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GraphRAG-UI

GraphRAG-UI is a user-friendly interface for GraphRAG, a powerful tool that uses the Retrieval-Augmented Generation (RAG) approach to index and query large text data. This project supports the latest version graphrag-0.3.3 and aims to provide a convenient management and interaction method for GraphRAG, supporting the configuration of local large language models like Ollama, making it easier for users to leverage.

Acknowledgments

This project is currently an upgrade based on the work of severian42 and his GraphRAG-Local-UI project. I would like to express my sincere gratitude to him for laying a solid foundation for this project. New features may be added in the future.

Features

• Intuitive Web Interface: GraphRAG-UI provides a user-friendly web interface for easy configuration and use of GraphRAG.
• Index Management: Quickly create, update, and manage your text data indexes.
• Query Execution: Submit natural language queries and retrieve relevant content from indexed data, followed by responses from a large language model.
• Configuration Options: Customize various settings and parameters to fine-tune the indexing and querying processes.
• Logging and Monitoring: Monitor the progress of indexing and querying tasks through detailed logs and status updates.

Sample screenshots:

Indexing

Visualize Graph (GIF image)

Chat With GraphRAG

Usage with pip

1. Install Ollama (optional):

   Visit the Ollama website to install. If you're on Linux, you can run the following command directly:

   curl -fsSL https://ollama.com/install.sh | sh

2. Install this software via pip:

   pip install graphrag-ui
   or
   pip install graphrag-ui -i https://pypi.org/simple

3. Start the API Server

   graphrag-ui-server

4. Start the UI

   Start the comprehensive UI

   graphrag-ui

   Or start the pure UI

   graphrag-ui-pure

Source code installation and usage

1. Create and activate a new conda environment:

   conda create -n graphrag-ui -y
   conda activate graphrag-ui

2. Install Ollama（optional）:

   Visit Ollama's website for installation instructions.

   Or Linux, run:

   curl -fsSL https://ollama.com/install.sh | sh

3. Clone the repository:

   git clone https://github.com/wade1010/graphrag-ui.git

4. Install the required packages:

   cd graphrag-ui
   pip install -r requirements.txt

5. Start the API server:

   python api.py --host 0.0.0.0 --port 8012 --reload

6. Start the UI:

   • Clean version

     This version only supports indexing, Prompt Tuning, and file management, without query functionality.

     gradio index_app.py
     or
     python index_app.py

   • Comprehensive version

     This version adds visualizations, configuration management, and GraphRAG chat functionality on top of the clean version.

     python app.py

7. Access the UI:

   • Clean version: http://localhost:7860
   • Comprehensive version: http://localhost:7862

Installation and Usage Blog

https://blog.csdn.net/wade1010/article/details/142374956