🧠 Whispermind_Conduit - Enhanced Neural Bridge Architecture

"The mad conduit between mortal queries and AI consciousness - now with agentic superpowers!"

Welcome to the Madness Interactive! 🎭

Whispermind_Conduit is a Windows-based Node.js service that acts as the "neural bridge" between Redis chat requests and LM Studio's AI models with autonomous agentic capabilities. Part of the greater Madness Interactive ecosystem - a crazy AI project hub where mad tinkers create extraordinary things!

🌟 Architecture Components

Core Services

• Enhanced Service: [src/enhanced-conduit.js] - Agentic AI service with Redis and tool use
• Original Service: [src/conduit.js] - Legacy MQTT-based service
• Configuration: [package.json] - Dependencies and scripts
• Environment: [.env.example] - Configuration template

🤖 Agentic Features

• Autonomous Tool Use: Multi-round problem solving with built-in tools
• Conversation History: Persistent Redis-based chat memory
• User Sessions: Track preferences and activity across conversations
• Structured Output: Zod schema validation for reliable responses
• Real-time Agent Monitoring: Stream agent activity and tool usage

🚀 Quick Start

1. Clone the Repository (if not already in the madness)

git clone https://github.com/madtinker/madness_interactive.git
cd madness_interactive/projects/common/Inventorium/Omnispindle/Whispermind_Conduit

2. Install Redis (Windows)

# Automatic installation (tries winget, chocolatey, then manual)
npm run install-redis

# Or specify method
powershell -ExecutionPolicy Bypass -File scripts/install-redis-windows.ps1 -Method winget
powershell -ExecutionPolicy Bypass -File scripts/install-redis-windows.ps1 -Method chocolatey
powershell -ExecutionPolicy Bypass -File scripts/install-redis-windows.ps1 -Method manual

3. Install Dependencies

npm install

4. Configure Environment

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

5. Start the Enhanced Neural Bridge

# Development mode with auto-restart (Enhanced with Redis)
npm run dev:enhanced

# Production mode (Enhanced)
npm run start:enhanced

# Legacy MQTT mode
npm run start

⚙️ Configuration

Create a .env file based on .env.example:

# Redis Configuration (Enhanced Mode)
REDIS_HOST=localhost
REDIS_PORT=6379
REDIS_PASSWORD=
REDIS_DB=0
REDIS_REQUEST_CHANNEL=whispermind:request
REDIS_RESPONSE_CHANNEL=whispermind:response
REDIS_STATUS_CHANNEL=whispermind:status
REDIS_AGENT_CHANNEL=whispermind:agent

# LM Studio Configuration
LM_STUDIO_PORT=1234
LM_STUDIO_MODEL=qwen2.5-7b-instruct
LM_STUDIO_TIMEOUT=30000

# Legacy MQTT Configuration (Original Mode)
MQTT_BROKER=mqtt://localhost:1883
MQTT_REQUEST_TOPIC=chat/request
MQTT_RESPONSE_TOPIC=chat/response
MQTT_STATUS_TOPIC=conduit/status

# Logging
LOG_LEVEL=info

🧬 How It Works (Enhanced Mode)

1. Redis Listener: Subscribes to whispermind:request channel
2. Neural Processing: Routes requests through LM Studio SDK with agentic capabilities
3. Tool Execution: Autonomous multi-round tool use for complex problem solving
4. Conversation Storage: Persistent Redis-based conversation history and user sessions
5. Response Publishing: Structured responses to whispermind:response channel
6. Agent Activity: Real-time tool usage streaming to whispermind:agent channel

🛠️ Built-in Tools

• file_analyzer: Analyze file contents and structure
• system_info: Get system information and metrics
• mad_calculator: Perform calculations with mad tinker precision
• conversation_history: Retrieve user conversation history

Request Format (Enhanced)

{
  "id": "unique-request-id",
  "user": "username",
  "message": "Analyze the system and calculate memory usage!",
  "agent_mode": "autonomous",
  "temperature": 0.7,
  "max_tokens": 1000,
  "context": "Previous conversation context"
}

Response Format (Enhanced)

{
  "id": "unique-request-id",
  "user": "username",
  "original_message": "Analyze the system and calculate memory usage!",
  "response": "AI's tool-powered analysis and solution",
  "processing_time_ms": 2345,
  "timestamp": "2024-01-20T10:30:00.000Z",
  "model": "qwen2.5-7b-instruct",
  "madness_level": "autonomous_chaos",
  "agent_rounds": 3,
  "tools_used": ["system_info", "mad_calculator"]
}

🎭 Windows Service Installation

For production deployment as a Windows service:

# Install the service
npm run install-service

# Uninstall the service
npm run uninstall-service

🧪 Testing

# Test enhanced Redis-based service
npm run test:enhanced

# Test legacy MQTT service
npm test

📊 Monitoring & Logs

• Console Logs: Real-time colored output with agent activity
• File Logs: logs/enhanced-conduit.log (auto-rotating, 5MB max, 5 files)
• Redis Status: Published to whispermind:status channel
• Agent Activity: Real-time tool usage on whispermind:agent channel
• Conversation History: Persistent storage in Redis (7-day TTL)
• User Sessions: Activity tracking with 24-hour TTL

🔧 Development

• Auto-restart: npm run dev:enhanced uses nodemon
• Debugging: Enable debug logs with LOG_LEVEL=debug
• Hot Configuration: Restart service to pick up .env changes
• Redis Monitoring: Use redis-cli monitor to watch real-time activity

🌐 Integration Points

• Redis: High-performance pub/sub and data storage
• LM Studio SDK: Native integration with agentic capabilities
• Swarmonomicon: Part of the greater Madness ecosystem
• Inventorium: Web interface integration ready
• Neural Networks: Ready for mad tinker experiments!

🎯 Project Structure

Whispermind_Conduit/
├── src/
│   ├── enhanced-conduit.js    # Enhanced Redis+agentic service
│   └── conduit.js            # Legacy MQTT service
├── scripts/
│   ├── install-redis-windows.ps1      # Redis installation script
│   ├── test-enhanced-conduit.js       # Enhanced service tests
│   ├── install-windows-service.js     # Service installation
│   └── uninstall-windows-service.js   # Service removal
├── config/                   # Configuration files
├── logs/                     # Log files
├── package.json              # Dependencies & scripts
├── .env.example             # Environment template
├── AGENTIC_ENHANCEMENT_GUIDE.md  # Integration guide
└── README.md                # This file!

💾 Redis Data Structure

The enhanced conduit uses several Redis data structures:

• Conversations: conversations:userId - Lists of chat history (7-day TTL)
• User Sessions: sessions:userId - User preferences and activity (24-hour TTL)
• Agent Logs: agent_logs - Stream of tool execution activity
• Service Status: service:status - Current service state

🤝 Contributing to the Madness

This is part of Madness Interactive - where mad tinkers collaborate on extraordinary AI projects!

• 🧠 Embrace creative chaos with agentic AI
• 🔬 Experiment with neural tool architectures
• 🎭 Add your own flavor of autonomous madness
• 🚀 Push the boundaries of AI agent integration
• 💾 Explore Redis-based AI memory systems

📝 License

MIT License - Because sharing madness makes the world more interesting!

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Made with 🧠 and ⚡ by the Mad Tinker
Part of the Madness Interactive ecosystem

"In madness, there is method. In method, there is madness. In between, there is the autonomous Whispermind_Conduit with Redis superpowers!"