Issue upgrading to 1.133.0 from 1.132.2

#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}
    extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/hardware-transcoding
      file: hwaccel.transcoding.yml
      service: quicksync # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
    #command: [ "start.sh", "immich" ]
    volumes:
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
      - /mnt/tank/Home/Photos:/home/photos:ro
      - /etc/localtime:/etc/localtime:ro
    env_file:
      - .env
    ports:
      - 2283:2283
#      - 2283:3001
    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@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5
    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
    environment:
      POSTGRES_PASSWORD: postgres #${DB_PASSWORD}
      POSTGRES_USER: postgres #${DB_USERNAME}
      POSTGRES_DB: immich #${DB_DATABASE_NAME}
      POSTGRES_INITDB_ARGS: '--data-checksums'
     # Uncomment the DB_STORAGE_TYPE: 'HDD' var if your database isn't stored on SSDs
     # DB_STORAGE_TYPE: 'HDD'
    volumes:
      - pgdata:/var/lib/postgresql/data
    restart: always

volumes:
  pgdata:
  model-cache:

#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}
    extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/hardware-transcoding
      file: hwaccel.transcoding.yml
      service: quicksync # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
    #command: [ "start.sh", "immich" ]
    volumes:
      - ${UPLOAD_LOCATION}:/usr/src/app/upload
      - /mnt/tank/Home/Photos:/home/photos:ro
      - /etc/localtime:/etc/localtime:ro
    env_file:
      - .env
    ports:
      - 2283:2283
#      - 2283:3001
    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@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5
    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
    environment:
      POSTGRES_PASSWORD: postgres #${DB_PASSWORD}
      POSTGRES_USER: postgres #${DB_USERNAME}
      POSTGRES_DB: immich #${DB_DATABASE_NAME}
      POSTGRES_INITDB_ARGS: '--data-checksums'
     # Uncomment the DB_STORAGE_TYPE: 'HDD' var if your database isn't stored on SSDs
     # DB_STORAGE_TYPE: 'HDD'
    volumes:
      - pgdata:/var/lib/postgresql/data
    restart: always

volumes:
  pgdata:
  model-cache: