feat(genai): Sample/tuning

[Guiners]

Description

Fixes #

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Checklist

• I have followed guidelines from CONTRIBUTING.MD and Samples Style Guide
• Tests pass: npm test (see Testing)
• Lint pass: npm run lint (see Style)
• Required CI tests pass (see CI testing)
• These samples need a new API enabled in testing projects to pass (let us know which ones)
• These samples need a new/updated env vars in testing projects set to pass (let us know which ones)
• This pull request is from a branch created directly off of GoogleCloudPlatform/nodejs-docs-samples. Not a fork.
• This sample adds a new sample directory, and I updated the CODEOWNERS file with the codeowners for this sample
• This sample adds a new sample directory, and I created GitHub Actions workflow for this sample
• This sample adds a new Product API, and I updated the Blunderbuss issue/PR auto-assigner with the codeowners for this sample
• Please merge this PR for me once it is approved

Note: Any check with (dev), (experimental), or (legacy) can be ignored and should not block your PR from merging (see CI testing).

[snippet-bot]

Here is the summary of changes.

You are about to add 4 region tags.

• genai/tuning/tuning-job-create.js:17, tag googlegenaisdk_tuning_job_create
• genai/tuning/tuning-job-get.js:17, tag googlegenaisdk_tuning_job_get
• genai/tuning/tuning-job-list.js:17, tag googlegenaisdk_tuning_job_list
• genai/tuning/tuning-textgen-with-txt.js:17, tag googlegenaisdk_tuning_textgen_with_txt

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[gemini-code-assist]

Summary of Changes

Hello @Guiners, 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 significantly enhances the Generative AI (GenAI) samples by adding a suite of examples focused on model tuning. It provides practical demonstrations for creating, managing, and utilizing tuned models, enabling developers to better understand and implement custom model fine-tuning workflows within their applications.

Highlights

• New GenAI Tuning Samples: Introduces four new sample files demonstrating how to interact with Generative AI tuning jobs, including creation, retrieval, listing, and using a tuned model for text generation.
• Comprehensive Testing: Adds corresponding test files for each new tuning sample, ensuring functionality and providing examples of how to test these features.
• Dependency Update: Incorporates 'proxyquire' as a new development dependency to facilitate mocking in the newly added test suites.

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[gemini-code-assist]

Code Review

This pull request introduces new samples and tests for GenAI tuning jobs, covering creation, retrieval, listing, and usage. While the new samples are a good addition, the accompanying tests have several significant issues, including flawed mocks, incorrect assertions, and excessively long timeouts, which compromise their reliability and effectiveness. Furthermore, the sample files themselves are not directly runnable from the command line, limiting their practical use. I have provided detailed feedback and specific code suggestions to address these points and improve the overall quality of the code.