b8efe4732d
Accumulated uncommitted infra changes: - Caddyfile: repoint HA/Zabbix to 192.168.1.4/.3, add ~20 new site routes - Immich: move media to /mnt/smsg, enable CUDA ML, mem limits, rewrite backup.sh - Add service stacks: agap-mcp, anki, family, freshrss, iperf3, kanboard, linkwarden, qbittorrent, radicale, syncthing, vikunja, windows - openwebui: enable API keys; ollama: drop CPU fallback - seafile/zabbix: extra_hosts entries; matrix: add user juris - Remove pihole stack and stale wiki/migrate.py - Ignore marketplace-mcp (standalone repo) and linkwarden runtime data Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LeqyaxJF2nbRXJtae2kNB2
58 lines
1.4 KiB
YAML
58 lines
1.4 KiB
YAML
# Configurations for hardware-accelerated machine learning
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# If using Unraid or another platform that doesn't allow multiple Compose files,
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# you can inline the config for a backend by copying its contents
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# into the immich-machine-learning service in the docker-compose.yml file.
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# See https://docs.immich.app/features/ml-hardware-acceleration for info on usage.
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services:
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armnn:
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devices:
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- /dev/mali0:/dev/mali0
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volumes:
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- /lib/firmware/mali_csffw.bin:/lib/firmware/mali_csffw.bin:ro # Mali firmware for your chipset (not always required depending on the driver)
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- /usr/lib/libmali.so:/usr/lib/libmali.so:ro # Mali driver for your chipset (always required)
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rknn:
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security_opt:
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- systempaths=unconfined
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- apparmor=unconfined
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devices:
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- /dev/dri:/dev/dri
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cpu: {}
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cuda:
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: 1
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capabilities:
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- gpu
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rocm:
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group_add:
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- video
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devices:
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- /dev/dri:/dev/dri
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- /dev/kfd:/dev/kfd
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openvino:
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device_cgroup_rules:
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- 'c 189:* rmw'
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devices:
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- /dev/dri:/dev/dri
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volumes:
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- /dev/bus/usb:/dev/bus/usb
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openvino-wsl:
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devices:
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- /dev/dri:/dev/dri
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- /dev/dxg:/dev/dxg
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volumes:
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- /dev/bus/usb:/dev/bus/usb
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- /usr/lib/wsl:/usr/lib/wsl
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