An advanced AI system built on the Mastra framework, featuring sophisticated cognitive capabilities, memory processing, and multi-agent orchestration. This project integrates cognitive skills from ai-opencog with modern AI infrastructure to create a powerful, self-evolving AI ecosystem.

• 🧠 Cognitive Skills: Advanced reasoning, code analysis, production optimization, and adaptive learning
• 💭 Memory System: Semantic, episodic, and wisdom memory repositories with automated processing
• 🤖 Deep Tree Echo Agent: Conversational AI with memory-enhanced responses
• ⚡ Workflow Orchestration: Automated daily, weekly, and monthly memory processing

• 🏗️ Mastra Framework: Modern TypeScript-based agent framework
• 📊 PostgreSQL + pgvector: Vector-enabled database for memory storage
• ⏰ Inngest Integration: Workflow scheduling and observability
• 🌐 Web Interface: Remix-based EchoSelf app with AI chat and visualization
• 🔗 Multi-platform: Slack and Telegram integrations

deep-tree-echo-mast/
├── src/
│   ├── mastra/                 # Mastra framework configuration
│   │   ├── agents/            # AI agents (Deep Tree Echo Agent)
│   │   ├── tools/             # Memory and conversation tools
│   │   ├── workflows/         # Automated memory processing
│   │   └── index.ts           # Main Mastra configuration
│   ├── skills/                # Cognitive capabilities
│   │   ├── cognitive/         # Code analysis and reasoning
│   │   ├── learning/          # Adaptive learning systems
│   │   ├── nanocog/          # Meta-cognitive orchestration
│   │   └── optimization/      # Production optimization
│   └── triggers/              # External integrations (Slack, Telegram)
├── echoself/                  # Remix web application
└── scripts/                   # Build and deployment scripts

• Node.js >= 20.9.0
• PostgreSQL with pgvector extension
• OpenAI API key (or compatible provider)

1. Clone the repository

   git clone https://github.com/drzo/deep-tree-echo-mast.git
   cd deep-tree-echo-mast

2. Install dependencies

   npm ci

3. Configure environment

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

4. Set up database

   # Ensure PostgreSQL with pgvector is running
   # Database will be automatically initialized

5. Start the development server

   npm run dev

# AI Configuration
OPENAI_API_KEY=your_openai_api_key
OPENAI_BASE_URL=https://api.openai.com/v1  # Optional

# Database
DATABASE_URL=postgresql://localhost:5432/mastra

# Scheduling (optional)
SCHEDULE_CRON_TIMEZONE=America/Los_Angeles
SCHEDULE_CRON_EXPRESSION=0 2 * * *

# External Integrations (optional)
SLACK_BOT_TOKEN=your_slack_token
TELEGRAM_BOT_TOKEN=your_telegram_token

# Start development server
npm run dev

# Type checking
npm run check

# Code formatting
npm run format
npm run check:format

# Testing
npm run test
npm run test:watch
npm run test:coverage

# Build for production
npm run build

# Terminal 1: Start Mastra dev server
npm run dev

# Terminal 2: Start Inngest dev server (for workflows)
npx inngest-cli@latest dev

• Chat API: POST /api/chat - Interact with Deep Tree Echo Agent
• Inngest: /api/inngest - Workflow management and scheduling

const response = await fetch('/api/chat', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({
    message: "Hello, can you help me analyze some code?",
    sessionId: "optional-session-id"
  })
});

const data = await response.json();
console.log(data.response);

The system includes advanced cognitive capabilities:

• Intelligent code quality analysis
• Pattern recognition and anti-pattern detection
• Maintainability scoring and suggestions

• Multi-step logical reasoning
• Problem decomposition and synthesis
• Contextual decision making

• Performance monitoring and optimization
• Resource usage analysis
• System health diagnostics

• Self-improving algorithms
• Pattern learning from interactions
• Behavioral adaptation over time

The Deep Tree Echo Agent maintains sophisticated memory:

• Semantic Memory: Factual knowledge and concepts
• Episodic Memory: Conversation history and experiences
• Wisdom Memory: Learned insights and patterns
• Working Memory: Active context and recent interactions

Memory processing runs automatically:

• Daily: Parse and categorize new interactions
• Weekly: Process and consolidate memories
• Monthly: Generate insights and wisdom

The EchoSelf web application provides:

• Interactive chat with the AI agent
• Memory visualization and exploration
• System monitoring and analytics
• Multi-platform integration management

• Mastra Framework: Core AI agent infrastructure
• Cognitive Skills: Extracted from ai-opencog project
• Memory Processing: Automated workflows for memory management
• Web Interface: Remix application in echoself/ directory

# Run all tests
npm run test

# Run cognitive skills tests specifically  
npm run test:skills

# Watch mode for development
npm run test:watch

# Coverage report
npm run test:coverage

1. Create skill file in src/skills/[category]/
2. Implement using Mastra Tool interface
3. Add to exports in src/skills/index.ts
4. Register in src/mastra/index.ts
5. Add tests in src/skills/tests/

• COGNITIVE_SKILLS_README.md - Detailed cognitive capabilities
• WARP.md - Development workflow and commands
• docs-mastra.md - Mastra framework documentation
• next-steps-nanocog.md - Future development roadmap
• echoself/README.md - Web interface documentation

npm run build

• Node.js 20.9.0+
• PostgreSQL with pgvector
• Persistent storage for memory
• Environment variables configured

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Run type checking and formatting
6. Submit a pull request

ISC License - see package.json for details

• Mastra Framework - AI agent framework
• ai-opencog - Source of cognitive skills
• Inngest - Workflow scheduling platform

Deep Tree Echo Mast - Where AI meets consciousness, memory meets wisdom, and code meets cognitive evolution. 🌳✨