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@cfloress cfloress commented Sep 5, 2025

Description

Fixes #

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Checklist

  • I have followed Contributing Guidelines from CONTRIBUTING.MD
  • Tests pass: go test -v ./.. (see Testing)
  • Code formatted: gofmt (see Formatting)
  • Vetting pass: go vet (see Formatting)
  • 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 sample adds a new sample directory, and I updated the CODEOWNERS file with the codeowners 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

@cfloress cfloress requested review from a team as code owners September 5, 2025 16:33
@product-auto-label product-auto-label bot added the samples Issues that are directly related to samples. label Sep 5, 2025
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Here is the summary of changes.

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Summary of Changes

Hello @cfloress, 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 Go samples for the Google Cloud Generative AI SDK. It introduces new functionalities across various domains, including batch prediction capabilities with different data sources, advanced image generation techniques, and the ability to generate videos from diverse inputs. Additionally, it provides an example of integrating Vertex AI Search to enhance content generation with external knowledge.

Highlights

  • Batch Prediction Samples: New samples have been added for batch prediction, demonstrating how to use the GenAI SDK with both Google Cloud Storage (GCS) for embeddings and general predictions, as well as BigQuery for input and output.
  • Image Generation Samples: New image generation samples are included, showcasing advanced control types such as style reference, Canny edge detection, and Scribble for more precise image manipulation.
  • Video Generation Samples: Samples for video generation have been added, illustrating how to generate videos from both text prompts and existing images.
  • Vertex AI Search Integration: A new sample demonstrates the integration of Vertex AI Search, allowing the Gemini model to use external data stores for content generation.
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Code Review

This pull request adds a significant number of new GenAI samples for video generation, batch prediction, Vertex AI search, and image generation. The code is generally well-structured for samples. However, I've found several issues in the tests where placeholder URIs for GCS and BigQuery are used, which will cause the system tests to fail. I've also suggested some minor improvements for consistency in error handling in the batch prediction samples. Please review the detailed comments.

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