version: "3.8"

name: immich

services:
  immich-server:
    container_name: immich_server
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
    devices:
      - /dev/dri:/dev/dri
    # command: [ "start.sh", "immich" ]
    volumes:
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
      - /etc/localtime:/etc/localtime:ro
      - /mnt/disks/vmdrive/ffmpeg:/usr/bin/ffmpeg:ro
      - /mnt/disks/vmdrive/ffmpeg.real:/usr/bin/ffmpeg.real:ro
    env_file:
      - .env
    ports:
      - 2283:2283
    depends_on:
      - redis
      - database
    restart: always


  immich-machine-learning:
    container_name: immich_machine_learning
    # For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
    # Example tag: ${IMMICH_VERSION:-release}-cuda
    image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
    # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
    #   file: hwaccel.ml.yml
    #   service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
    volumes:
      - model-cache:/cache
    env_file:
      - .env
    restart: always

  redis:
    container_name: immich_redis
    image: redis:6.2-alpine@sha256:afb290a0a0d0b2bd7537b62ebff1eb84d045c757c1c31ca2ca48c79536c0de82
    restart: always

  database:
    container_name: immich_postgres
    # image: tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
    image: ghcr.io/immich-app/postgres:14-vectorchord0.3.0-pgvectors0.2.0
    env_file:
      - .env
    environment:
      POSTGRES_PASSWORD: ${DB_PASSWORD}
      POSTGRES_USER: ${DB_USERNAME}
      POSTGRES_DB: ${DB_DATABASE_NAME}
      DB_STORAGE_TYPE: 'HDD'
    volumes:
      - pgdata:/var/lib/postgresql/data
    restart: always

volumes:
  pgdata:
  model-cache: