I'm not sure if I got your issue, but I can do platform-dependent `index` `pytorch` installation using the following snippet in `pyproject.toml` and `uv sync` just handles it accordingly.
Some Windows machines have compatible GPUs while others don't, so this doesn't necessarily help. What is really required is querying the OS for what type of compute unit it has and then installing the right version of an ML library, but I'm not sure that will be done.
I happened to use uv recently for a pet project, and I totally agree with you. It's really really good. I couldn't believe its dependency resolution and pulling can be so fast. Imho, it's the python package manager (I don't know the most suitable name to categorize it) done right, everything just works, the correct way.
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