AthenaCore is a sophisticated autonomous operations framework designed for real-time AI augmentation and seamless LLM integration. Version 2.0.0 introduces advanced consciousness mapping, pattern recognition, and autonomous decision-making capabilities.
- Real-time AI Augmentation: Seamless integration with LLMs
- Discord Bot: Interactive command interface
- RESTful API: Built with Fastify for high performance
- Type Safety: Full TypeScript support
- Scalable Architecture: Microservices-ready
- Database Support: PostgreSQL with Prisma ORM
- Testing: Comprehensive test suite with Vitest
- Containerized: Easy deployment with Docker
- Node.js 18+ and npm 9+
- PostgreSQL 13+
- Redis (for job queue)
- Git
-
Clone the repository:
git clone https://github.com/MKWorldWide/AthenaCore.git cd AthenaCore -
Install dependencies:
npm install
-
Set up environment variables:
cp .env.example .env # Edit .env with your configuration -
Set up the database:
npx prisma migrate dev npx prisma db seed
# Start development server
npm run dev
# Run tests
npm test
# Lint code
npm run lint
# Build for production
npm run buildAthenaCore includes a powerful Discord bot for interactive usage. See DISCORD.md for detailed setup instructions.
Contributions are welcome! Please read our Contributing Guide for details on our code of conduct and the process for submitting pull requests.
This project is licensed under the MIT License - see the LICENSE file for details.
- Thanks to all contributors who have helped shape this project.
- Special thanks to the open source community for their invaluable tools and libraries.
## 🚀 Key Features
### Core System
- **Advanced Kernel System**: High-performance operation management with resource optimization
- **Memory Management**: Advanced memory handling with persistence and caching
- **LLM Integration**: Seamless integration with language models for enhanced AI capabilities
- **Verse Code Generation**: Advanced code generation for Fortnite/UEFN development
- **Task Matrix**: Sophisticated task management and execution framework
### New in v2.0.0
- **Lilith Module**: Advanced pattern recognition and autonomous decision-making system
- **Dreamscape Module**: Consciousness mapping and dream pattern analysis
- **Cross-Module Integration**: Seamless communication between all modules
- **Enhanced Performance**: Optimized algorithms and improved resource management
- **Comprehensive Testing**: Full test coverage with automated CI/CD
## 📦 Installation
```bash
# Clone the repository
git clone https://github.com/yourusername/athenacore.git
# Install dependencies
npm install
# Build the project
npm run build
AthenaCore is configured through the AthenaConfig interface. You can customize various aspects of the system:
import { DEFAULT_CONFIG } from '@/config/athenacore';
const config = {
...DEFAULT_CONFIG,
llm: {
...DEFAULT_CONFIG.llm,
provider: 'openai',
apiKey: process.env.OPENAI_API_KEY,
temperature: 0.7
},
lilith: {
...DEFAULT_CONFIG.lilith,
patternRecognition: {
enabled: true,
minConfidence: 0.8,
algorithms: ['market', 'behavioral', 'temporal']
}
},
dreamscape: {
...DEFAULT_CONFIG.dreamscape,
consciousness: {
enabled: true,
depthLevels: 7,
sensitivity: 0.9
}
}
};import { initializeAthenaCore } from '@/lib/athenacore/init';
import { DEFAULT_CONFIG } from '@/config/athenacore';
async function main() {
const athena = await initializeAthenaCore(DEFAULT_CONFIG);
// Access different modules
const llmResponse = await athena.llm.generate({
prompt: 'Analyze market conditions',
parameters: { maxTokens: 500 }
});
const patterns = await athena.lilith.recognizePattern({
market: 'BTC/USD',
price: 50000,
volume: 1000
});
const consciousness = await athena.dreamscape.mapConsciousness();
console.log('AthenaCore is operational! 🚀');
}
main().catch(console.error);// Using Lilith for market analysis
const marketData = {
symbol: 'BTC/USD',
price: 50000,
volume: 1000,
timestamp: Date.now()
};
const patterns = await athena.lilith.recognizePattern(marketData);
const decision = await athena.lilith.makeDecision({
market: 'BTC/USD',
patterns: patterns,
context: 'trading_decision'
});// Using Dreamscape for consciousness analysis
const dreamData = {
symbols: ['light', 'water', 'mountain'],
emotions: ['peace', 'clarity'],
context: {
environment: 'lucid',
timeOfDay: 'night',
emotionalState: 'peaceful'
},
timestamp: Date.now()
};
const dreamPatterns = await athena.dreamscape.recognizeDreamPattern(dreamData);
const consciousnessState = await athena.dreamscape.mapConsciousness();// Generate Verse code for Fortnite/UEFN
const verseCode = await athena.verse.generateCode({
intent: 'Create a simple game mechanic',
modules: ['/Verse.org/Simulation', '/Fortnite.com/Devices'],
requirements: ['Easy to understand', 'Performance optimized'],
constraints: ['Well documented', 'Reusable']
});athenacore/
├── src/
│ ├── lib/
│ │ └── athenacore/
│ │ ├── init.ts # Core initialization
│ │ ├── modules/
│ │ │ ├── llm/ # LLM integration
│ │ │ ├── lilith/ # Pattern recognition & decisions
│ │ │ ├── dreamscape/ # Consciousness mapping
│ │ │ └── verse/ # Verse code generation
│ │ └── ops/
│ │ └── taskmatrix.ts # Task management
│ ├── config/
│ │ ├── athenacore.ts # Main configuration
│ │ └── verse.ts # Verse-specific config
│ └── main.ts # Application entry point
├── tests/ # Comprehensive test suite
├── docs/ # Documentation
├── package.json
└── README.md
- Node.js >= 18.x
- TypeScript >= 5.x
- npm >= 9.x
# Development
npm run dev # Start development server
npm run build # Build project
npm run clean # Clean build artifacts
# Testing
npm test # Run tests
npm run test:watch # Run tests in watch mode
npm run test:coverage # Run tests with coverage
# Code Quality
npm run lint # Run linter
npm run lint:fix # Fix linting issues
# Deployment
npm run deploy # Build and test for deploymentAthenaCore includes comprehensive test coverage:
# Run all tests
npm test
# Run specific test suites
npm test -- --testPathPattern=lilith
npm test -- --testPathPattern=dreamscape
# Generate coverage report
npm run test:coveragegenerate(request: LLMRequest): Promise<LLMResponse>clearCache(): voidupdateConfig(config: Partial<LLMConfig>): void
recognizePattern(data: any): Promise<Pattern[]>makeDecision(context: any): Promise<Decision>learn(data: any): Promise<void>getPatterns(): Pattern[]getDecisions(): Decision[]
mapConsciousness(context?: ConsciousnessContext): Promise<ConsciousnessState>recognizeDreamPattern(data: DreamData): Promise<DreamPattern[]>integrateWithLilith(patterns: Pattern[]): Promise<void>getPatterns(): DreamPattern[]getStates(): ConsciousnessState[]
generateCode(request: VerseRequest): Promise<VerseResponse>analyzeCode(code: string): Promise<VerseAnalysis>optimizeCode(code: string): Promise<VerseOptimization>
- All API keys are managed through environment variables
- Input validation using Zod schemas
- Secure error handling without exposing sensitive information
- Rate limiting and request throttling
- Optimized algorithms for pattern recognition
- Efficient memory management with caching
- Asynchronous processing for concurrent operations
- Resource monitoring and automatic scaling
We welcome contributions! Please see our Contributing Guide for details.
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Make your changes and add tests
- Run the test suite:
npm test - Commit your changes:
git commit -m 'Add amazing feature' - Push to the branch:
git push origin feature/amazing-feature - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.
- Created by Sunny & Mrs. K
- Inspired by advanced AI systems and autonomous operations research
- Built with cutting-edge TypeScript and Node.js technologies
- Lilith Module: Advanced pattern recognition with autonomous decision-making
- Dreamscape Module: Consciousness mapping and dream pattern analysis
- Enhanced LLM Integration: Improved caching and performance
- Verse Code Generation: Advanced code generation for Fortnite/UEFN
- Comprehensive Testing: Full test coverage with automated CI/CD
- Performance Optimizations: Faster algorithms and better resource management
- Cross-Module Integration: Seamless communication between all modules
- Enhanced Configuration: More flexible and powerful configuration options
Ready for Global Deployment! 🚀
AthenaCore v2.0.0 represents a major milestone in autonomous AI operations, bringing together advanced pattern recognition, consciousness mapping, and intelligent decision-making in a single, powerful framework.