Immich

name: immich

services:
  immich-server:
    container_name: immich_server
    labels:
      - "com.centurylinklabs.watchtower.enable=false"
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
    extends:
      file: hwaccel.transcoding.yml
      service: nvenc # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
    volumes:
      # Do not edit the next line. If you want to change the media storage location on your system, edit the value of UPLOAD_LOCATION in the .env file
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
      - /etc/localtime:/etc/localtime:ro
    env_file:
      - .env
    ports:
      - '2283:2283'
    depends_on:
      - redis
      - database
    restart: always
    healthcheck:
      disable: false

  immich-machine-learning:
    container_name: immich_machine_learning
    labels:
      - "com.centurylinklabs.watchtower.enable=false"
    # 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}-cuda
    extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
      file: hwaccel.ml.yml
      service: cuda # 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
    healthcheck:
      disable: false

  redis:
    container_name: immich_redis
    labels:
      - "com.centurylinklabs.watchtower.enable=false"
    image: docker.io/redis:6.2-alpine@sha256:905c4ee67b8e0aa955331960d2aa745781e6bd89afc44a8584bfd13bc890f0ae
    healthcheck:
      test: redis-cli ping || exit 1
    restart: always

  database:
    container_name: immich_postgres
    labels:
      - "com.centurylinklabs.watchtower.enable=false"
    image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
    environment:
      POSTGRES_PASSWORD: ${DB_PASSWORD}
      POSTGRES_USER: ${DB_USERNAME}
      POSTGRES_DB: ${DB_DATABASE_NAME}
      POSTGRES_INITDB_ARGS: '--data-checksums'
    volumes:
      # Do not edit the next line. If you want to change the database storage location on your system, edit the value of DB_DATA_LOCATION in the .env file
      - ${DB_DATA_LOCATION}:/var/lib/postgresql/data
    healthcheck:
      test: >-
        pg_isready --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" || exit 1;
        Chksum="$$(psql --dbname="$${POSTGRES_DB}" --username="$${POSTGRES_USER}" --tuples-only --no-align
        --command='SELECT COALESCE(SUM(checksum_failures), 0) FROM pg_stat_database')";
        echo "checksum failure count is $$Chksum";
        [ "$$Chksum" = '0' ] || exit 1
      interval: 5m
      start_interval: 30s
      start_period: 5m
    command: >-
      postgres
      -c shared_preload_libraries=vectors.so
      -c 'search_path="$$user", public, vectors'
      -c logging_collector=on
      -c max_wal_size=2GB
      -c shared_buffers=512MB
      -c wal_compression=on
    restart: always

volumes:
  model-cache:

# Configurations for hardware-accelerated machine learning

# If using Unraid or another platform that doesn't allow multiple Compose files,
# you can inline the config for a backend by copying its contents
# into the immich-machine-learning service in the docker-compose.yml file.

# See https://immich.app/docs/features/ml-hardware-acceleration for info on usage.

services:
  armnn:
    devices:
      - /dev/mali0:/dev/mali0
    volumes:
      - /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
      - /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)

  cpu: {}

  cuda:
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities:
                - gpu

  openvino:
    device_cgroup_rules:
      - 'c 189:* rmw'
    devices:
      - /dev/dri:/dev/dri
    volumes:
      - /dev/bus/usb:/dev/bus/usb

  openvino-wsl:
    devices:
      - /dev/dri:/dev/dri
      - /dev/dxg:/dev/dxg
    volumes:
      - /dev/bus/usb:/dev/bus/usb
      - /usr/lib/wsl:/usr/lib/wsl

# Configurations for hardware-accelerated transcoding

# If using Unraid or another platform that doesn't allow multiple Compose files,
# you can inline the config for a backend by copying its contents
# into the immich-microservices service in the docker-compose.yml file.

# See https://immich.app/docs/features/hardware-transcoding for more info on using hardware transcoding.

services:
  cpu: {}

  nvenc:
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities:
                - gpu
                - compute
                - video

  quicksync:
    devices:
      - /dev/dri:/dev/dri

  rkmpp:
    security_opt: # enables full access to /sys and /proc, still far better than privileged: true
      - systempaths=unconfined
      - apparmor=unconfined
    group_add:
      - video
    devices:
      - /dev/rga:/dev/rga
      - /dev/dri:/dev/dri
      - /dev/dma_heap:/dev/dma_heap
      - /dev/mpp_service:/dev/mpp_service
      #- /dev/mali0:/dev/mali0 # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
    volumes:
      #- /etc/OpenCL:/etc/OpenCL:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping
      #- /usr/lib/aarch64-linux-gnu/libmali.so.1:/usr/lib/aarch64-linux-gnu/libmali.so.1:ro # only required to enable OpenCL-accelerated HDR -> SDR tonemapping

  vaapi:
    devices:
      - /dev/dri:/dev/dri

  vaapi-wsl: # use this for VAAPI if you're running Immich in WSL2
    devices:
      - /dev/dri:/dev/dri
    volumes:
      - /usr/lib/wsl:/usr/lib/wsl
    environment:
      - LIBVA_DRIVER_NAME=d3d12