# Processing machine - tile generator (see docs/DEPLOY_WEBAPP.md).
#
# Runs on the powerful machine (GPU + PDAL) and exposes the API that remote
# maps (Raspberry Pi, docker-compose.maps.yml + LIDAR_GENERATION_URL) call:
# drawing an area -> IGN download + GPU processing here; source tiles and
# XYZ tiles served to the lightweight machines (/api/tiles + static files,
# /tiles/XYZ).
#
#   docker compose -f docker-compose.worker.yml up -d --build
#   docker compose -f docker-compose.worker.yml logs -f worker
#   docker compose -f docker-compose.worker.yml down
#
# One-off batch processing of the tiles present in input/:
#   docker compose -f docker-compose.worker.yml run --rm --build process
#   (any argument replaces the default command: repeat
#    python3 -m lidar_pipeline /data/input -o /data/output -r 0.2 -g all ... in full)
services:
  # Tile generator: XYZ map + generation API (full image, GPU)
  worker:
    build: .
    image: lidar-lidar
    container_name: lidar-worker
    init: true
    user: "1000:1000"
    gpus: all            # remove this line on a machine without a GPU
    ports:
      - "8973:8973"      # reachable by the remote maps (LIDAR_GENERATION_URL
                          # and LIDAR_SOURCE_URL point here)
    volumes:
      # input/ writable: the API downloads missing IGN tiles into it
      - ./input:/data/input
      - ./output:/data/output
    environment:
      - TZ=Europe/Paris
      - LIDAR_INPUT_DIR=/data/input
      - LIDAR_OUTPUT_DIR=/data/output
      - LIDAR_PORT=8973
      # Generations started from a remote map use the GPU
      - LIDAR_GPU=1
      - LIDAR_WORKERS=auto
      # Workers per GPU capped by the free VRAM when the run starts
      # ((free - reserve) / per-worker peak); the excess runs on the CPU.
      # Peak estimated at 2048 MiB: adjust after measuring (nvidia-smi during a run).
      # - LIDAR_GPU_WORKER_MIB=2048
      # - LIDAR_GPU_RESERVE_MIB=512
      # One thread per worker: single-threaded BLAS/OpenMP, otherwise 12 workers x N
      # threads swamp the 14 cores (load 68+ observed during runs)
      - OMP_NUM_THREADS=1
      - OPENBLAS_NUM_THREADS=1
      - MKL_NUM_THREADS=1
      - NUMEXPR_NUM_THREADS=1
      # Protect the API if the network is not trusted: same value as
      # LIDAR_REMOTE_TOKEN on every remote map (otherwise leave commented out)
      # - LIDAR_API_TOKEN=change-me
    command: python3 -m uvicorn lidar_pipeline.mapserve:app --host 0.0.0.0 --port 8973
    restart: unless-stopped

  # One-off processing of the input/ tiles (one pass, then exit)
  process:
    build: .
    image: lidar-lidar
    container_name: lidar-process
    init: true
    user: "1000:1000"
    gpus: all            # remove this line on a machine without a GPU
    volumes:
      - ./input:/data/input
      - ./output:/data/output
    environment:
      - TZ=Europe/Paris
    command: ["python3", "-m", "lidar_pipeline", "/data/input", "-o", "/data/output", "-r", "0.2", "-g", "all"]
    profiles:
      - process