* docs+scripts: install fixes — desktop-prod tauri resolution, Ubuntu white-screen guidance, honest GPU/prereq docs (#960 #961 #962) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> * docs(changelog): add the install-fixes batch under [Unreleased] (#964) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> --------- Co-authored-by: mergetest <test@local> Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
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OmniVoice Studio — Install on Linux
This page is self-contained: follow it top to bottom and you'll end up with a working OmniVoice Studio install on a Debian / Ubuntu / Fedora / Arch host.
Prerequisites
Using the AppImage or .deb
- Linux x86_64 with a desktop session (X11 or Wayland) capable of running a Tauri / WebKitGTK app.
- ~10 GB free disk for the app, its Python environment, and model weights.
- Optional: an NVIDIA driver for CUDA GPU acceleration — the app runs CPU-only without one. For AMD GPUs see AMD GPU (ROCm).
That's it — Python, FFmpeg, and the model weights are bundled or bootstrapped by the app itself on first launch. No toolchain needed.
Building from source
Everything above, plus the toolchain:
-
git —
sudo apt install git(Debian/Ubuntu),sudo dnf install git(Fedora), orsudo pacman -S git(Arch). -
curl — usually preinstalled; used by the Bun and rustup install one-liners below.
-
Python 3.11+ — typically
sudo apt install python3.11on Debian/Ubuntu,sudo dnf install python3.11on Fedora, or already installed on Arch. -
Bun —
curl -fsSL https://bun.sh/install | bash. -
FFmpeg —
sudo apt install ffmpeg(Debian/Ubuntu),sudo dnf install ffmpeg-free(Fedora), orsudo pacman -S ffmpeg(Arch). -
Rust / Cargo —
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | shor via your package manager (e.g.,sudo apt install rustc cargo). If you use rustup, reopen the shell or source"$HOME/.cargo/env"before runningbun run desktop-prod. -
GTK/WebKit deps for the Tauri shell:
# Debian / Ubuntu sudo apt install libwebkit2gtk-4.1-dev libayatana-appindicator3-dev librsvg2-dev libssl-dev libxdo-dev build-essential # Fedora sudo dnf install webkit2gtk4.1-devel libappindicator-gtk3-devel librsvg2-devel openssl-devel # Arch sudo pacman -S --needed base-devel webkit2gtk-4.1 libayatana-appindicator librsvg openssl xdotool -
Optional: a Hugging Face token for diarization + the larger TTS engines (see docs/setup/huggingface-token.md).
Install (from source)
git clone https://github.com/debpalash/OmniVoice-Studio.git
cd OmniVoice-Studio
bun install
bun run desktop-prod
The first launch creates the Python venv via uv, syncs deps, and downloads
model weights (~2.4 GB). Subsequent launches start in seconds.
Install (AppImage)
Download the latest AppImage from the Releases page, make it executable, and run:
chmod +x OmniVoice.Studio_*.AppImage
./OmniVoice.Studio_*.AppImage
No FUSE? Use --appimage-extract-and-run:
./OmniVoice.Studio_*.AppImage --appimage-extract-and-run
Install (.deb)
sudo apt install ./OmniVoice.Studio_*.amd64.deb
omnivoice-studio
The desktop app uses these canonical paths (kept in sync with
scripts/desktop-prod.sh by the docs-drift CI gate):
APP_ID="com.debpalash.omnivoice-studio"
APP_NAME="OmniVoice Studio"
AppImage white screen / EGL errors (Fedora 44, Ubuntu 24.04+, 26.04)
Two separate WebKitGTK rendering issues land the Tauri window as a
fully-white frame with no UI. Which one you have depends on your WebKitGTK
version (pkg-config --modversion webkit2gtk-4.1 prints it).
Modern WebKitGTK (2.48+ — Ubuntu 24.04 and newer, incl. 26.04): try this first. WebKit's DMA-BUF renderer fails against some GPU drivers; the terminal typically shows:
Could not create default EGL display: EGL_BAD_PARAMETER
Disable the DMA-BUF renderer before launching:
WEBKIT_DISABLE_DMABUF_RENDERER=1 ./OmniVoice.Studio_*.AppImage
WebKitGTK 2.44 / 2.46 (Fedora 44, Ubuntu 24.04 at release): a compositing-mode regression blanks the surface on first paint. Disable compositing mode instead:
WEBKIT_DISABLE_COMPOSITING_MODE=1 ./OmniVoice.Studio_*.AppImage
OmniVoice's AppRun launcher autodetects the broken 2.44/2.46 range and sets this second variable for you (shipped in v0.3+). The manual env-var path remains the documented fallback when running from a checked-out source tree.
Last resort — if neither variable alone helps, force software rendering (slower, but always paints):
WEBKIT_DISABLE_DMABUF_RENDERER=1 LIBGL_ALWAYS_SOFTWARE=1 ./OmniVoice.Studio_*.AppImage
.deb ffprobe conflict
Pre-v0.3 .deb packages installed ffprobe into /usr/bin/ffprobe and
clobbered the system copy on some distros. v0.3+ relocates the bundled
binary into /usr/lib/omnivoice-studio/bin/ffprobe and the postrm script
runs dpkg --search to undo the old conflict on upgrade. If you upgraded
from a pre-v0.3 .deb and ffprobe -version now reports the wrong binary,
re-install the system package:
sudo apt install --reinstall ffmpeg
Restricted networks (China / Russia)
If uv times out fetching the python-build-standalone tarball or PyPI:
# Use a faster Python source mirror (China only — verify a current mirror)
export UV_PYTHON_INSTALL_MIRROR=https://ghproxy.com/https://github.com/astral-sh/python-build-standalone/releases/download
# Use a PyPI mirror
export UV_DEFAULT_INDEX=https://pypi.tuna.tsinghua.edu.cn/simple
# Or skip the download entirely if you have a compatible system Python
export UV_PYTHON_PREFERENCE=only-system
# Be tolerant of slow links
export UV_HTTP_TIMEOUT=120
export UV_HTTP_RETRIES=5
The Phase 3 install milestone (INST-07..11) ships an OS-level mirror cascade that picks these defaults automatically; for v0.3 set them by hand.
AMD GPU (ROCm)
ROCm support is Linux-only and opt-in. The default install ships the
CUDA build of PyTorch (the pytorch-cuda index in pyproject.toml), so on
an AMD-only machine torch.cuda.is_available() is False and OmniVoice runs
on CPU until you opt into the ROCm variant. (On Windows there is no ROCm path
at all — PyTorch publishes no Windows ROCm wheels; see
windows.md.)
Three ways to opt in, in order of preference:
1. First-run setup screen (recommended). On Linux the setup screen's
Compute card offers "AMD GPU (ROCm, Linux)" next to the default
Auto. When OmniVoice detects an AMD GPU and the ROCm userspace
(/opt/rocm present, or rocminfo on PATH), the ROCm option is pre-selected;
with an AMD GPU but no ROCm runtime it stays offered-but-unselected — install
ROCm first (or continue on CPU). Choosing ROCm makes the bootstrap reinstall
torch/torchaudio from the ROCm wheel index
(https://download.pytorch.org/whl/rocm6.2 by default) right after the
dependency sync.
2. Environment variable (existing installs / headless). Set
OMNIVOICE_TORCH_VARIANT=rocm before launching — the next bootstrap performs
the same ROCm reinstall. OMNIVOICE_TORCH_INDEX=<url> overrides the wheel
index when you need a different ROCm version
(pytorch.org lists available
wheels). If the reinstall fails (network, unsupported card), OmniVoice keeps
the default torch build and warns instead of breaking the install.
3. Manual wheel swap (fallback). Replace torch with the ROCm wheel after the first-run install populates the venv:
# From the project directory (source install), into OmniVoice's uv venv.
# Current stable is ROCm 6.2 — match your installed ROCm/driver version
# (https://pytorch.org/get-started/locally/ lists available wheels).
uv pip install --reinstall torch torchaudio \
--index-url https://download.pytorch.org/whl/rocm6.2
Once a ROCm build of PyTorch is in the venv, detection is automatic —
get_best_device() returns the GPU (ROCm-built PyTorch reports through
torch.cuda.is_available()), and OmniVoice auto-sets
HSA_OVERRIDE_GFX_VERSION for consumer cards whose GFX ID isn't in the
official ROCm support matrix. Relaunch and the Settings → System panel should
report the GPU device instead of cpu. Verify the wheel sees your card:
uv run python -c "import torch; print(torch.cuda.is_available(), torch.cuda.get_device_name(0))"
Notes:
- ROCm is exercised far less than the default CUDA/MPS/CPU paths — it works, but expect rough edges on consumer cards and report what you hit.
- Unsupported GFX (e.g. some consumer RDNA cards): if it still won't run, set
HSA_OVERRIDE_GFX_VERSIONyourself (e.g.export HSA_OVERRIDE_GFX_VERSION=11.0.0) to the nearest supported architecture before launching. - ZLUDA (CUDA-on-ROCm translation) can work but is unsupported here — prefer a native ROCm wheel.
Tracking issue: #124.
Hugging Face token (optional but recommended)
See docs/setup/huggingface-token.md.
Troubleshooting
Hit a wall? See docs/install/troubleshooting.md.