services:
  resume-matcher:
    image: ghcr.io/srbhr/resume-matcher
    build:
      context: .
      # Optional, for slow networks (empty by default = no change):
      #   DEBIAN_MIRROR=https://mirrors.edge.kernel.org/debian docker compose build
      args:
        - DEBIAN_MIRROR=${DEBIAN_MIRROR:-}
        - DEBIAN_SECURITY_MIRROR=${DEBIAN_SECURITY_MIRROR:-}
        - PIP_INDEX_URL=${PIP_INDEX_URL:-}
        - PLAYWRIGHT_DOWNLOAD_HOST=${PLAYWRIGHT_DOWNLOAD_HOST:-}
    container_name: resume-matcher
    ports:
      # Reachable from this machine only. To open it from a phone or another computer,
      # set BIND_ADDRESS=0.0.0.0 and add the address you will use to ALLOWED_HOSTS.
      - "${BIND_ADDRESS:-127.0.0.1}:${PORT:-3000}:3000"
    # Makes host.docker.internal (your machine, e.g. for Ollama) resolve on Linux too.
    # Docker Desktop (macOS/Windows) already provides it.
    extra_hosts:
      - "host.docker.internal:host-gateway"
    volumes:
      - resume-data:/app/backend/data
    #secrets:
    #  - llm_api_key
    environment:
      # domain in reverse proxy
      - FRONTEND_BASE_URL=${FRONTEND_BASE_URL:-http://localhost:3000}
      # Extra hostnames the app answers for (comma-separated), besides localhost and the
      # FRONTEND_BASE_URL host, e.g. 192.168.1.20 for LAN access. "*" allows any.
      - ALLOWED_HOSTS=${ALLOWED_HOSTS:-}
      # Logging configuration: DEBUG, INFO, WARNING, ERROR
      - LOG_LEVEL=${LOG_LEVEL:-INFO}
      #- LOG_LEVEL_FILE=${LOG_LEVEL_FILE:-}
      # Debug level for LiteLLM: DEBUG, INFO, WARNING, ERROR
      - LOG_LLM=${LOG_LLM:-WARNING}
      #- LOG_LLM_FILE=${LOG_LLM_FILE:-}
      # LLM Configuration - configure via Settings UI or set env vars for explicit overrides
      # Supported providers: openai, anthropic, openrouter, gemini, deepseek, ollama
      # Defaults are defined in apps/backend/app/config.py
      - LLM_PROVIDER=${LLM_PROVIDER:-openai}
      - LLM_MODEL=${LLM_MODEL:-}
      # Optional Docker Secret file path (same behavior as Postgres-style *_FILE)
      #- LLM_API_KEY_FILE=${LLM_API_KEY_FILE:-/run/secrets/llm_api_key}
      - LLM_API_KEY=${LLM_API_KEY:-}
      # Ollama (or LM Studio, llama.cpp) running on this machine, outside Docker: inside
      # the container "localhost" is the container itself, so use host.docker.internal:
      # - LLM_API_BASE=http://host.docker.internal:11434
      # On Linux, Ollama must also listen beyond 127.0.0.1 (see SETUP.md, "Using Ollama
      # with Docker").
      - LLM_API_BASE=${LLM_API_BASE:-}
      # CORS origins (JSON array format). FRONTEND_BASE_URL is auto-included.
      #- CORS_ORIGINS=["http://localhost:3000","http://127.0.0.1:3000"]
    restart: unless-stopped
    # Fast iteration: `docker compose watch` (Compose 2.22+). Backend code is synced into
    # the running container and the app restarts; no image rebuild. Frontend, dependency
    # and image changes rebuild the image (Chromium and Python deps stay cached).
    # Plain `docker compose up` ignores this block.
    develop:
      watch:
        - action: sync+restart
          path: ./apps/backend/app
          target: /app/backend/app
          ignore:
            - __pycache__/
        - action: rebuild
          path: ./apps/frontend
          ignore:
            - node_modules/
            - .next/
        - action: rebuild
          path: ./apps/backend/pyproject.toml
        - action: rebuild
          path: ./Dockerfile
        - action: rebuild
          path: ./docker

#secrets:
#  llm_api_key:
#    file: ./secrets/llm_api_key

volumes:
  resume-data:
    driver: local