services:
  llms:
    image: ghcr.io/servicestack/llms:latest
    container_name: llms-py
    ports:
      # Only reachable from this machine. Use "8000:8000" to expose it on your LAN.
      - "127.0.0.1:8000:8000"
    env_file:
      # All API keys live here, one VAR=value per line, no quotes.
      # Create it with `cp .env.example .env`, or run:
      #   curl -fsSL https://llmspy.org/install.sh | bash
      # which generates ~/.llms/.env for you.
      - .env
    volumes:
      # User-modifiable config kept outside the container.
      # llms.json and providers.json are auto-created on first run.
      - ~/.llms:/home/llms/.llms
    extra_hosts:
      # Lets the container reach services on the host (ollama, LM Studio, ...)
      # via http://host.docker.internal:11434 etc.
      - "host.docker.internal:host-gateway"
    restart: unless-stopped
    healthcheck:
      test: [ "CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000').read()" ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 10s