Scientia AI 🧠

Scientia is an AI-powered knowledge exploration and management system that combines a powerful language model with a local knowledge base to provide intelligent responses and insights.

Features

• 🤖 Advanced AI Chat Interface
• 📚 Local Knowledge Base Management
• 🔍 Intelligent Document Processing
• 📊 Topic Analysis and Exploration
• 🔄 RAG (Retrieval-Augmented Generation)
• 📝 Multi-format Document Support (PDF, DOCX, Images)
• 🔒 Privacy-focused (all data stays local)

Installation

Using Homebrew (recommended)

1. Install Homebrew if you haven't already:

   /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
   

2. Tap the Scientia repository:

   brew tap scientia-ai/scientia
   

3. Install Scientia:

   brew install scientia
   

From Source

1. Clone the repository:

   git clone https://github.com/scientia-ai/scientia.git
   cd scientia
   

2. Create a virtual environment and activate it:

   python3 -m venv venv
   source venv/bin/activate
   

3. Install uv:

   pip install uv
   

4. Install dependencies using uv:

   uv sync 
   

5. Set up the configuration:

   cp config.example.yml config.yml
   

   Edit config.yml with your preferred settings.

6. Run the application:

   python src/main.py
   

Web Interface

The web interface provides several features:

1. Chat Interface

   • Interactive conversations with AI
   • Knowledge base integration
   • Suggested follow-up questions
   • Topic analysis mode

2. Knowledge Base

   • Add text or documents
   • Search existing knowledge
   • Manage privacy levels
   • Tag and organize information

3. Advanced Tools

   • Knowledge visualization (coming soon)
   • Concept mapping (coming soon)
   • Source analysis (coming soon)

System Requirements

• Python 3.10+
• 8GB RAM (16GB recommended)
• Local storage for knowledge base
• Optional: NVIDIA GPU for faster processing

Core Dependencies

• PyTorch: Machine learning framework
• Transformers: Language model support
• ChromaDB: Vector database for knowledge storage
• Streamlit: Web interface
• Tesseract: OCR support

Development Setup

1. Set up your environment:

Contributing

1. Fork the repository from https://github.com/dirvine/scientia
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add amazing feature'
4. Push to the branch: git push origin feature/amazing-feature
5. Open a Pull Request

License

MIT License - see LICENSE

Support

• 📖 Documentation
• 🐛 Issue Tracker
• 💬 Discussions

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Built with ❤️ using Streamlit, Hugging Face, and ChromaDB