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Need to add port 3003 for machine learning or microservices fails to connect #2313

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opened 2026-02-05 05:57:27 +03:00 by OVERLORD · 0 comments
OVERLORD commented 2026-02-05 05:57:27 +03:00
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Originally created by @spusuf on GitHub (Feb 29, 2024).

The bug

Default compose.yml does not expose port 3003 on machine learning server for microservices to connect to. If you look at the logs there are a bunch of errors about failing to connect to machine learning server. Needed to add the following to get my instance to work:

immich-machine-learning:
  ports:
    - 3003:3003

The OS that Immich Server is running on

Debian 12

Version of Immich Server

1.97.0

Version of Immich Mobile App

1.96.0.build.125

Platform with the issue

  • Server
  • Web
  • Mobile

Your docker-compose.yml content

version: "3.8"

#
# WARNING: Make sure to use the docker-compose.yml of the current release:
#
# https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml
#
# The compose file on main may not be compatible with the latest release.
#

name: immich

services:
  immich-server:
    container_name: immich_server
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
    command: [ "start.sh", "immich" ]
    volumes:
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
      - /etc/localtime:/etc/localtime:ro
    env_file:
      - stack.env
    ports:
      - 2283:3001
    depends_on:
      - redis
      - database
    restart: always

  immich-microservices:
    container_name: immich_microservices
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
    # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/hardware-transcoding
    #   file: hwaccel.transcoding.yml
    #   service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
    command: [ "start.sh", "microservices" ]
    volumes:
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
      - /etc/localtime:/etc/localtime:ro
    env_file:
      - stack.env
    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:
      - stack.env
    restart: always
    ports:
      - 3003:3003

  redis:
    container_name: immich_redis
    image: registry.hub.docker.com/library/redis:6.2-alpine@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5
    restart: always

  database:
    container_name: immich_postgres
    image: registry.hub.docker.com/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
    environment:
      POSTGRES_PASSWORD: ${DB_PASSWORD}
      POSTGRES_USER: ${DB_USERNAME}
      POSTGRES_DB: ${DB_DATABASE_NAME}
    volumes:
      - pgdata:/var/lib/postgresql/data
    restart: always

volumes:
  pgdata:
  model-cache:

Your .env content

UPLOAD_LOCATION=/mnt/POOL/photos/immich/library
IMMICH_VERSION=release
DB_PASSWORD=postgres
DB_HOSTNAME=immich_postgres
DB_USERNAME=postgres
DB_DATABASE_NAME=immich
REDIS_HOSTNAME=immich_redis

Reproduction steps

Run docker compose with latest compose.yml
Start the Face Detection job
Observe logs in microservices container
Errors appear

Additional information

No response

Originally created by @spusuf on GitHub (Feb 29, 2024). ### The bug Default compose.yml does not expose port 3003 on machine learning server for microservices to connect to. If you look at the logs there are a bunch of errors about failing to connect to machine learning server. Needed to add the following to get my instance to work: ``` immich-machine-learning: ports: - 3003:3003 ``` ### The OS that Immich Server is running on Debian 12 ### Version of Immich Server 1.97.0 ### Version of Immich Mobile App 1.96.0.build.125 ### Platform with the issue - [X] Server - [ ] Web - [ ] Mobile ### Your docker-compose.yml content ```YAML version: "3.8" # # WARNING: Make sure to use the docker-compose.yml of the current release: # # https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml # # The compose file on main may not be compatible with the latest release. # name: immich services: immich-server: container_name: immich_server image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release} command: [ "start.sh", "immich" ] volumes: - ${UPLOAD_LOCATION}:/usr/src/app/upload - /etc/localtime:/etc/localtime:ro env_file: - stack.env ports: - 2283:3001 depends_on: - redis - database restart: always immich-microservices: container_name: immich_microservices image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release} # extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/hardware-transcoding # file: hwaccel.transcoding.yml # service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding command: [ "start.sh", "microservices" ] volumes: - ${UPLOAD_LOCATION}:/usr/src/app/upload - /etc/localtime:/etc/localtime:ro env_file: - stack.env 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: - stack.env restart: always ports: - 3003:3003 redis: container_name: immich_redis image: registry.hub.docker.com/library/redis:6.2-alpine@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5 restart: always database: container_name: immich_postgres image: registry.hub.docker.com/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0 environment: POSTGRES_PASSWORD: ${DB_PASSWORD} POSTGRES_USER: ${DB_USERNAME} POSTGRES_DB: ${DB_DATABASE_NAME} volumes: - pgdata:/var/lib/postgresql/data restart: always volumes: pgdata: model-cache: ``` ### Your .env content ```Shell UPLOAD_LOCATION=/mnt/POOL/photos/immich/library IMMICH_VERSION=release DB_PASSWORD=postgres DB_HOSTNAME=immich_postgres DB_USERNAME=postgres DB_DATABASE_NAME=immich REDIS_HOSTNAME=immich_redis ``` ### Reproduction steps ```bash Run docker compose with latest compose.yml Start the Face Detection job Observe logs in microservices container Errors appear ``` ### Additional information _No response_
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Reference: immich-app/immich#2313
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