docker-compose.prod.yml

version: '3.8'

services:
  engine:
    build:
      context: ./src/python-engine
      dockerfile: Dockerfile
    image: agentrank-engine:latest
    container_name: agentrank-engine
    restart: always
    user: "1000:1000"
    ports:
      - "8001:8000"
    environment:
      # LLM Configuration
      - AZURE_OPENAI_ENDPOINT=${AZURE_OPENAI_ENDPOINT}
      - AZURE_OPENAI_API_KEY=${AZURE_OPENAI_API_KEY}
      - AZURE_OPENAI_DEPLOYMENT=${AZURE_OPENAI_DEPLOYMENT:-gpt-4o}
      - AZURE_OPENAI_API_VERSION=${AZURE_OPENAI_API_VERSION:-2024-02-15-preview}
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}

      # Storage Configuration
      - R2_ACCOUNT_ID=${R2_ACCOUNT_ID}
      - R2_ACCESS_KEY=${R2_ACCESS_KEY}
      - R2_SECRET_KEY=${R2_SECRET_KEY}
      - R2_BUCKET_NAME=${R2_BUCKET_NAME:-agentrank-replays}
      - R2_PUBLIC_URL=${R2_PUBLIC_URL}

      # System Configuration
      - PYTHONUNBUFFERED=1

    # In production, we assume the code is baked into the image.
    # We only mount data volumes for persistence.
    volumes:
      - ./engine-data:/app/data
      - ./recordings:/app/recordings

    # Resource Limits for Production
    deploy:
      resources:
        limits:
          cpus: '2.0'
          memory: 4G
        reservations:
          cpus: '0.5'
          memory: 1G

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

    # Health check is defined in Dockerfile, but can be overridden here if needed.
    healthcheck:
      test: [ "CMD", "curl", "-f", "http://localhost:8000/health" ]
      interval: 30s
      timeout: 10s
      retries: 3