feat(genai): nano-banana-samples

[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 5 region tags.

• genai/image-generation/imggen-mmflash-edit-img-with-txt-img.js:17, tag googlegenaisdk_imggen_mmflash_edit_img_with_txt_img
• genai/image-generation/imggen-mmflash-locale-aware-with-txt.js:17, tag googlegenaisdk_imggen_mmflash_locale_aware_with_txt
• genai/image-generation/imggen-mmflash-multiple-imgs-with-txt.js:17, tag googlegenaisdk_imggen_mmflash_multiple_imgs_with_txt
• genai/image-generation/imggen-mmflash-txt-and-img-with-txt.js:17, tag googlegenaisdk_imggen_mmflash_txt_and_img_with_txt
• genai/image-generation/imggen_virtual-try-on-with-txt-img.js:17, tag googlegenaisdk_imggen_virtual_try_on_with_txt_img

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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 expands the Node.js samples for the Google GenAI SDK by introducing a suite of new examples focused on advanced image generation and model tuning. The additions demonstrate how to leverage the "gemini-2.5-flash-image-preview" model for tasks like image editing, multi-image generation, and creating rich, illustrated content. Furthermore, a dedicated sample for virtual try-on capabilities and another for initiating and monitoring Gemini model tuning jobs have been added. These updates aim to provide comprehensive and up-to-date demonstrations of the SDK's multimedia and customization features.

Highlights

• New Image Generation Samples: Introduced four new Node.js samples demonstrating various image generation capabilities using the "gemini-2.5-flash-image-preview" model, including editing images with text, locale-aware generation, generating multiple images, and creating illustrated recipes.
• Virtual Try-On Sample: Added a new sample showcasing virtual try-on functionality, allowing users to apply clothing items to a person's image.
• Tuning Job Creation Sample: Included a new sample for creating and monitoring tuning jobs for Gemini models, demonstrating how to fine-tune models with custom datasets.
• SDK Dependency Update: The "@google/genai" SDK dependency has been updated to version "1.20.0", bringing in the latest features and improvements.
• Refactoring of Existing Sample: An existing image generation sample ("imggen-mmflash-with-txt.js") was refactored to align with new conventions, including function renaming and standardized output directory handling.

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[gemini-code-assist]

Code Review

This pull request adds a comprehensive set of new samples for the Google GenAI SDK, focusing on image generation and model tuning capabilities. The changes include new sample files, corresponding tests, and updates to existing code and dependencies. My review focuses on improving code quality by addressing hardcoded values, removing debug logs, fixing typos, and enhancing test coverage and implementation patterns for better maintainability and robustness. There are a few key areas for improvement, including a critical issue with a region tag and a high-severity test regression.

[gericdong]

This model is only available on globe endpoints.