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System Overview

The Docker Cerebras demo showcases a sophisticated multi-agent system designed for Node.js programming assistance. Understanding the architecture and components will help you make the most of this workshop.

System Architecture

Multi-Agent Architecture

The system consists of three specialized agents orchestrated through Docker Compose, each with distinct roles and capabilities for comprehensive programming assistance.

Agent Roles and Responsibilities

🦆 DevDuck - The Coordinator

  • Model: Qwen3 (unsloth/qwen3-gguf:4B-UD-Q4_K_XL)
  • Role: Main development assistant and project coordinator
  • Capabilities: Routes requests to appropriate sub-agents based on user needs
  • Function: Acts as the central hub for user interactions

💻 Local Agent - Development Expert

  • Model: Qwen2.5 (ai/qwen2.5:latest)
  • Role: General development tasks and project coordination
  • Specialization: Node.js programming expert for understanding code, explaining concepts, and generating code snippets
  • Function: Handles standard development queries and code generation

🧠 Cerebras Agent - Advanced Computing

  • Model: Llama-4 Scout (llama-4-scout-17b-16e-instruct)
  • Provider: Cerebras API
  • Specialization: Complex Node.js problem-solving scenarios requiring advanced reasoning
  • Function: Handles complex computational tasks and advanced problem-solving

Docker Compose's Central Role

Docker Compose serves as the backbone of this multi-agent system:

🚀 Service Orchestration

  • Manages the lifecycle of all three agents
  • Handles startup and shutdown sequences
  • Ensures proper dependency management

⚙️ Configuration Management

  • Defines agent prompts and behaviors
  • Manages model configurations
  • Sets service dependencies

🌐 Network Coordination

  • Establishes secure inter-agent communication channels
  • Creates isolated network environments
  • Manages port mappings and exposure

🔐 Environment Management

  • Handles API keys and secrets
  • Manages model parameters
  • Controls runtime configurations

Key Features

  1. Multi-agent coordination: Intelligent routing between specialized agents based on task requirements

  2. Node.js programming expertise: All agents specialize in Node.js development with comprehensive knowledge

  3. FastAPI web interface: RESTful API with intuitive web interface for seamless interaction

  4. Docker containerization: Easy deployment and scaling with Docker Compose

  5. Flexible model configuration: Support for multiple LLM providers (local and cloud) with easy configuration

  6. Token streaming: Real-time response streaming for better user experience

Use Cases and Applications

This system excels in scenarios requiring:

🔧 Development Tasks

  • Code generation and explanation
  • Project coordination and planning
  • Code analysis and optimization
  • Testing strategy development

🎓 Learning and Support

  • Educational programming assistance
  • Complex problem-solving guidance
  • Best practices recommendations
  • Real-time programming help

Workshop Journey

What's Next?

In the following sections, you'll:

  1. Set up the complete development environment
  2. Deploy the multi-agent system using Docker Compose
  3. Learn to interact with each agent effectively
  4. Practice real-world programming scenarios
  5. Explore advanced features and customization options

Architecture Diagram

graph TB
    User[User Interface] --> DevDuck[DevDuck Coordinator]
    DevDuck --> LocalAgent[Local Agent]
    DevDuck --> CerebrasAgent[Cerebras Agent]
    LocalAgent --> Docker[Docker Compose]
    CerebrasAgent --> Docker
    DevDuck --> Docker
    Docker --> FastAPI[FastAPI Web Interface]
    CerebrasAgent --> CerebrasAPI[Cerebras API]