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- version: "3.8"
- services:
- immich-server:
- container_name: immich_server
- image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
- ports:
- - "2450:2283"
- depends_on:
- - redis
- - database
- volumes:
- - ${UPLOAD_LOCATION}:/usr/src/app/upload
- - /srv/dev-disk-by-uuid-455ecddd-d762-4c16-8b87-4f47721f9208/Hauptordner1/Bilder:/mnt/lib1:ro
- - /srv/dev-disk-by-uuid-2e5aebd3-e509-4523-8976-d8095258f48a/Hauptordner2/Backups_smartphone/Andy/Samsung Galaxy S21/DCIM:/mnt/lib2:ro
- - /srv/dev-disk-by-uuid-2e5aebd3-e509-4523-8976-d8095258f48a/Hauptordner2/Backups_smartphone/Soravi/Mi10/DCIM:/mnt/lib3:ro
- - /etc/localtime:/etc/localtime:ro
- env_file:
- - stack.env
- restart: always
- healthcheck:
- disable: false
- immich-machine-learning:
- container_name: immich_machine_learning
- image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
- volumes:
- - model-cache:/cache
- env_file:
- - stack.env
- 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
- 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:
- - ${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:
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