Add a complete example for the most common publishing workflow, GitHub
Actions to PyPI, with screenshots for settings and a standalone
companion repo.
Closes#14398
<!--
Thank you for contributing to uv! To help us out with reviewing, please
consider the following:
- Does this pull request include a summary of the change? (See below.)
- Does this pull request include a descriptive title?
- Does this pull request include references to any relevant issues?
-->
## Summary
<!-- What's the purpose of the change? What does it do, and why? -->
Upgrade checkout action to v5 --
https://github.com/actions/checkout/releases
## Test Plan
<!-- How was it tested? -->
This PR adds a new integrations doc page for using uv with
[Coiled](https://coiled.io/). It's a slightly adapted version of this
blog post https://docs.coiled.io/blog/uv-coiled-cloud-scripts.html
Side note: it's been really pleasant using uv and Coiled together
recently
cc @zanieb for visibility
---------
Co-authored-by: Zanie Blue <contact@zanie.dev>
<!--
Thank you for contributing to uv! To help us out with reviewing, please
consider the following:
- Does this pull request include a summary of the change? (See below.)
- Does this pull request include a descriptive title?
- Does this pull request include references to any relevant issues?
-->
## Summary
Closes#15586
<!--
Thank you for contributing to uv! To help us out with reviewing, please
consider the following:
- Does this pull request include a summary of the change? (See below.)
- Does this pull request include a descriptive title?
- Does this pull request include references to any relevant issues?
-->
## Summary
i noticed some of the line highlights are wrong in the docs
## Test Plan
visual verification
## Summary
Follow up to
https://github.com/astral-sh/uv/pull/15269#issuecomment-3194000772
Enables the following additional images to be published
* buildpack-deps:trixie
* debian:trixie-slim
* alpine:3.22
## Test Plan
Existing Tests. The newly added images were checked manually.
I updated the Github Actions integration guide to run Github's
`setup-python` before Astral's `setup-uv`, as `setup-uv`'s
`activate-environment: true` doesn't work with the original ordering.
There is a discussion about this behavior in the `setup-uv` repo
[here](https://github.com/astral-sh/setup-uv/issues/479).
<!--
Thank you for contributing to uv! To help us out with reviewing, please
consider the following:
- Does this pull request include a summary of the change? (See below.)
- Does this pull request include a descriptive title?
- Does this pull request include references to any relevant issues?
-->
## Summary
Update the documentation for the Github Actions integration. Caveat: I'm
unsure if there are any other reasons where the original ordering (that
is,`setup-uv` before `setup-python`) might be preferred.
## Test Plan
Tested in a private Github Actions push, as documented in the
aforementioned discussion on `setup-uv`'s repo. Confirmed that removing
`source .venv/bin/activate` and replacing it with `activate-environment:
true` now works in this ordering (but didn't work with the original
ordering where `uv` installs before Github's `python`).
Closes#13057
Sets `UV_TOOL_BIN_DIR` to `/usr/local/bin` for all derived images to
allow `uv tool install` to work out of the box.
Note, when the default image user is overwritten (e.g. `USER <UID>`) by
a less privileged one, an alternative writable location would now need
to be set by downstream consumers to prevent issues, hence I'm labeling
this as a breaking change for 0.8.x release.
Relates to https://github.com/astral-sh/uv-docker-example/pull/55
Each image was tested to work with uv tool with `UV_TOOL_BIN_DIR` set to
`/usr/local/bin` with the default root user and alternative non-root
users to confirm breaking nature of the change.
## Summary
This PR intends to enable `--torch-backend=auto` to detect Intel GPUs
automatically:
- On Linux, detection is performed using the `lspci` command via
`Display controller` id.
- On Windows, ~~detection is done via a `powershell` query to
`Win32_VideoController`~~. Skip support for now—revisit once a better
solution is available.
Currently, Intel GPUs (XPU) do not rely on specific driver or toolkit
versions to distribute different PyTorch wheels.
## Test Plan
<!-- How was it tested? -->
On Linux:

~~On Windows:
~~
---------
Co-authored-by: Charlie Marsh <charlie.r.marsh@gmail.com>
## Summary
Allows `--torch-backend=auto` to detect AMD GPUs. The approach is fairly
well-documented inline, but I opted for `rocm_agent_enumerator` over
(e.g.) `rocminfo` since it seems to be the recommended approach for
scripting:
https://rocm.docs.amd.com/projects/rocminfo/en/latest/how-to/use-rocm-agent-enumerator.html.
Closes https://github.com/astral-sh/uv/issues/14086.
## Test Plan
```
root@rocm-jupyter-gpu-mi300x1-192gb-devcloud-atl1:~# ./uv-linux-libc-11fb582c5c046bae09766ceddd276dcc5bb41218/uv pip install torch --torch-backend=auto
Resolved 11 packages in 251ms
Prepared 2 packages in 6ms
Installed 11 packages in 257ms
+ filelock==3.18.0
+ fsspec==2025.5.1
+ jinja2==3.1.6
+ markupsafe==3.0.2
+ mpmath==1.3.0
+ networkx==3.5
+ pytorch-triton-rocm==3.3.1
+ setuptools==80.9.0
+ sympy==1.14.0
+ torch==2.7.1+rocm6.3
+ typing-extensions==4.14.0
```
---------
Co-authored-by: Zanie Blue <contact@zanie.dev>
## Summary
<!-- What's the purpose of the change? What does it do, and why? -->
Replace wrong `cuda124` version to the correct `cuda128` version in
torch docs
## Test Plan
<!-- How was it tested? -->
<!--
Thank you for contributing to uv! To help us out with reviewing, please
consider the following:
- Does this pull request include a summary of the change? (See below.)
- Does this pull request include a descriptive title?
- Does this pull request include references to any relevant issues?
-->
## Summary
I follow the advices from the IDE spell checker and grammar checker, fix
some typos, and improve the docs.