# ──────────────────────────────────────────────────────────────
#  VoiceStudio — Docker Compose
#
#  Quick start:
#    docker compose -f deploy/docker-compose.yml --profile cpu up    # CPU mode
#    docker compose -f deploy/docker-compose.yml --profile gpu up    # NVIDIA GPU
#    docker compose -f deploy/docker-compose.yml --profile rocm up   # AMD GPU (ROCm)
#
#  All services bind to port 3900, so they MUST be opt-in via profiles —
#  otherwise `compose up` would race them and one would fail to bind.
#
#  First run downloads ~4 GB of models. Progress is shown in logs.
#  Open http://localhost:3900 once the health check passes.
#
#  SECURITY: The port is bound to 127.0.0.1 by default — only this
#  machine can reach the API. To expose VoiceStudio on your LAN (or
#  through a reverse proxy / tunnel), change the port mapping to
#  "0.0.0.0:3900:3900" or "3900:3900". VoiceStudio itself ships no
#  authentication — if you expose it, put it behind a reverse proxy
#  with auth (Caddy basic_auth, nginx + htpasswd, Tailscale, etc.).
# ──────────────────────────────────────────────────────────────

services:
  # ── CPU mode — activate with: docker compose --profile cpu up
  omnivoice:
    image: ghcr.io/debpalash/omnivoice-studio:latest
    # To build from source instead of pulling, comment out `image:` and
    # uncomment the two lines below:
    build:
      context: ..
      dockerfile: deploy/Dockerfile
    container_name: omnivoice-studio
    profiles: ["cpu"]
    ports:
      - "127.0.0.1:3900:3900"
    volumes:
      - omnivoice-data:/app/omnivoice_data
    environment:
      - HF_HOME=/app/omnivoice_data/huggingface
      - HF_TOKEN=${HF_TOKEN:-}
      - OMNIVOICE_DATA_DIR=/app/omnivoice_data
      - PYTHONPATH=/app/backend
      - PYTHONUNBUFFERED=1
      # Bind uvicorn to 0.0.0.0 *inside* the container so the host-side port
      # mapping above can forward traffic in. The 127.0.0.1 prefix on the
      # `ports:` mapping is what enforces loopback-only on the host —
      # OMNIVOICE_BIND_HOST=0.0.0.0 here only opens the container's own
      # interface. The backend default is 127.0.0.1 (see backend/main.py).
      - OMNIVOICE_BIND_HOST=0.0.0.0
      # Headless server: relax the desktop-only loopback origin gate so the
      # web UI's /system/* and /api/settings/* routes work through Docker's
      # NAT (issue #261). Already baked into the image; shown here so it's
      # discoverable. If you front the container with your own auth proxy on
      # loopback, set this to 0 to re-enable the strict gate.
      - OMNIVOICE_SERVER_MODE=1
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:3900/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 120s
    restart: unless-stopped

  # ── GPU mode — activate with: docker compose --profile gpu up
  omnivoice-gpu:
    image: ghcr.io/debpalash/omnivoice-studio:latest
    build:
      context: ..
      dockerfile: deploy/Dockerfile
    container_name: omnivoice-studio-gpu
    profiles: ["gpu"]
    ports:
      - "127.0.0.1:3900:3900"
    volumes:
      - omnivoice-data:/app/omnivoice_data
    environment:
      - HF_HOME=/app/omnivoice_data/huggingface
      - HF_TOKEN=${HF_TOKEN:-}
      - OMNIVOICE_DATA_DIR=/app/omnivoice_data
      - PYTHONPATH=/app/backend
      - PYTHONUNBUFFERED=1
      # Bind uvicorn to 0.0.0.0 *inside* the container — same as the CPU
      # service above. The host-side `127.0.0.1:3900:3900` mapping keeps
      # LAN reachability off by default.
      - OMNIVOICE_BIND_HOST=0.0.0.0
      # See the CPU service above — relaxes the loopback origin gate for the
      # headless Docker deployment (issue #261). Set to 0 to re-enable it.
      - OMNIVOICE_SERVER_MODE=1
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:3900/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 180s
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    restart: unless-stopped

  # ── AMD GPU (ROCm) mode — activate with: docker compose --profile rocm up
  # Uses the dedicated `:rocm` image variant (#1165). The GPU is passed
  # through as plain device nodes — no toolkit needed, the host only needs
  # the amdgpu kernel driver (the ROCm userspace ships inside the image).
  # Podman works with the same two --device flags (Quadlet: AddDevice=).
  omnivoice-rocm:
    image: ghcr.io/debpalash/omnivoice-studio:rocm
    # To build from source instead of pulling, comment out `image:` and
    # uncomment the lines below. BASE_IMAGE/GPU_FLAVOR are required — the
    # Dockerfile's defaults build the CUDA variant.
    # build:
    #   context: ..
    #   dockerfile: deploy/Dockerfile
    #   args:
    #     BASE_IMAGE: rocm/pytorch:rocm7.2.4_ubuntu24.04_py3.12_pytorch_release_2.8.0
    #     GPU_FLAVOR: rocm
    container_name: omnivoice-studio-rocm
    profiles: ["rocm"]
    ports:
      - "127.0.0.1:3900:3900"
    devices:
      - /dev/kfd
      - /dev/dri
    volumes:
      - omnivoice-data:/app/omnivoice_data
    environment:
      - HF_HOME=/app/omnivoice_data/huggingface
      - HF_TOKEN=${HF_TOKEN:-}
      - OMNIVOICE_DATA_DIR=/app/omnivoice_data
      - PYTHONPATH=/app/backend
      - PYTHONUNBUFFERED=1
      # See the CPU service above — container-internal bind + relaxed
      # loopback origin gate for the headless Docker deployment.
      - OMNIVOICE_BIND_HOST=0.0.0.0
      - OMNIVOICE_SERVER_MODE=1
      # RDNA3 consumer cards (RX 7900 XTX/XT and friends, gfx1100): if the
      # GPU is not detected, uncomment the override below. The backend
      # auto-sets it for known consumer GFX IDs, so try without it first.
      # - HSA_OVERRIDE_GFX_VERSION=11.0.0
    healthcheck:
      test: ["CMD", "curl", "-sf", "http://localhost:3900/health"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 180s
    restart: unless-stopped

volumes:
  omnivoice-data: