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Document the uv install route, and the prerequisites it cannot cover - #1

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Document the uv install route, and the prerequisites it cannot cover#1
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@rysk-t rysk-t commented Sep 4, 2026

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The site's install guide describes only the conda route, so nothing here mentions uv — even though the YORU repository ships its own pyproject.toml and uv.lock, and as of v1.1.2 uv is the only supported route on macOS. This brings the docs in line with Kamikouchi-lab/YORU#41 and the v1.1.2 release.

_guides/01_install.md — restructured around two routes

Install with uv (new): how to install uv itself (winget on Windows, the install script or Homebrew elsewhere), then git cloneuv syncuv run yoru. Notes that no system Python and no conda are needed, since uv fetches the Python 3.10 the project pins, and that YORU has to be run from the repository root — the launcher resolves web/ and config/ relative to the working directory.

Install with conda: unchanged apart from the CUDA note below. The step numbering skipped 2, which is also fixed.

Prerequisites (new), the pieces neither installer can provide:

  • A Chromium browser. The launcher is served by Eel, which uses its chrome mode, so the guide now says exactly where Eel looks on each OS (the App Paths\chrome.exe registry key on Windows; Google Chrome.appChromium.appmdfind on macOS; four binary names on PATH on Linux) and quotes the error you get when it finds nothing. Microsoft Edge is Chromium-based but registers as msedge.exe, so Eel does not find it, and Safari is unsupported by Eel — worth stating, since both are reasonable things to try. Only the launcher needs a browser; every other GUI is a native window.
  • An NVIDIA driver. Driver versions that support CUDA 12.x (527.41+ on Windows, 525.60.13+ on Linux), and how to check with nvidia-smi.
  • macOS. macOS 14+ on Apple Silicon (Intel Macs cannot work: the macOS wheels of the pinned PyTorch and Qt are arm64 only), xcode-select --install before uv sync because imgui and gevent publish no arm64 wheels and are compiled during the sync, and the Camera / Input Monitoring / Screen Recording prompts that appear on first use.

Choosing the compute device (new): the CUDA → MPS → CPU order, the YORU_DEVICE override and the training-GUI selector added in v1.1.2, plus the MPS-vs-CPU realtime inference note.

The CUDA toolkit is not required

Both install pages said to install the CUDA toolkit. It is not needed on either route: the PyTorch wheels ship the CUDA runtime themselves (cudart, cuBLAS and cuDNN live inside the installed torch package). Verified on a Windows box with no toolkit at all — no nvcc on PATH, CUDA_PATH unset — where torch.version.cuda reports 12.4 and CUDA training runs.

The pages now ask for the driver, and note that the CUDA Version printed by nvidia-smi is the driver's ceiling rather than the version in use, which is the usual source of the confusion. The toolkit is presented as optional, for nvcc and the profilers.

Version pointers → v1.1.2

_config.yml, the home.md versions table and guides link, the banner in _guides/01_install.md, the stable-release references in beta.md (plus a v1.1.2 row in its version history), and the stable pointer in _beta_guides/01_install.md.

home.md also mirrors the README changes: an "Install via uv" section, a "Compute device" section, and Requirements updated with the OS matrix, the driver requirement and a Software list.

Note on the beta pages

I deliberately kept these to a minimum, since Beta 2 is a different code line: only the stable-version pointer and the CUDA toolkit correction (which applies to the beta's wheels just the same). The beta guide's existing "Alternative: install with uv" section is left as is. Drop that commit hunk if you would rather the beta pages move separately.

The install guide only described the conda route, so nothing on the site
mentioned uv even though the repository ships pyproject.toml and uv.lock, and
uv is now the only supported route on macOS. It also asked readers to install
the CUDA toolkit, which is not needed: the PyTorch wheels carry their own CUDA
runtime, so what has to be present is the driver.

The stable install guide is restructured around the two routes with a shared
prerequisites section: the Chromium browser Eel needs (with what it looks for
on each OS, and why Edge and Safari do not work), the NVIDIA driver, and the
Apple Silicon requirements -- macOS 14+, the Xcode Command Line Tools that the
imgui and gevent source builds need, and the Camera / Input Monitoring /
Screen Recording prompts. A section on choosing the compute device covers
YORU_DEVICE and the training-GUI selector added in v1.1.2.

home.md mirrors the README changes, and the stable version pointers move to
v1.1.2 across the site.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01G3rHpfKzAnmYkxhmvHKwiP
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