refactor example - qwen3_reranker

[reidliu41]

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

• Move the to main, make the entrypoint clean and keep the same style with the other examples

Test Plan

Test Result

(Optional) Documentation Update

[gemini-code-assist]

Summary of Changes

Hello @reidliu41, 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 focuses on refactoring the qwen3_reranker.py example script to improve its overall structure, readability, and consistency with standard Python practices. The changes involve encapsulating model initialization and main execution logic into functions, making the script's entry point cleaner and more maintainable.

Highlights

• Code Structure Refinement: I've refactored the qwen3_reranker.py example script to encapsulate the LLM model initialization within a dedicated get_model() function. This promotes better organization and reusability of the model setup.
• Standard Entry Point Adoption: The main execution logic of the script has been moved into a main() function, and the script now uses the standard if __name__ == "__main__": main() pattern. This improves the script's adherence to common Python best practices and consistency with other examples.
• Output Formatting: I've added separator lines (---) around the printed score output to enhance readability and make the results clearer when the script is executed.

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[gemini-code-assist]

Code Review

This pull request refactors the examples/offline_inference/qwen3_reranker.py script by introducing get_model() and main() functions. This is a positive change that improves the script's structure, making it cleaner and more aligned with common Python practices.

My review focuses on enhancing these new functions by suggesting the addition of docstrings and type hints. These additions would improve code clarity, maintainability, and consistency, which are valuable for example code. My suggestions refer to Python's PEP 257 (Docstring Conventions) and PEP 484 (Type Hints).

Additionally, the PR description checklist is largely unfilled. It would be beneficial for the author to complete it to provide more context about the purpose, testing, and any related documentation updates for this change.

[github-actions]

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[noooop]

Please wait for #19675

More usage will be added, hoping they can be considered during refactoring.

[dengcao]

You can use Vllm to deploy the Qwen3-Reranker large model.There is already a temporary solution:
ModelsCope：
https://www.modelscope.cn/models/dengcao/Qwen3-Reranker-8B
https://www.modelscope.cn/models/dengcao/Qwen3-Reranker-4B
https://www.modelscope.cn/models/dengcao/Qwen3-Reranker-0.6B

GitHub：
https://github.com/dengcao/Qwen3-Reranker-8B
https://github.com/dengcao/Qwen3-Reranker-4B
https://github.com/dengcao/Qwen3-Reranker-0.6B