README.md

📚 Ragify

A modern, intuitive interface for building RAG-powered AI applications with MindsDB.

🚀 Features

• 🔌 Multi-Source Data Integration: Connect to various data sources including Airbyte connections.
• 🧠 Smart Knowledge Base: Automatically create and manage AI-powered knowledge bases.
• 💬 Interactive Chat: Engage with your data through natural conversations.
• 🔧 No-Code Configuration: Set up and manage your RAG system without writing code.
• 🎯 Precise Retrieval: Get accurate, context-aware responses from your data.
• 🔄 Airbyte Integration: Seamlessly fetch data from hundreds of sources using Airbyte.

🏃 Quick Start

0. Clone & Install

   git clone https://github.com/parthiv11/ragify.git
   cd ragify
   pip install -r requirements.txt

1. Add .env

   copy.env.exampleand create.evn` and populate it

2. Run MindsDB

   python -m mindsdb

3. Run FastAPI

   uvicorn main:app --reload

4. Run Streamlit

   streamlit run app.py

5. Access the UI Open http://localhost:8501 in your browser.

🛠️ Architecture

Ragify combines MindsDB's powerful RAG capabilities with a streamlined user interface:

📊 Data Integration

Ragify supports multiple ways to ingest your data:

1. Airbyte Sources

   • Connect to hundreds of data sources using Airbyte.
   • Automatic schema detection and data synchronization.
   • Real-time data updates.

2. Direct Connections

   • Native database connections.
   • File uploads.
   • API integrations.

3. Knowledge Base Creation

   • Automatic vector embedding.
   • Smart chunking and indexing.
   • Metadata extraction.

Watch the demo video here.

🤝 Contributing

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

📝 License

MIT License

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Built with ❤️ using MindsDB, Airbyte, and Streamlit.