Sagi is a production-ready, open-source LLM agent framework that combines advanced technologies to create powerful AI agents. It features:

• 🧠 Deep-research workflow architecture, more details refers to the doc
• 🛠️ MCP (Model Context Protocol) integration, the guide of the usage of MCP refers to the doc
• 📊 GraphRAG-powered retrieval system, HiRAG mcp server refers to the repo

• [2025/04] 🔥 Sigi is publicly released!

• Interactive Web UI
• Advanced file chunking & indexing supports
• Improved documentation with more demos

1. System Requirements

   • Docker and Docker Compose (Installation Guide)

2. Clone the Repository

   git clone https://github.com/vercel/ofnil-agentic-rag-open.git
   cd ofnil-agentic-rag-open
   git submodule update --init --recursive  # Download MCP servers and Markify(MinerU)

3. Environment Setup

   cp .env.example .env

   Configure the following in your .env file:

   • OPENAI_API_KEY - Your OpenAI API key
   • BRAVE_API_KEY - Your Brave Search API key
   • OPENAI_BASE_URL - (Optional) Custom endpoint URL

1. Build the Docker Container

   ./dev/setup_dc.sh

2. Access the Container (Choose one method)

   • Option A: Use VSCode Remote Container (Recommended). You can run bash dev/install_vscode_extensions.sh to install the basic plugins for the development.
   • Option B: Access via terminal:

     docker exec -it "$(whoami)_chatbot_open" /bin/bash

3. Install Dependencies

   pip install -r requirements.txt

4. Start CLI

   python cli.py

We welcome contributions! Please feel free to submit a Pull Request.

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.