feat(unraid): publish container to GHCR and add Community Applications app - #253
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…s template - add docker-publish workflow: build build/Dockerfile and push ghcr.io/stemdeckapp/stemdeck on release + manual dispatch (linux/amd64) - add templates/stemdeck.xml: Unraid Docker template (port 8000, /app/jobs + /cache volumes, persistent library default, optional NVIDIA runtime vars) - add ca_profile.xml at repo root for the CA submission scan - document the GHCR image and Unraid install in README The published image keeps the default Linux x86_64 (CUDA) torch wheel, so a single image runs on CPU by default and uses the GPU when started with --runtime=nvidia; _detect_device() auto-selects CUDA.
Drop the workflow_dispatch version input and compute it with git describe (hatch-vcs style) so manual builds carry a real dev version. Fetch full history + tags on checkout so git describe resolves.
Add a push trigger on main so every merge builds and pushes ghcr.io/stemdeckapp/stemdeck:edge. :edge never moves :latest, which stays reserved for stable releases.
…n the run example
Align DEFAULT_PORT (app/core/settings.py) and the desktop launcher's configured_port() fallback (desktop/src-tauri/src/main.rs) from 8080 to 8000 so every path -- container, run.sh, and desktop -- shares one default. Update the settings comment and the port-default test accordingly.
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What
Makes StemDeck installable on Unraid via Community Applications (CA), and publishes the server container to GHCR so any self-hosted deployment can pull it.
No application code changes: the existing server container (
build/Dockerfile) already runs the same FastAPI app. This is purely distribution.Changes
.github/workflows/docker-publish.yml- buildsbuild/Dockerfileand pushesghcr.io/stemdeckapp/stemdeckonrelease: published(and manualworkflow_dispatch). linux/amd64, GHCR login viaGITHUB_TOKEN, action SHAs pinned.templates/stemdeck.xml- Unraid Docker template: port 8000,/app/jobs+/cachevolumes mapped to appdata,STEMDECK_PERSIST_LIBRARY=1default, optional NVIDIA runtime vars, 1024x1024 icon fromdesktop/src-tauri/icons/icon.png.ca_profile.xml(repo root) - author profile read by the CA submission scan.README.md- GHCRdocker runsnippet + an Unraid install subsection.Why one image covers CPU and GPU
The image keeps the default Linux x86_64 torch wheel, which is the CUDA build (the desktop tarballs swap it to CPU in
scripts/linux/make-portable.sh, but the container does not)._detect_device()inapp/core/config.pyauto-selects CUDA whentorch.cuda.is_available(). So the same image runs on CPU by default and uses the GPU when started with--runtime=nvidia.Validation
xmllint --nooutpasses on both XML files.Manual follow-ups (not in this PR)
Support/Forumat it (currently GitHub issues).Known limitation
RTX 50-series (Blackwell / sm_120) may fall back to CPU: torch 2.6 + cu124 predates sm_120, and the project pins away from torch 2.7+ due to the torchaudio writer removal. Noted in the template Overview.