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COGNITO

Private. Local. Fast.

A fully local AI assistant that runs on your machine. No cloud, no data collection, no subscriptions. Your conversations stay yours.

Cognito Screenshot

✨ Features

🔒 100% Private

  • All inference runs locally on your hardware
  • No data ever leaves your machine
  • No API keys or cloud accounts required

🚀 Fast & Lightweight

  • Powered by llama.cpp for efficient inference
  • Supports GGUF quantized models
  • Works on Apple Silicon, NVIDIA GPUs, or CPU

🔍 Intelligent Search

  • Built-in web search (model decides when to search)
  • Deep search mode for comprehensive research
  • Automatic context injection

📄 Document RAG

  • Upload PDFs and text files
  • Chat with your documents

🎨 Modern Interface

  • Clean, dark-themed UI
  • Chat history with session management
  • System prompt customization

⬇️ In-App Model Downloads

  • Browse models directly from Hugging Face
  • One-click download of any GGUF model
  • Automatic model management
  • No external tools needed

🛠️ Installation

Prerequisites

1. Node.js (v18+)

  • Check if installed: 
    node --version
  • Install:
    • Download Node.js (LTS recommended)
    • Or use a version manager like nvm (Mac/Linux) or nvm-windows.

2. Python (v3.10+)

  • Check if installed: 
    python --version  # or python3 --version
  • Install:
    • Download Python
    • Windows Users: Make sure to check "Add Python to PATH" during installation.

3. GPU Acceleration (Optional but Recommended)

  • macOS: Apple Silicon (M1/M2/M3) works out of the box.
  • Windows/Linux: NVIDIA GPU with CUDA drivers installed.

Quick Start

  1. Clone the repository

    git clone https://github.com/ArjunDeshwal/cognitoai.git
cd cognitoai

  2. Set up Python backend

    macOS/Linux:

    python3 -m venv venv
source venv/bin/activate
pip install -r backend/requirements.txt

    Windows:

    python -m venv venv
venv\Scripts\activate
pip install -r backend/requirements.txt

  3. Install frontend dependencies

    cd app
npm install

  4. Run the app

    npm run electron:dev

  5. Download a model

    • Click "⬇️ Models" in the header
    • Browse and download a GGUF model
    • Select it to start chatting!

📁 Project Structure

cognito/
├── app/                    # Electron + React frontend
│   ├── src/
│   │   ├── App.tsx         # Main React component
│   │   ├── App.css         # Styles
│   │   ├── services/api.ts # API client
│   │   └── components/     # UI components
│   ├── electron/
│   │   ├── main.cjs        # Electron main process
│   │   └── preload.cjs     # Preload script
│   └── package.json
├── backend/
│   ├── server.py           # FastAPI server
│   ├── document_rag.py     # Document processing
│   └── requirements.txt
├── tools/
│   └── info/web_search.py  # Web search tool
└── README.md

🤝 Contributing

Open source on GitHub ·

Development Setup

  1. Fork the repository
  2. Create a feature branch 
    git checkout -b feature/amazing-feature
  3. Make your changes
  4. Test thoroughly
  5. Commit with clear messages 
    git commit -m "feat: add amazing feature"
  6. Push and create a Pull Request

Contribution Ideas

  • 🐛 Bug Fixes - Found a bug? We'd love a fix!
  • ✨ New Features - Check issues for feature requests
  • 📖 Documentation - Improve docs, add examples
  • 🎨 UI/UX - Enhance the interface
  • ⚡ Performance - Optimize inference, reduce memory
  • 🧪 Tests - Add test coverage

Code Style

  • Frontend: TypeScript, React hooks, CSS modules
  • Backend: Python 3.10+, FastAPI, type hints
  • Commits: Use Conventional Commits

Reporting Issues

When reporting bugs, please include:

  • OS and version
  • Node.js and Python versions
  • Steps to reproduce
  • Error messages/logs

📜 License

MIT License - see LICENSE for details.

🙏 Acknowledgments

Built with ❤️ for privacy