vault backup: 2024-03-10 02:48:00
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@@ -165,4 +165,90 @@ docker run -d \
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-v /var/run/docker.sock:/var/run/docker.sock \
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containrrr/watchtower -c \
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--schedule "0 0 3 * * *"
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```
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```
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# Reader
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`docker run -d --restart=always --name=reader -v /mnt/usb3-1/reader/logs:/logs -v /mnt/usb3-1/reader/storage:/storage -p 4567:8080 hectorqin/reader java -jar /app/bin/reader.jar --spring.profiles.active=prod --reader.app.secure=true --reader.app.secureKey=Saligia7 --reader.app.inviteCode=Saligia7`
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# Immich
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```yaml
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version: '3.8'
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#
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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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- ${UPLOAD_LOCATION}:/usr/src/app/upload
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env_file:
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- stack.env
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ports:
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- 2283:3001
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depends_on:
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- redis
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- database
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restart: always
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immich-microservices:
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container_name: immich_microservices
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image: ghcr.io/immich-app/immich-server:${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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env_file:
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- stack.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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- /mnt/sata3-1/immich/model-cache:/cache
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env_file:
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- stack.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@sha256:51d6c56749a4243096327e3fb964a48ed92254357108449cb6e23999c37773c5
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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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volumes:
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- /mnt/sata3-1/immich/pgdata:/var/lib/postgresql/data
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restart: always
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```
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# Uptime-Kuma
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`docker run -d --restart=always -p 3001:3001 -v uptime-kuma:/app/data --name uptime-kuma louislam/uptime-kuma:latest`
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