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Machine learning request to "http://immich-machine-learning:3003" failed with status 500 #5939

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opened 2026-02-05 11:52:41 +03:00 by OVERLORD · 0 comments
OVERLORD commented 2026-02-05 11:52:41 +03:00
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Originally created by @H4rl3k1n on GitHub (May 1, 2025).

I have searched the existing issues, both open and closed, to make sure this is not a duplicate report.

  • Yes

The bug

since latest version 1.132.3 searchfunction doesnt work anymore. i tryed different clip models:
immich-app/XLM-Roberta-Large-Vit-B-16Plus
ViT-B-16-SigLIP-i18n-256__webli

The OS that Immich Server is running on

Ubuntu Server 24.04 lts

Version of Immich Server

1..132.3

Version of Immich Mobile App

1.132.3

Platform with the issue

  • Server
  • Web
  • Mobile

Your docker-compose.yml content

name: immich

services:
  immich-server:
    container_name: immich_server
    image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
    # extends:
    #   file: hwaccel.transcoding.yml
    #   service: cpu # 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
    ports:
      - '2283:2283'
    depends_on:
      - redis
      - database
    restart: always
    healthcheck:
      disable: false

  immich-machine-learning:
    container_name: immich_machine_learning
    # For hardware acceleration, add one of -[armnn, cuda, rocm, openvino, rknn] 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, rocm, openvino, openvino-wsl, rknn] for accelerated inference - use the `-wsl` version for WSL2 where applicable
    volumes:
      - /dockervolumes/immich/immich_cache:/cache
    restart: always
    healthcheck:
      disable: false

  redis:
    container_name: immich_redis
    image: docker.io/redis:6.2-alpine@sha256:148bb5411c184abd288d9aaed139c98123eeb8824c5d3fce03cf721db58066d8
    healthcheck:
      test: redis-cli ping || exit 1
    volumes:
      - /dockervolumes/immich/immich_redis:/data
    restart: always

  database:
    container_name: immich_postgres
    image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:739cdd626151ff1f796dc95a6591b55a714f341c737e27f045019ceabf8e8c52
    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

Your .env content

UPLOAD_LOCATION=/dockervolumes/immich/immich_upload
DB_DATA_LOCATION=/dockervolumes/immich/immich_postgres
DB_PASSWORD=postgres
DB_USERNAME=postgres
DB_DATABASE_NAME=immich
IMMICH_VERSION=v1.132.3

Reproduction steps

  1. upgrade to version 1.132.3
  2. use search function

Relevant log output

[Nest] 17  - 05/01/2025, 6:45:55 AM    WARN [Api:MachineLearningRepository~m3pj7itl] Machine learning request to "http://immich-machine-learning:3003" failed with status 500: Internal Server Error

[Nest] 17  - 05/01/2025, 6:45:55 AM   ERROR [Api:ErrorInterceptor~m3pj7itl] Unknown error: Error: Machine learning request '{"clip":{"textual":{"modelName":"ViT-B-16-SigLIP-i18n-256__webli","options":{"language":"de"}}}}' failed for all URLs

Error: Machine learning request '{"clip":{"textual":{"modelName":"ViT-B-16-SigLIP-i18n-256__webli","options":{"language":"de"}}}}' failed for all URLs

    at MachineLearningRepository.predict (/usr/src/app/dist/repositories/machine-learning.repository.js:98:15)

    at process.processTicksAndRejections (node:internal/process/task_queues:105:5)

    at async MachineLearningRepository.encodeText (/usr/src/app/dist/repositories/machine-learning.repository.js:121:26)

    at async SearchService.searchSmart (/usr/src/app/dist/services/search.service.js:62:27)

Additional information

i tryed the usual stuff:
new machine learning intelligent search, reboot, restart, reinstall but always get this error.

i tryed a fallback to 1.131.3, here the searchfunction works fine.

Originally created by @H4rl3k1n on GitHub (May 1, 2025). ### I have searched the existing issues, both open and closed, to make sure this is not a duplicate report. - [x] Yes ### The bug since latest version 1.132.3 searchfunction doesnt work anymore. i tryed different clip models: immich-app/XLM-Roberta-Large-Vit-B-16Plus ViT-B-16-SigLIP-i18n-256__webli ### The OS that Immich Server is running on Ubuntu Server 24.04 lts ### Version of Immich Server 1..132.3 ### Version of Immich Mobile App 1.132.3 ### Platform with the issue - [x] Server - [ ] Web - [ ] Mobile ### Your docker-compose.yml content ```YAML name: immich services: immich-server: container_name: immich_server image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release} # extends: # file: hwaccel.transcoding.yml # service: cpu # 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 ports: - '2283:2283' depends_on: - redis - database restart: always healthcheck: disable: false immich-machine-learning: container_name: immich_machine_learning # For hardware acceleration, add one of -[armnn, cuda, rocm, openvino, rknn] 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, rocm, openvino, openvino-wsl, rknn] for accelerated inference - use the `-wsl` version for WSL2 where applicable volumes: - /dockervolumes/immich/immich_cache:/cache restart: always healthcheck: disable: false redis: container_name: immich_redis image: docker.io/redis:6.2-alpine@sha256:148bb5411c184abd288d9aaed139c98123eeb8824c5d3fce03cf721db58066d8 healthcheck: test: redis-cli ping || exit 1 volumes: - /dockervolumes/immich/immich_redis:/data restart: always database: container_name: immich_postgres image: docker.io/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:739cdd626151ff1f796dc95a6591b55a714f341c737e27f045019ceabf8e8c52 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 ``` ### Your .env content ```Shell UPLOAD_LOCATION=/dockervolumes/immich/immich_upload DB_DATA_LOCATION=/dockervolumes/immich/immich_postgres DB_PASSWORD=postgres DB_USERNAME=postgres DB_DATABASE_NAME=immich IMMICH_VERSION=v1.132.3 ``` ### Reproduction steps 1. upgrade to version 1.132.3 2. use search function ### Relevant log output ```shell [Nest] 17 - 05/01/2025, 6:45:55 AM WARN [Api:MachineLearningRepository~m3pj7itl] Machine learning request to "http://immich-machine-learning:3003" failed with status 500: Internal Server Error [Nest] 17 - 05/01/2025, 6:45:55 AM ERROR [Api:ErrorInterceptor~m3pj7itl] Unknown error: Error: Machine learning request '{"clip":{"textual":{"modelName":"ViT-B-16-SigLIP-i18n-256__webli","options":{"language":"de"}}}}' failed for all URLs Error: Machine learning request '{"clip":{"textual":{"modelName":"ViT-B-16-SigLIP-i18n-256__webli","options":{"language":"de"}}}}' failed for all URLs at MachineLearningRepository.predict (/usr/src/app/dist/repositories/machine-learning.repository.js:98:15) at process.processTicksAndRejections (node:internal/process/task_queues:105:5) at async MachineLearningRepository.encodeText (/usr/src/app/dist/repositories/machine-learning.repository.js:121:26) at async SearchService.searchSmart (/usr/src/app/dist/services/search.service.js:62:27) ``` ### Additional information i tryed the usual stuff: new machine learning intelligent search, reboot, restart, reinstall but always get this error. i tryed a fallback to 1.131.3, here the searchfunction works fine.
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Reference: immich-app/immich#5939
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