docker-compose.yml

version: "3.8"

# Docker Compose configuration for Trading System
# This orchestrates the trading bot and dashboard services

services:
  # Go ADK Service (High-speed execution)
  adk_service:
    build:
      context: ./go/adk_trading
      dockerfile: Dockerfile
    container_name: adk-service
    env_file:
      - .env
    ports:
      - "8080:8080"
      - "8091:8091"
    volumes:
      - ./data:/app/data
      - ./logs:/app/logs
    restart: unless-stopped
    networks:
      - trading-network
    healthcheck:
      test: ["CMD", "wget", "--spider", "-q", "http://localhost:8091/healthz"]
      interval: 10s
      timeout: 5s
      retries: 3

  # Main trading bot service
  trading_bot:
    build:
      context: .
      dockerfile: Dockerfile
      target: production
    container_name: trading-bot

    # Load environment variables from .env file
    # Create this file from .env.example with your actual API keys
    env_file:
      - .env

    # Additional environment variables
    environment:
      - PYTHONUNBUFFERED=1
      - ADK_BASE_URL=http://adk-service:8080/api
      - LOG_LEVEL=${LOG_LEVEL:-INFO}
      - TRADING_MODE=${TRADING_MODE:-paper}
      - TZ=${TZ:-America/New_York}

    # Mount volumes for persistent data
    volumes:
      # Trading data: positions, history, cache
      - ./data:/app/data
      # Application logs
      - ./logs:/app/logs
      # Mount source code for development (comment out in production)
      # - ./src:/app/src:ro

    # Restart policy: always restart unless explicitly stopped
    restart: unless-stopped

    # Resource limits to prevent container from consuming too much
    deploy:
      resources:
        limits:
          cpus: "2"
          memory: 2G
        reservations:
          cpus: "0.5"
          memory: 512M

    # Health check configuration
    healthcheck:
      test: ["CMD", "pgrep", "-f", "python.*main.py"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

    # Logging configuration
    logging:
      driver: "json-file"
      options:
        max-size: "10m"
        max-file: "3"

    depends_on:
      adk_service:
        condition: service_healthy

    # Network configuration
    networks:
      - trading-network

  # Dashboard service (Streamlit)
  dashboard:
    build:
      context: .
      dockerfile: Dockerfile
      target: production
    container_name: trading-dashboard

    # Override entrypoint to run Streamlit instead of main.py
    command:
      [
        "streamlit",
        "run",
        "dashboard/app.py",
        "--server.port=8501",
        "--server.address=0.0.0.0",
      ]

    # Load environment variables
    env_file:
      - .env

    environment:
      - PYTHONUNBUFFERED=1
      - TZ=${TZ:-America/New_York}

    # Mount volumes (read-only for data safety)
    volumes:
      # Read-only access to trading data
      - ./data:/app/data:ro
      # Read-only access to logs
      - ./logs:/app/logs:ro
      # Mount dashboard code for hot reload in development
      # - ./dashboard:/app/dashboard:ro

    # Expose Streamlit port
    ports:
      - "8501:8501"

    # Restart policy
    restart: unless-stopped

    # Resource limits
    deploy:
      resources:
        limits:
          cpus: "1"
          memory: 1G
        reservations:
          cpus: "0.25"
          memory: 256M

    # Health check for Streamlit
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8501/_stcore/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 60s

    # Logging configuration
    logging:
      driver: "json-file"
      options:
        max-size: "10m"
        max-file: "3"

    # Depends on trading bot (optional - can run independently)
    depends_on:
      trading_bot:
        condition: service_healthy

    # Network configuration
    networks:
      - trading-network

  # Hindsight Memory Service (Optional - Agentic Memory for Trade Learning)
  # See: https://github.com/vectorize-io/hindsight
  hindsight:
    image: ghcr.io/vectorize-io/hindsight:latest
    container_name: hindsight-memory

    # Environment configuration
    environment:
      # Uses OpenRouter API key (same as trading system)
      - HINDSIGHT_API_LLM_API_KEY=${OPENROUTER_API_KEY}
      - HINDSIGHT_API_LLM_MODEL=openai/gpt-4o-mini

    # Expose API and UI ports
    ports:
      - "8888:8888" # API
      - "9999:9999" # UI

    # Persistent storage for memory banks
    volumes:
      - hindsight_data:/home/hindsight/.pg0

    # Resource limits (memory system is lightweight)
    deploy:
      resources:
        limits:
          cpus: "1"
          memory: 1G
        reservations:
          cpus: "0.25"
          memory: 256M

    # Health check - verify API is responding
    healthcheck:
      test: ["CMD", "wget", "--spider", "-q", "http://localhost:8888/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 60s

    # Restart policy
    restart: unless-stopped

    # Logging configuration
    logging:
      driver: "json-file"
      options:
        max-size: "10m"
        max-file: "3"

    # Network configuration
    networks:
      - trading-network

    # Profile: only start when explicitly requested
    # Use: docker compose --profile memory up
    profiles:
      - memory

# Define networks
networks:
  trading-network:
    driver: bridge
    name: trading-network

# Named volumes for persistent data
volumes:
  hindsight_data:
    driver: local
  # trading_data:
  #   driver: local
  # trading_logs:
  #   driver: local