Skip to content

Conversation

houseroad
Copy link
Collaborator

@houseroad houseroad commented Jul 2, 2025

Essential Elements of an Effective PR Description Checklist

  • The purpose of the PR, such as "Fix some issue (link existing issues this PR will resolve)".
  • The test plan, such as providing test command.
  • The test results, such as pasting the results comparison before and after, or e2e results
  • (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

Tag DeepSeek related PRs to organize the review.

Test Plan

Simulated in the mergify on a few PRs, like #20322

Test Result

Tagged as expected.

(Optional) Documentation Update

N/A

Signed-off-by: Lu Fang <lufang@fb.com>
@houseroad houseroad requested review from ywang96 and comaniac July 2, 2025 10:43
Copy link
Contributor

@gemini-code-assist gemini-code-assist bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Summary of Changes

Hello @houseroad, 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 introduces an automated labeling rule to streamline the review process for changes related to DeepSeek models. By automatically applying a 'deepseek' label, it aims to improve the organization and discoverability of relevant pull requests, making it easier for reviewers to identify and prioritize them.

Highlights

  • Automated Labeling: A new Mergify rule, label-deepseek, has been added to automatically apply the 'deepseek' label to relevant pull requests.
  • Labeling Conditions: The 'deepseek' label is applied if the PR title contains 'DeepSeek' (case-insensitive) or if any changed files match specific DeepSeek-related paths within examples/, tests/, vllm/entrypoints/openai/tool_parsers/, vllm/model_executor/models/, vllm/reasoning/, or vllm/transformers_utils/ directories.
Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point in your pull request via creating an issue comment (i.e. comment on the pull request page) using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands.

Feature Command Description
Code Review /gemini review Performs a code review for the current pull request in its current state.
Pull Request Summary /gemini summary Provides a summary of the current pull request in its current state.
Comment @gemini-code-assist Responds in comments when explicitly tagged, both in issue comments and review comments.
Help /gemini help Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist is currently in preview and may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments to provide feedback.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

  1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution.

Copy link
Contributor

@gemini-code-assist gemini-code-assist bot left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Code Review

This pull request adds a Mergify rule to automatically label PRs related to DeepSeek. The logic is sound, but I've suggested a couple of improvements to the file matching patterns to make them more robust and comprehensive. Specifically, I recommend using case-insensitive matching and broadening the pattern for the examples directory to include non-Python files.

Comment on lines +34 to +39
- files~=^examples/.*deepseek.*\.py
- files~=^tests/.*deepseek.*\.py
- files~=^vllm/entrypoints/openai/tool_parsers/.*deepseek.*\.py
- files~=^vllm/model_executor/models/.*deepseek.*\.py
- files~=^vllm/reasoning/.*deepseek.*\.py
- files~=^vllm/transformers_utils/.*deepseek.*\.py
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

medium

This is a good start for automatically labeling DeepSeek-related PRs. I have a couple of suggestions to make it more robust:

  1. Broader file matching for examples: The current pattern for the examples directory (^examples/.*deepseek.*\.py) only matches Python files. However, the repository also contains .jinja files related to DeepSeek in that directory (e.g., tool_chat_template_deepseekr1.jinja). I'd recommend a more general pattern to catch these as well.

  2. Case-insensitive matching: The file path matching is currently case-sensitive. To make the rules more robust against variations in file naming (e.g., deepseek.py vs. DeepSeek.py), it would be better to use case-insensitive matching for all file paths.

Here is a suggestion that incorporates both points.

      - files~=(?i)^examples/.*deepseek.*
      - files~=(?i)^tests/.*deepseek.*\.py
      - files~=(?i)^vllm/entrypoints/openai/tool_parsers/.*deepseek.*\.py
      - files~=(?i)^vllm/model_executor/models/.*deepseek.*\.py
      - files~=(?i)^vllm/reasoning/.*deepseek.*\.py
      - files~=(?i)^vllm/transformers_utils/.*deepseek.*\.py

Copy link

github-actions bot commented Jul 2, 2025

👋 Hi! Thank you for contributing to the vLLM project.

💬 Join our developer Slack at https://slack.vllm.ai to discuss your PR in #pr-reviews, coordinate on features in #feat- channels, or join special interest groups in #sig- channels.

Just a reminder: PRs would not trigger full CI run by default. Instead, it would only run fastcheck CI which starts running only a small and essential subset of CI tests to quickly catch errors. You can run other CI tests on top of those by going to your fastcheck build on Buildkite UI (linked in the PR checks section) and unblock them. If you do not have permission to unblock, ping simon-mo or khluu to add you in our Buildkite org.

Once the PR is approved and ready to go, your PR reviewer(s) can run CI to test the changes comprehensively before merging.

To run CI, PR reviewers can either: Add ready label to the PR or enable auto-merge.

🚀

@houseroad houseroad requested a review from DarkLight1337 July 2, 2025 10:48
@vllm-bot vllm-bot merged commit 0c600b9 into vllm-project:main Jul 2, 2025
10 of 12 checks passed
@mergify mergify bot added the deepseek Related to DeepSeek models label Jul 2, 2025
huydhn pushed a commit to huydhn/vllm that referenced this pull request Jul 8, 2025
LyrisZhong pushed a commit to LyrisZhong/vllm that referenced this pull request Jul 23, 2025
avigny pushed a commit to avigny/vllm that referenced this pull request Jul 31, 2025
Signed-off-by: Lu Fang <lufang@fb.com>
Signed-off-by: avigny <47987522+avigny@users.noreply.github.com>
Pradyun92 pushed a commit to Pradyun92/vllm that referenced this pull request Aug 6, 2025
jinzhen-lin pushed a commit to jinzhen-lin/vllm that referenced this pull request Aug 9, 2025
Signed-off-by: Lu Fang <lufang@fb.com>
Signed-off-by: Jinzhen Lin <linjinzhen@hotmail.com>
googlercolin pushed a commit to googlercolin/vllm that referenced this pull request Aug 29, 2025
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
ci/build deepseek Related to DeepSeek models
Projects
None yet
Development

Successfully merging this pull request may close these issues.

3 participants