Ragpi

Documentation | API Reference

Ragpi is an open-source AI assistant that answers questions using your documentation, GitHub issues, and READMEs. It combines LLMs with intelligent search to provide relevant, documentation-backed answers through a simple API. It supports multiple providers like OpenAI, Ollama, and Deepseek, and has built-in integrations with Discord and Slack.

Key Features

• 📚 Builds knowledge bases from docs, GitHub issues and READMEs
• 🤖 Agentic RAG system for dynamic document retrieval
• 🔌 Supports OpenAI, Ollama, Deepseek & OpenAI-Compatible models
• 💬 Discord integration for community support
• 🚀 API-first design with Docker deployment

Quick Start

This is a quick guide to get you started with Ragpi locally. To deploy Ragpi to a production environment, refer to the Deployment Documentation to learn more about different deployment options.

1. Clone and configure:

Clone the repository and navigate to the project directory:

git clone https://github.com/ragpi/ragpi.git
cd ragpi

Copy the example environment file and open it for editing:

cp .env.example .env

Configure the essential environment variables in .env:

# Add your OpenAI API key
OPENAI_API_KEY=your_api_key_here

# Optional: Add your GtiHub Token if using a GitHub connector
GITHUB_TOKEN=your_github_token

# Optional: Add API authentication
RAGPI_API_KEY=your_secret_api_key

Note: If you would like to enable API authentication, set the RAGPI_API_KEY environment variable to a self-generated key. Include this key in the x-api-key header for all requests.

2. Start services:

Start Ragpi using Docker Compose:

docker compose -f docker-compose.prod.yml up -d

3. Add your first source:

Use the Sitemap Connector to create a new source:

curl -X POST http://localhost:8000/sources \
  -H "Content-Type: application/json" \
  -d '{
    "name": "example-docs",
    "description": "Documentation for example project",
    "connector": {
      "type": "sitemap",
      "sitemap_url": "https://your-docs.com/sitemap.xml"
    }
  }'

4. Monitor Synchronization Progress:

Get the task_id from the response of the above command and monitor the source synchronization progress:

curl http://localhost:8000/tasks/{task_id}

5. Ask questions:

Once the source is synchronized, you can ask questions:

curl -X POST http://localhost:8000/chat \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [{
      "role": "user",
      "content": "How do I configure X?"
    }]
  }'

Connectors

Ragpi supports multiple connectors to fetch data from various sources:

• Documentation Website (Sitemap)
• GitHub Issues
• GitHub README Files

Explore connectors →

Providers

Ragpi supports multiple LLM providers for generating responses and embeddings:

• OpenAI (default)
• Ollama
• Deepseek
• OpenAI-compatible APIs

Configure providers →

Integrations

Ragpi supports integrations with popular platforms like Discord and Slack:

• Discord
• Slack