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allign port number for vLLM Docker run command with example config file#109

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anandhu-eng wants to merge 3 commits intomainfrom
anandhu-eng-patch-1
Open

allign port number for vLLM Docker run command with example config file#109
anandhu-eng wants to merge 3 commits intomainfrom
anandhu-eng-patch-1

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What does this PR do?

Type of change

  • Bug fix
  • New feature
  • Documentation update
  • Refactor/cleanup

Related issues

Testing

  • Tests added/updated
  • All tests pass locally
  • Manual testing completed

Checklist

  • Code follows project style
  • Pre-commit hooks pass
  • Documentation updated (if needed)

@anandhu-eng anandhu-eng requested a review from a team as a code owner January 29, 2026 21:42
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github-actions bot commented Jan 29, 2026

MLCommons CLA bot All contributors have signed the MLCommons CLA ✍️ ✅

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Summary of Changes

Hello @anandhu-eng, 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 primarily focuses on a documentation update. It corrects an inconsistency in the example vLLM Docker run command within the Readme.md file, ensuring the exposed port aligns with the intended configuration. This change improves the accuracy of the provided example for users.

Highlights

  • Documentation Update: The Readme.md file for the 04_GPTOSS120B_Example has been updated to align the port number used in the vLLM Docker run command from 8000 to 3000.

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Code Review

This pull request updates the port number in the vLLM Docker run command to align with the example configuration file, which is a good correction. However, the documentation update is incomplete. The 'Debugging' section still contains references to the old port number, which could cause confusion. I've added a comment suggesting updates to that section for consistency.


```
docker run --runtime nvidia --gpus all -v ${HF_HOME}:/root/.cache/huggingface --env "HUGGING_FACE_HUB_TOKEN=$HF_TOKEN" -p 8000:8000 --ipc=host vllm/vllm-openai:latest --model ${MODEL_NAME} --gpu_memory_utilization 0.95
docker run --runtime nvidia --gpus all -v ${HF_HOME}:/root/.cache/huggingface --env "HUGGING_FACE_HUB_TOKEN=$HF_TOKEN" -p 3000:3000 --ipc=host vllm/vllm-openai:latest --model ${MODEL_NAME} --gpu_memory_utilization 0.95
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medium

This change correctly aligns the vLLM port with the configuration file. However, the 'Debugging' section in this file is now outdated as it still refers to port 8000.

To maintain consistency, please update the mitmproxy command and the related explanation in the 'Debugging' section to use port 3000.

For example, line 70 should be:

mitmproxy -p 8001  --mode reverse:http://localhost:3000/

The surrounding text should also be updated to refer to port 3000.

Additionally, there's a typo on line 73: mitmproxy is launched on port 8001, not 8081.

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+1

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