[WIP] Vllm recipes tool improve

[louie-tsai]

Purpose

Add a simple flow to convert a validated vLLM Recipe into deployment-ready config.yml and env.sh.

The recipe remains the baseline. Hardware and workload information are optional and can be used to refine deployment-sensitive runtime settings so users can deploy models with configurations that better match their actual system and workload.

flowchart LR
    R["vLLM Recipe"] --> C["Recipe Converter"]
    H["Hardware Info (optional)"] --> C
    W["Workload Info (optional)"] --> C
    C --> F["config.yml + env.sh"]
    F --> D["vLLM Docker Image"]
    D --> E["OpenAI Endpoint"]

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This helps bridge validated vLLM Recipes to an optimized deployment without requiring users to manually translate and tune recipe parameters.

Test Plan

Verify recipe-only conversion still works.

Verify hardware detection and optional workload inputs refine runtime settings.

Verify config.yml and env.sh are generated correctly.

Verify unsupported runtime-tuning hardware fails clearly.

Test Result

Tested recipe conversion and runtime tuning on Intel Xeon CPU, including hardware detection, workload inputs, and generated vLLM configuration.

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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.

[claude]

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