0.8.0 Alpha 5

Important

macOS first launch (no code signing yet). After dragging StemDeck to Applications, clear the Gatekeeper quarantine flag or macOS will say the app is damaged:

xattr -dr com.apple.quarantine /Applications/StemDeck.app

Optional: start from a clean slate. To reproduce a true first-run experience, open each path in Finder via the Go menu, then Go to Folder (Shift+Cmd+G), and move the folders to Trash:

• ~/Library/Application Support/StemDeck
• ~/Library/WebKit/app.stemdeck.desktop
• ~/Library/Caches/stemdeck
• ~/Library/Caches/app.stemdeck.desktop

You can also delete ~/Library/Preferences/app.stemdeck.desktop.plist the same way. This is optional; the app will work without it.

What's new in 0.8.0 Alpha 5

Faster Windows FFmpeg setup (Windows)

First-run setup downloaded FFmpeg from gyan.dev, a single mirror that is very slow outside North America. Users in Europe and Asia reported downloads crawling at 0.1 MB/s and the setup window showing "Not Responding" for many minutes at the "Checking FFmpeg" stage.

• Windows now downloads FFmpeg from the BtbN GitHub builds, served over GitHub's CDN, which is dramatically faster worldwide. The archive is still verified by SHA256 before it is used.
• StemDeck now detects an FFmpeg you place yourself in the data/ffmpeg folder, including the upstream layout where the binaries live in a bin/ subfolder. When you have already provided FFmpeg, setup skips the download entirely.

Fixes #248 and #244. Thanks to @unvency for suggesting the BtbN source, and to @albertchou667788-source for the report from Taiwan.

Installing

• macOS: drop the .app into Applications and launch (run the xattr command above first).
• Windows: unzip the downloaded .zip, then run StemDeck.exe from the extracted folder.
• Linux: download the .tar.gz for your hardware, extract it, and run ./StemDeck. Install the WebKitGTK + GTK runtime prerequisites first (FFmpeg is fetched automatically on first launch):

  sudo apt install libwebkit2gtk-4.1-0 libgtk-3-0
  

  The NVIDIA build additionally needs a working NVIDIA driver such that nvidia-smi reports your GPU (the CUDA runtime itself is bundled -- no separate CUDA toolkit install needed). If you have no NVIDIA GPU, use the CPU-only tarball.

Artifact scan

• Windows portable packages (CPU + NVIDIA) scanned with ClamAV in CI before upload.
• Linux portable packages (CPU + NVIDIA) scanned with ClamAV in CI before upload.

Artifact build

• macOS arm64 and x64 DMGs and runtime packs built and inspected on a macOS runner before upload.
• Windows portable ZIPs (CPU + NVIDIA) built on a Windows runner.
• Linux portable tarballs (CPU + NVIDIA) built on a Linux runner.