docker-compose.yml

# ==============================================================================
# ARLA Project Docker Compose - Optimized for Development
# ==============================================================================

services:
  # Main application service
  app:
    build:
      context: .
      dockerfile: Dockerfile
      args:
        BUILDKIT_INLINE_CACHE: 1
    volumes:
      # Source code volumes for live development
      - ./agent-core/src:/app/agent-core/src:rw
      - ./agent-engine/src:/app/agent-engine/src:rw
      - ./agent-sim/src:/app/agent-sim/src:rw
      - ./agent-concurrent/src:/app/agent-concurrent/src:rw
      - ./agent-persist/src:/app/agent-persist/src:rw
      - ./simulations:/app/simulations:rw

      # Configuration and dependency files
      - ./pyproject.toml:/app/pyproject.toml:ro
      - ./poetry.lock:/app/poetry.lock:ro
      - ./agent-core/pyproject.toml:/app/agent-core/pyproject.toml:ro
      - ./agent-engine/pyproject.toml:/app/agent-engine/pyproject.toml:ro
      - ./agent-sim/pyproject.toml:/app/agent-sim/pyproject.toml:ro
      - ./agent-concurrent/pyproject.toml:/app/agent-concurrent/pyproject.toml:ro
      - ./agent-persist/pyproject.toml:/app/agent-persist/pyproject.toml:ro

      # Data and output directories
      - ./data:/app/data:rw
      - ./mlruns:/app/mlruns:rw

      # Scripts and utilities
      - ./scripts:/app/scripts:rw

      # Preserve virtual environment and cache
      - poetry_venv:/app/.venv
      - poetry_cache:/opt/poetry-cache
    env_file:
      - .env
    environment:
      PYTHONPATH: "/app/agent-core/src:/app/agent-engine/src:/app/agent-sim/src:/app/agent-concurrent/src:/app/agent-persist/src:/app/simulations"
      PYTHONDONTWRITEBYTECODE: 1
      PYTHONUNBUFFERED: 1
    depends_on:
      db:
        condition: service_healthy
      redis:
        condition: service_healthy
      mlflow:
        condition: service_healthy
    networks:
      - arla_network
    healthcheck:
      test: ["CMD", "python", "-c", "import agent_sim; print('OK')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

  # Celery worker service
  worker:
    build:
      context: .
      dockerfile: Dockerfile
      args:
        BUILDKIT_INLINE_CACHE: 1
    command: >
      sh -c "
        echo 'Starting Celery worker...' &&
        /opt/poetry/bin/poetry run agentsim start-worker -Q 'experiments,simulations' -c 4
      "
    volumes:
      # Same volumes as app for consistency
      - ./agent-core/src:/app/agent-core/src:rw
      - ./agent-engine/src:/app/agent-engine/src:rw
      - ./agent-sim/src:/app/agent-sim/src:rw
      - ./agent-concurrent/src:/app/agent-concurrent/src:rw
      - ./agent-persist/src:/app/agent-persist/src:rw
      - ./simulations:/app/simulations:rw
      - ./pyproject.toml:/app/pyproject.toml:ro
      - ./poetry.lock:/app/poetry.lock:ro
      - ./agent-core/pyproject.toml:/app/agent-core/pyproject.toml:ro
      - ./agent-engine/pyproject.toml:/app/agent-engine/pyproject.toml:ro
      - ./agent-sim/pyproject.toml:/app/agent-sim/pyproject.toml:ro
      - ./agent-concurrent/pyproject.toml:/app/agent-concurrent/pyproject.toml:ro
      - ./agent-persist/pyproject.toml:/app/agent-persist/pyproject.toml:ro
      - ./data:/app/data:rw
      - ./mlruns:/app/mlruns:rw
      - poetry_venv:/app/.venv
      - poetry_cache:/opt/poetry-cache
    env_file:
      - .env
    environment:
      PYTHONPATH: "/app/agent-core/src:/app/agent-engine/src:/app/agent-sim/src:/app/agent-concurrent/src:/app/agent-persist/src:/app/simulations"
      PYTHONDONTWRITEBYTECODE: 1
      PYTHONUNBUFFERED: 1
    depends_on:
      db:
        condition: service_healthy
      redis:
        condition: service_healthy
      mlflow:
        condition: service_healthy
    networks:
      - arla_network
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "python", "-c", "import agent_sim; print('OK')"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 40s

  # PostgreSQL database
  db:
    image: postgres:15-alpine
    volumes:
      - postgres_data:/var/lib/postgresql/data/
    env_file:
      - .env
    ports:
      - "${POSTGRES_PORT:-5432}:5432"
    command: >
      postgres
      -c max_connections=400
      -c shared_buffers=128MB
      -c effective_cache_size=512MB
      -c maintenance_work_mem=64MB
      -c checkpoint_completion_target=0.9
      -c wal_buffers=16MB
      -c default_statistics_target=100
      -c random_page_cost=1.1
    networks:
      - arla_network
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U ${POSTGRES_USER:-postgres} -d ${POSTGRES_DB:-arla}"]
      interval: 10s
      timeout: 5s
      retries: 5
      start_period: 30s

  # Redis cache and message broker
  redis:
    image: redis:7.2-alpine
    ports:
      - "${REDIS_PORT:-6379}:6379"
    volumes:
      - redis_data:/data
    command: >
      redis-server
      --appendonly yes
      --appendfsync everysec
      --maxmemory 256mb
      --maxmemory-policy allkeys-lru
    networks:
      - arla_network
    healthcheck:
      test: ["CMD", "redis-cli", "ping"]
      interval: 10s
      timeout: 3s
      retries: 5
      start_period: 10s

  # MLflow experiment tracking
  mlflow:
    image: ghcr.io/mlflow/mlflow:v2.14.1
    ports:
      - "${MLFLOW_PORT:-5001}:5000"
    volumes:
      - ./mlruns:/mlruns:rw
    env_file:
      - .env
    environment:
      MLFLOW_AUTH_CONFIG_PATH: /auth_config.ini
    command:
      - bash
      - -c
      - |
        set -e
        echo "Installing dependencies..."
        apt-get update && apt-get install -y --no-install-recommends curl libpq-dev
        pip install --no-cache-dir psycopg2-binary

        echo "Creating auth config..."
        cat > /auth_config.ini << 'EOF'
        [mlflow]
        admin_username = admin
        admin_password = password
        default_permission = READ
        database_uri = postgresql://${POSTGRES_USER:-postgres}:${POSTGRES_PASSWORD:-password}@db:5432/${POSTGRES_DB:-arla}
        EOF

        echo "Starting MLflow server..."
        exec mlflow server \
          --host 0.0.0.0 \
          --port 5000 \
          --backend-store-uri file:///mlruns \
          --app-name basic-auth \
          --serve-artifacts
    depends_on:
      db:
        condition: service_healthy
    networks:
      - arla_network
    healthcheck:
      test: ["CMD", "curl", "-f", "-u", "admin:password", "http://localhost:5000/health"]
      interval: 30s
      timeout: 10s
      retries: 5
      start_period: 60s
    restart: unless-stopped

  # Container log viewer
  dozzle:
    image: amir20/dozzle:latest
    container_name: arla_dozzle
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock:ro
    ports:
      - "${DOZZLE_PORT:-9999}:8080"
    environment:
      DOZZLE_LEVEL: info
      DOZZLE_TAILSIZE: 300
      DOZZLE_FILTER: "name=arla"
    networks:
      - arla_network
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:8080"]
      interval: 30s
      timeout: 10s
      retries: 3

# Named volumes for data persistence
volumes:
  postgres_data:
    driver: local
  redis_data:
    driver: local
  poetry_venv:
    driver: local
  poetry_cache:
    driver: local

# Custom network for service communication
networks:
  arla_network:
    driver: bridge
    ipam:
      config:
        - subnet: 172.20.0.0/16