# Docker Compose for Azure OpenAI deployment
# Usage:
#   1. Copy .env.example to .env and fill in your Azure OpenAI credentials
#   2. Build the image: docker compose -f docker-compose.azure.yml build
#   3. Run the gateway: docker compose -f docker-compose.azure.yml up -d moltbot-azure-gateway
#   4. Or run the CLI: docker compose -f docker-compose.azure.yml run --rm moltbot-azure-cli

services:
  moltbot-azure-gateway:
    build:
      context: .
      dockerfile: Dockerfile
    image: moltbot-azure:local
    container_name: moltbot-azure-gateway
    environment:
      HOME: /home/node
      TERM: xterm-256color
      # Gateway authentication token (generate a secure token for production)
      CLAWDBOT_GATEWAY_TOKEN: ${CLAWDBOT_GATEWAY_TOKEN:-your-secure-gateway-token}
      # Azure OpenAI Configuration (required)
      AZURE_OPENAI_API_KEY: ${AZURE_OPENAI_API_KEY:?Azure OpenAI API key is required}
      AZURE_OPENAI_RESOURCE_NAME: ${AZURE_OPENAI_RESOURCE_NAME:?Azure OpenAI resource name is required}
      AZURE_OPENAI_DEPLOYMENT_NAME: ${AZURE_OPENAI_DEPLOYMENT_NAME:?Azure OpenAI deployment name is required}
      AZURE_OPENAI_API_VERSION: ${AZURE_OPENAI_API_VERSION:-2024-08-01-preview}
      # Optional: provide full endpoint URL instead of resource name
      AZURE_OPENAI_ENDPOINT: ${AZURE_OPENAI_ENDPOINT}
    volumes:
      # Persist configuration and session data
      - ${CLAWDBOT_CONFIG_DIR:-./data/config}:/home/node/.moltbot
      - ${CLAWDBOT_WORKSPACE_DIR:-./data/workspace}:/home/node/clawd
    ports:
      # Gateway HTTP/WebSocket port
      - "${CLAWDBOT_GATEWAY_PORT:-18789}:18789"
      # Bridge port for channel connections
      - "${CLAWDBOT_BRIDGE_PORT:-18790}:18790"
    init: true
    restart: unless-stopped
    command:
      [
        "node",
        "dist/index.js",
        "gateway",
        "--bind",
        "${CLAWDBOT_GATEWAY_BIND:-lan}",
        "--port",
        "${CLAWDBOT_GATEWAY_PORT:-18789}",
        "--allow-unconfigured"
      ]
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:18789/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 30s

  moltbot-azure-cli:
    build:
      context: .
      dockerfile: Dockerfile
    image: moltbot-azure:local
    container_name: moltbot-azure-cli
    environment:
      HOME: /home/node
      TERM: xterm-256color
      BROWSER: echo
      # Azure OpenAI Configuration (required)
      AZURE_OPENAI_API_KEY: ${AZURE_OPENAI_API_KEY:?Azure OpenAI API key is required}
      AZURE_OPENAI_RESOURCE_NAME: ${AZURE_OPENAI_RESOURCE_NAME:?Azure OpenAI resource name is required}
      AZURE_OPENAI_DEPLOYMENT_NAME: ${AZURE_OPENAI_DEPLOYMENT_NAME:?Azure OpenAI deployment name is required}
      AZURE_OPENAI_API_VERSION: ${AZURE_OPENAI_API_VERSION:-2024-08-01-preview}
      AZURE_OPENAI_ENDPOINT: ${AZURE_OPENAI_ENDPOINT}
    volumes:
      - ${CLAWDBOT_CONFIG_DIR:-./data/config}:/home/node/.moltbot
      - ${CLAWDBOT_WORKSPACE_DIR:-./data/workspace}:/home/node/clawd
    stdin_open: true
    tty: true
    init: true
    entrypoint: ["node", "dist/index.js"]

  # Minimal test service to verify Azure OpenAI connection
  moltbot-azure-test:
    build:
      context: .
      dockerfile: Dockerfile
    image: moltbot-azure:local
    environment:
      HOME: /home/node
      TERM: xterm-256color
      AZURE_OPENAI_API_KEY: ${AZURE_OPENAI_API_KEY:?Azure OpenAI API key is required}
      AZURE_OPENAI_RESOURCE_NAME: ${AZURE_OPENAI_RESOURCE_NAME:?Azure OpenAI resource name is required}
      AZURE_OPENAI_DEPLOYMENT_NAME: ${AZURE_OPENAI_DEPLOYMENT_NAME:?Azure OpenAI deployment name is required}
      AZURE_OPENAI_API_VERSION: ${AZURE_OPENAI_API_VERSION:-2024-08-01-preview}
    command: ["node", "dist/index.js", "models", "list"]
    profiles:
      - test

# Named volumes for persistent storage (optional, use bind mounts above for easier access)
volumes:
  moltbot-config:
  moltbot-workspace: