Skip to content

[Misc] ADD Docker compose exemple #20210

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: main
Choose a base branch
from

Conversation

maher-naija-pro
Copy link

@maher-naija-pro maher-naija-pro commented Jun 28, 2025

Essential Elements of an Effective PR Description Checklist

  • [x ] 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.
  • [x ] The test results, such as pasting the results comparison before and after, or e2e results
  • [ x] (Optional) The necessary documentation update, such as updating supported_models.md and examples for a new model.

Purpose

Easy start vllm server with docker compose

Test Plan

NB: update tockn and model name on docker compose file

docker-compose up -d

Test Result

docker ps
=> vllm started

(Optional) Documentation Update

To start vllm with docker compose

Update env var with your token and model name

start docker compose

docker-compose up -d

Copy link

👋 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.

🚀

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 @maher-naija-pro, 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 a new Docker Compose example to streamline the deployment and startup of the vLLM server. The provided configuration aims to simplify the process for users to quickly launch a vLLM instance with GPU support.

Highlights

  • New Docker Compose Example: I've added a new file, docker-compose.yml-exemple, which provides a complete Docker Compose configuration to easily set up and run the vLLM server.
  • vLLM Service Configuration: The example defines a vllm service using the vllm/vllm-openai:v0.9.1 image, configured with nvidia runtime for GPU access, port 8000 mapping, and a volume for models.
  • Customizable Server Parameters: The command section within the Docker Compose file includes placeholders and examples for common vLLM server arguments such as --model, --tensor-parallel-size, --compilation-config, and --gpu-memory-utilization, along with an environment variable for HUGGING_FACE_HUB_TOKEN.
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 docker-compose example to help users start the vLLM server. I've added comments to improve the example's correctness and clarity, focusing on the model caching mechanism and correcting a typo.

ports:
- "8000:8000"
volumes:
- models:/models
Copy link
Contributor

Choose a reason for hiding this comment

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

high

The current volume configuration mounts a volume at /models, but vLLM and the underlying Hugging Face libraries download models to /root/.cache/huggingface by default. This means models won't be persisted in the models volume as intended. To correctly cache the models, you should mount the volume to /root/.cache/huggingface.

      - models:/root/.cache/huggingface

volumes:
- models:/models
environment:
HUGGING_FACE_HUB_TOKEN: "YOUR TOKEN HERE"
Copy link
Contributor

Choose a reason for hiding this comment

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

high

To ensure that models are stored in the correctly mounted volume, you should explicitly set the HF_HOME environment variable. This directs the Hugging Face library to use the specified path for caching.

      HF_HOME: /root/.cache/huggingface
      HUGGING_FACE_HUB_TOKEN: "YOUR TOKEN HERE"

HUGGING_FACE_HUB_TOKEN: "YOUR TOKEN HERE"
restart: always
command: >
--model YOUR-MODEL-NALE
Copy link
Contributor

Choose a reason for hiding this comment

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

medium

Typo: YOUR-MODEL-NALE should be YOUR-MODEL-NAME.

      --model YOUR-MODEL-NAME

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

Successfully merging this pull request may close these issues.

1 participant