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Add new genai samples:

  • Compute tokens with text input.
  • Count tokens with text input.
  • Count tokens response usage metadata.
  • Count tokens with video input.

All local tests have passed

@jdomingr jdomingr requested review from a team as code owners December 18, 2025 20:41
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snippet-bot bot commented Dec 18, 2025

Here is the summary of changes.

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@product-auto-label product-auto-label bot added the samples Issues that are directly related to samples. label Dec 18, 2025
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Summary of Changes

Hello @jdomingr, 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 GenAI samples by adding comprehensive examples for token counting functionalities. These new samples cover various scenarios, such as counting tokens from plain text, extracting detailed token information, analyzing usage metadata from content generation, and handling multimodal inputs that combine text and video. This enhancement provides developers with clearer guidance on managing token usage within their GenAI applications.

Highlights

  • New Token Counting Samples (Text): Introduced new samples demonstrating how to count tokens from text input, including computing detailed token information (IDs and actual tokens) and extracting usage metadata from content generation responses.
  • New Token Counting Sample (Video): Added a new sample illustrating how to count tokens when the input includes both text and video content.
  • SDK Version Update: The Google.GenAI package dependency has been updated from version 0.3.0 to 0.9.0.

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Code Review

This pull request introduces four new samples for the GenAI SDK, demonstrating various ways to count tokens for text and video inputs. The new samples are accompanied by corresponding tests. The code is clear and effectively showcases the intended features. I have one suggestion to enhance the robustness of one sample by handling a potential null response from the API, which will also improve consistency with the other added samples.

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