fix: move nightly whl to cuda version folder

[dougyster]

Motivation

For better organization, nightly whl files are added to the respective cuda version folder instead of the current generic nightly folder in the whl repo. Now, the folder structure is as follows:

cu129/

• index.html (sglang, sgl-kernel)
• /sglang (nightly whl)
• /sgl-kernel (sgl kernel)

The workflow now accepts a cuda python version as a parameter (defaults to cu129)

Modifications

Updated update_nightly_whl_index.py to place whl in the correct position, and auto detect the cuda python version (ie. if cuda-python=13.0, then whls will be placed in cu130)

Accuracy Tests

https://github.com/sgl-project/whl/tree/gh-pages/cu129

Installation of nightly whl works with: pip install sglang==0.5.8.dev0+g0189f41c3 --extra-index-url https://sgl-project.github.io/whl/cu129/

However, there is a hash mismatch for kernel 0.3.21 for x86_64 -
sgl_kernel-0.3.21-cp310-abi3-manylinux2014_x86_64.whl
is outdated or out of sync, and the newest hash is e7f66eb6a149ae2d1ea5a5bc29bc14cbb4322a23952d8d861eedbb253850c90f. This is unrelated to this code change, and someone likely created a new sgl-kernel whl and didn't update the index accordingly.

Benchmarking and Profiling

n/a

Checklist

• [Done ] Format your code according to the Format code with pre-commit.
• [Done ] Add unit tests according to the Run and add unit tests.
• [Done ] Update documentation according to Write documentations.
• [Done ] Provide accuracy and speed benchmark results according to Test the accuracy and Benchmark the speed.
• [Done ] Follow the SGLang code style guidance.

Review Process

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   • /tag-run-ci-label, /rerun-failed-ci, /tag-and-rerun-ci
4. After green CI and required approvals, ask Merge Oncalls to merge.

[gemini-code-assist]

Summary of Changes

Hello @dougyster, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request refactors the nightly wheel build process to introduce a more structured and organized repository layout. By dynamically detecting the CUDA version from project dependencies, it ensures that nightly wheel files are placed into dedicated CUDA-specific directories, making it easier to manage and access builds tailored to different CUDA environments. This change primarily affects the automation script responsible for updating the wheel index.

Highlights

• New Wheel Repository Structure: Nightly wheel files are now organized into CUDA version-specific folders (e.g., cu129/) instead of a single generic nightly/ folder, improving organization.
• Automated CUDA Version Detection: The update_nightly_whl_index.py script now automatically detects the CUDA Python version from the cuda-python dependency in pyproject.toml to determine the correct folder for wheel placement.
• Updated Index Generation Logic: The script's logic for generating index.html files has been updated to reflect the new folder structure and ensure proper linking for both sglang and sgl-kernel packages within the CUDA version directory.

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[gemini-code-assist]

Code Review

This pull request refactors the nightly wheel update script to organize wheels into CUDA version-specific folders. The changes include auto-detecting the CUDA version from pyproject.toml and updating the directory structure and index files accordingly. The implementation is solid, but I have one suggestion to improve the robustness of the CUDA version detection.

[Fridge003]

This might be not right. Since we don't have a pyproject.toml for cuda 130 now...
Is it possible to pass an argument the update_wheel_index function, indicating the version of Cuda?

[dougyster]

No problem! Thank you for pointing this out ~