mirror of
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78 lines
2.8 KiB
YAML
78 lines
2.8 KiB
YAML
#
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# WARNING: Make sure to use the docker-compose.yml of the current release:
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#
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# https://github.com/immich-app/immich/releases/latest/download/docker-compose.yml
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#
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# The compose file on main may not be compatible with the latest release.
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#
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name: immich
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services:
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immich-server:
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container_name: immich_server
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image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
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command: ['start.sh', 'immich']
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volumes:
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- ${UPLOAD_LOCATION}:/usr/src/app/upload
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- /etc/localtime:/etc/localtime:ro
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env_file:
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- .env
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ports:
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- 2283:3001
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depends_on:
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- redis
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- database
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restart: always
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immich-microservices:
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container_name: immich_microservices
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image: ghcr.io/immich-app/immich-server:${IMMICH_VERSION:-release}
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# extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/hardware-transcoding
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# file: hwaccel.transcoding.yml
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# service: cpu # set to one of [nvenc, quicksync, rkmpp, vaapi, vaapi-wsl] for accelerated transcoding
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command: ['start.sh', 'microservices']
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volumes:
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- ${UPLOAD_LOCATION}:/usr/src/app/upload
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- /etc/localtime:/etc/localtime:ro
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env_file:
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- .env
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depends_on:
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- redis
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- database
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restart: always
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immich-machine-learning:
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container_name: immich_machine_learning
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# For hardware acceleration, add one of -[armnn, cuda, openvino] to the image tag.
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# Example tag: ${IMMICH_VERSION:-release}-cuda
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image: ghcr.io/immich-app/immich-machine-learning:${IMMICH_VERSION:-release}
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# extends: # uncomment this section for hardware acceleration - see https://immich.app/docs/features/ml-hardware-acceleration
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# file: hwaccel.ml.yml
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# service: cpu # set to one of [armnn, cuda, openvino, openvino-wsl] for accelerated inference - use the `-wsl` version for WSL2 where applicable
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volumes:
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- model-cache:/cache
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env_file:
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- .env
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restart: always
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redis:
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container_name: immich_redis
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image: registry.hub.docker.com/library/redis:6.2-alpine@sha256:84882e87b54734154586e5f8abd4dce69fe7311315e2fc6d67c29614c8de2672
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restart: always
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database:
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container_name: immich_postgres
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image: registry.hub.docker.com/tensorchord/pgvecto-rs:pg14-v0.2.0@sha256:90724186f0a3517cf6914295b5ab410db9ce23190a2d9d0b9dd6463e3fa298f0
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environment:
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POSTGRES_PASSWORD: ${DB_PASSWORD}
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POSTGRES_USER: ${DB_USERNAME}
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POSTGRES_DB: ${DB_DATABASE_NAME}
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POSTGRES_INITDB_ARGS: '--data-checksums'
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volumes:
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- ${DB_DATA_LOCATION}:/var/lib/postgresql/data
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restart: always
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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"]
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volumes:
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model-cache:
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