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology

RAG Web UI

Social Robots Knowledge Management #Artificial Intelligence #RAG Technology #Intelligent Dialogue #Knowledge Management #Document Processing #Vector Database Standard Picks Open Source

Overview :

RAG Web UI is an intelligent dialogue system based on RAG technology that combines document retrieval with large language models to provide intelligent question-and-answer services based on knowledge bases for enterprises and individuals. The system employs a decoupled architecture, supporting smart management of various document formats (such as PDF, DOCX, Markdown, Text), including automatic chunking and vectorization. Its dialogue engine supports multi-turn dialogue and citation references, delivering accurate knowledge retrieval and generation services. The system also allows flexible switching between high-performance vector databases (such as ChromaDB and Qdrant), ensuring good scalability and performance optimization. As an open-source project, it offers developers a wealth of technical implementations and application scenarios, making it suitable for building enterprise-class knowledge management systems or intelligent customer service platforms.

Target Users :

This product is primarily aimed at enterprises and individual developers looking to build intelligent question-answering systems, particularly those who wish to implement efficient knowledge management and intelligent dialogue based on their own knowledge bases. It is also suitable for developers interested in RAG technology, as they can learn and practice the application of RAG technology in intelligent dialogue systems through this project.

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Use Cases

Internal knowledge base Q&A system: Enterprises can upload internal documents to the system, allowing employees to quickly retrieve the knowledge they need through the dialogue interface.

Intelligent customer service platform: Enterprises can utilize this system to build intelligent customer service, providing customers with automated Q&A services based on knowledge bases.

Personal knowledge management assistant: Individual users can upload their notes, documents, etc., to the system and use the dialogue interface for knowledge retrieval and organization.

Features

Supports intelligent management of various document formats (PDF, DOCX, Markdown, Text)

Automatic document chunking and vectorization, supporting asynchronous processing and incremental updates

Accurate retrieval and generation based on RAG technology, supporting multi-turn dialogue and citation references

Decoupled architecture, supporting distributed file storage and high-performance vector databases

Flexible switching between various vector databases (such as ChromaDB and Qdrant)

How to Use

1. Clone the project repository: `git clone https://github.com/rag-web-ui/rag-web-ui.git`

2. Configure environment variables: Copy `backend/.env.example` to `backend/.env` and adjust the settings as needed

3. Start the service: Run `docker-compose up -d` to launch the service

4. Access the front-end interface: Open your browser and go to `http://localhost:3000` to start using it

5. Upload documents: Upload the documents you need to process through the front-end interface; the system will automatically handle chunking and vectorization.