immich/docs/docs/guides/remote-machine-learning.md

Remote Machine Learning

To alleviate performance issues on low-memory systems like the Raspberry Pi, you may also host Immich's machine-learning container on a more powerful system (e.g. your laptop or desktop computer):

• Set the URL in Machine Learning Settings on the Admin Settings page to point to the designated ML system, e.g. http://workstation:3003.
• Copy the following docker-compose.yml to your ML system.
  • If using hardware acceleration, the hwaccel.ml.yml file also needs to be added
• Start the container by running docker compose up -d.

:::info Smart Search and Face Detection will use this feature, but Facial Recognition is handled in the server. :::

:::danger When using remote machine learning, the thumbnails are sent to the remote machine learning container. Use this option carefully when running this on a public computer or a paid processing cloud. :::

name: immich_remote_ml

services:
  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:
    #   file: hwaccel.ml.yml
    #   service: # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
    volumes:
      - model-cache:/cache
    restart: always
    ports:
      - 3003:3003

volumes:
  model-cache:

Please note that version mismatches between both hosts may cause instabilities and bugs, so make sure to always perform updates together.

:::caution As an internal service, the machine learning container has no security measures whatsoever. Please be mindful of where it's deployed and who can access it. :::