Project Prometheus

A hierarchical multi-agent system for AGI research and development, implementing a "society of minds" architecture with specialized AI agents collaborating in a structured yet adversarial ecosystem.

Architecture Overview

Project Prometheus is executed by a hierarchical, multi-agent system composed of specialized AI agents, each with distinct roles and responsibilities:

Agent Hierarchy

• Agent Prometheus (Master Control & Strategy): The highest-level agent serving as project director

  • Interprets constitutional mission and decomposes into strategic research phases
  • Allocates computational resources and synthesizes findings from subordinate agents
  • Responsible for overall project planning and coordination

• Agent Daedalus (Cognitive Architect): Lead R&D agent responsible for core AGI architecture design

  • Explores and integrates architectural pathways
  • Develops hybrid neuro-symbolic core with interplay between sub-symbolic learning and formal reasoning
  • Designs robust, generalizable intelligence systems

• Agent Logos (Symbolic Reasoner & Verifier): Specialized sub-agent reporting to Daedalus

  • Focuses on "System 2" components of hybrid brain
  • Develops formal logic systems, knowledge graphs, and program synthesis capabilities
  • Serves as verifier for logical consistency of reasoning traces and plans

• Agent Odysseus (Embodied Explorer & Tool User): Responsible for grounding knowledge in reality

  • Operates within complex, high-fidelity simulations
  • Interacts with external tools (databases, APIs, code execution environments)
  • Generates rich, multimodal, experiential data to bridge abstract knowledge and real-world application

• Agent Themis (Safety & Alignment Overseer): Most critical agent with highest priority and veto power

  • Serves as internal perpetual red team
  • Continuously audits, stress-tests, and evaluates all architectures and behaviors
  • Monitors for emergent undesirable behaviors and specification gaming
  • Uses interpretability tools to ensure alignment with project constitution

Key Features

• Hierarchical Multi-Agent Architecture: Structured communication and coordination between specialized agents
• Safety-First Design: Integrated safety monitoring and veto mechanisms
• Hybrid Intelligence: Combining neural networks with symbolic reasoning
• Embodied Learning: Real-world grounding through simulation and tool interaction
• Formal Verification: Logical consistency checking and program synthesis
• RESTful API: Complete REST API for system interaction and monitoring
• Real-time Monitoring: Comprehensive system status and metrics
• Scalable Infrastructure: Redis-based event bus and distributed task execution

Quick Start

Prerequisites

• Python 3.10+
• Redis server
• Docker (optional)

Installation

1. Clone the repository:

git clone https://github.com/aicubeKruz/project-prometheus.git
cd project-prometheus

2. Install dependencies:

pip install -r requirements.txt

3. Configure environment:

cp .env.example .env
# Edit .env with your configuration

4. Start Redis server:

# Using Docker
docker run -d -p 6379:6379 redis:latest

# Or install locally and start
redis-server

5. Run the API server:

python main.py

The API will be available at http://localhost:8000

API Documentation

Once running, visit:

• Interactive API docs: http://localhost:8000/docs
• Alternative docs: http://localhost:8000/redoc

Usage Examples

Initialize the System

# Setup agent hierarchy
curl -X POST "http://localhost:8000/api/v1/system/hierarchy/setup"

# Initialize project with mission
curl -X POST "http://localhost:8000/api/v1/system/initialize" \
  -H "Content-Type: application/json" \
  -d '{
    "mission": "Develop safe and aligned artificial general intelligence",
    "research_phases": [
      "architecture_design",
      "symbolic_reasoning_development", 
      "embodied_learning",
      "safety_validation"
    ]
  }'

Create and Execute Tasks

# Create a task
curl -X POST "http://localhost:8000/api/v1/tasks/" \
  -H "Content-Type: application/json" \
  -d '{
    "agent_id": "<agent-id>",
    "name": "Design Hybrid Architecture",
    "description": "Develop the neuro-symbolic hybrid core",
    "priority": "high"
  }'

# Execute task
curl -X POST "http://localhost:8000/api/v1/tasks/<task-id>/execute"

Monitor System Status

# Get system status
curl "http://localhost:8000/api/v1/system/status"

# Get agent hierarchy
curl "http://localhost:8000/api/v1/system/hierarchy"

# Trigger safety audit
curl -X POST "http://localhost:8000/api/v1/system/safety/audit"

Development

Project Structure

project_prometheus/
├── prometheus/
│   ├── core/                 # Core domain models and base classes
│   ├── agents/              # Specialized agent implementations
│   ├── api/                 # FastAPI routes and dependencies
│   ├── services/            # Business logic services
│   ├── infrastructure/      # External integrations (Redis, etc.)
│   └── config/              # Configuration management
├── tests/                   # Test suites
├── docs/                    # Documentation
└── scripts/                 # Utility scripts

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=prometheus tests/

# Run specific test category
pytest tests/unit/
pytest tests/integration/

Code Quality

# Format code
black prometheus/
isort prometheus/

# Type checking
mypy prometheus/

# Linting
flake8 prometheus/

Configuration

Key configuration options in .env:

• API_KEY_REQUIRED: Enable API key authentication
• SAFETY_CHECKS_ENABLED: Enable safety monitoring
• MAX_AGENTS: Maximum number of agents
• SIMULATION_ENABLED: Enable simulation environments
• LOG_LEVEL: Logging verbosity

Safety Considerations

Project Prometheus implements multiple safety layers:

1. Themis Agent: Continuous safety monitoring and veto power
2. Hierarchical Control: Structured oversight and coordination
3. Formal Verification: Logical consistency checking
4. Emergency Halt: System-wide shutdown capability
5. Rate Limiting: API request throttling
6. Input Validation: Comprehensive parameter validation

Contributing

1. Fork the repository
2. Create a feature branch
3. Make changes with tests
4. Run code quality checks
5. Submit pull request

License

This project is licensed under the MIT License with additional safety considerations - see the LICENSE file for details.

Safety Notice: This system is designed for AGI research. Always ensure proper safety measures and monitoring are in place.

Support

For questions and support:

• Repository: https://github.com/aicubeKruz/project-prometheus
• Documentation: See DEPLOYMENT.md for deployment guide
• Contributing: See CONTRIBUTING.md for development guidelines
• Issues: Use GitHub issues
• API Reference: Available at /docs endpoint when running

Roadmap

• Advanced neural architecture implementation
• Enhanced simulation environments
• Distributed agent deployment
• Advanced safety mechanisms
• Integration with external AI models
• Performance optimization
• Comprehensive monitoring dashboard

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Note: This is a research system for AGI development. Use responsibly and ensure proper safety measures are in place.