VOT1 - Self-Improving Memory System

VOT1 is an advanced self-improving system focused on memory management with OWL reasoning and visualization. It implements a robust vector-based memory system combined with semantic reasoning capabilities and automates self-improvement through AI-powered workflows.

Key Features

• Vector-based Memory Management: Store and retrieve memories using vector embeddings for semantic similarity search
• OWL Reasoning Engine: Apply ontology-based reasoning to memories and system components
• Self-Improvement Workflows: Automated workflows for enhancing system components
• THREE.js Dashboard: Interactive 3D visualization of memory connections with cyberpunk aesthetic

Getting Started

Prerequisites

• Python 3.9+
• Node.js 14+ (for dashboard)
• Git

Installation

1. Clone the repository:

   git clone https://github.com/villageofthousands/vot1.git
   cd vot1

2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

3. Set up environment variables:

   cp .env.example .env
   # Edit .env with your API keys and configuration

Running the System

To start the dashboard:

python -m src.vot1.dashboard.app

The dashboard will be available at http://localhost:5000

Self-Improvement Workflow

VOT1 includes a self-improvement workflow that can enhance various components:

# Run self-improvement targeting the THREE.js visualization
python -m scripts.run_self_improvement --target three-js --thinking-tokens 8192 --mode agent --iterations 1

Options:

• --target: Component to improve (three-js, memory, owl-reasoning, dashboard)
• --mode: Improvement mode (agent, workflow, analysis)
• --thinking-tokens: Maximum tokens for thinking steps
• --iterations: Number of improvement iterations

Architecture

VOT1 consists of several key components:

• Memory Manager: Core system for storing and retrieving vector-based memories
• OWL Reasoning Engine: Provides semantic reasoning based on ontology
• Self-Improvement Framework: Automates the enhancement of system components
• Dashboard: Visualization and interaction layer with THREE.js rendering

Contributing

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

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Please make sure to update tests as appropriate.

See CONTRIBUTING.md for more information.

License

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

Acknowledgments

• THREE.js for 3D visualization
• OWLready2 for OWL reasoning
• Sentence Transformers for vector embeddings