[Implict caching] Add entry for implicit caching

[rlazo]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @rlazo, 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 introduces a new mock response file to simulate successful implicit caching behavior within Vertex AI. This addition is crucial for testing and demonstrating how the system handles responses where content is served from a cache, specifically by including relevant token count details for cached content.

Highlights

• Implicit Caching Mock Response: A new mock response file, "mock-responses/vertexai/unary-success-implicit-caching.json", has been introduced. This file provides a simulated Vertex AI response, including "cachedContentTokenCount" and "cacheTokensDetails", to represent a successful implicit caching scenario.

🧠 New Feature in Public Preview: You can now enable Memory to help Gemini Code Assist learn from your team's feedback. This makes future code reviews more consistent and personalized to your project's style. Click here to enable Memory in your admin console.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature	Command	Description
Code Review	/gemini review	Performs a code review for the current pull request in its current state.
Pull Request Summary	/gemini summary	Provides a summary of the current pull request in its current state.
Comment	@gemini-code-assist	Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help	/gemini help	Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[github-actions]

Coverage Diff

Coverage is identical

[gemini-code-assist]

Code Review

This pull request adds a new mock JSON response for a Vertex AI API call that demonstrates implicit caching. The mock data appears largely correct, but I've found an inconsistency in the usageMetadata where the totalTokenCount does not equal the sum of promptTokenCount and candidatesTokenCount. I've provided a suggestion to correct this to ensure the mock data is accurate for any tests that might rely on these values.

[gemini-code-assist]

There's an inconsistency in the token counts in usageMetadata. The totalTokenCount should typically be the sum of promptTokenCount and candidatesTokenCount.

Here, promptTokenCount is 12013 and candidatesTokenCount is 15. Their sum is 12128, but totalTokenCount is set to 12101.

To ensure the mock data is consistent and reliable for testing, please correct this value.

Suggested change

	"totalTokenCount": 12101,
	"totalTokenCount": 12128,

[andrewheard]

LGTM

cc: @paulb777