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MNKY Agents Demo

MNKY Agents Demo is a Python FastAPI application that demonstrates agent interaction patterns and provides a testing environment for the MOOD MNKY agent framework. This application serves as a reference implementation and development tool for agent-based features.

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Overview

The MNKY Agents Demo provides a lightweight, Python-based implementation of agent interactions, making it easy to test agent capabilities, experiment with prompts, and develop agent features without the complexity of the full Next.js ecosystem.

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Key Features

  • FastAPI Framework: Modern Python web framework for API development
  • Agent Integration: Demonstrates integration with MOOD, CODE, and SAGE agents
  • Testing Environment: Isolated environment for agent development
  • Docker Support: Containerized deployment for easy setup
  • API Endpoints: RESTful API for agent interactions

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Architecture

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Technology Stack

  • Framework: FastAPI (Python)
  • API: RESTful API with OpenAPI documentation
  • Containerization: Docker and Docker Compose
  • Deployment: Docker containers, cloud platforms

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Application Structure

apps/mnky-agents-demo/
├── api/                      # FastAPI application
│   ├── main.py              # Application entry point
│   ├── router.py             # API route definitions
│   └── routes/               # Individual route handlers
├── static/                   # Static files (HTML, CSS)
├── Dockerfile                # Docker configuration
├── docker-compose.yml        # Docker Compose setup
├── requirements.txt          # Python dependencies
└── pyproject.toml           # Project configuration

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Getting Started

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Prerequisites

  • Python 3.9+
  • Docker and Docker Compose (optional)
  • Environment variables configured

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Setup

  1. Navigate to application directory: 
    cd apps/mnky-agents-demo
  2. Install dependencies: 
    pip install -r requirements.txt
  3. Configure environment variables: Create .env: 
    OPENAI_API_KEY=<your-openai-key>
SUPABASE_URL=<your-supabase-url>
SUPABASE_KEY=<your-supabase-key>
  4. Run application: 
    python -m api.main
# Or
uvicorn api.main:app --reload
  5. Access API: http://localhost:8000
  6. API Docs: http://localhost:8000/docs

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Docker Setup

# Build and run with Docker Compose
docker-compose up --build

# Run in background
docker-compose up -d

# View logs
docker-compose logs -f

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API Endpoints

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Agent Interactions

  • POST /api/agents/mood - Interact with MOOD MNKY agent
  • POST /api/agents/code - Interact with CODE MNKY agent
  • POST /api/agents/sage - Interact with SAGE MNKY agent

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Health & Status

  • GET /health - Health check endpoint
  • GET /status - Application status
See API Documentation for full endpoint details.

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Development

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Running Tests

# Run all tests
pytest

# Run specific test file
pytest tests/test_agents.py

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

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Code Quality

# Format code
black api/

# Lint code
flake8 api/

# Type checking
mypy api/

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Docker Deployment

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Build Image

docker build -t mnky-agents-demo .

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Run Container

docker run -p 8000:8000 \
  -e OPENAI_API_KEY=<key> \
  -e SUPABASE_URL=<url> \
  mnky-agents-demo