
Developed two Colab notebooks for the GoogleCloudPlatform-_-generative-ai repository, enabling data scientists and ML engineers to evaluate generative AI agents using the Gen AI Eval SDK. Leveraging Python and cloud computing skills, the work included setting up authentication, SDK installation, and variable initialization to streamline agent evaluation runs. Enhanced documentation by refining notebook guidance, particularly clarifying the expected input format for reasoning engine IDs, which improved onboarding and accuracy for users. Focused on creating a repeatable, user-friendly evaluation workflow, these contributions accelerated adoption of generative AI evaluation tooling and established a foundation for scalable, end-to-end agent assessment processes.
Delivered Gen AI Eval SDK Colab notebooks for evaluating agents and refined notebook guidance for reasoning engine ID input to improve onboarding and accuracy of agent evaluations. These efforts establish a repeatable, user-friendly evaluation workflow for data scientists and ML engineers, accelerating adoption of Gen AI Eval tooling in the Google Cloud Platform generative AI project.
Delivered Gen AI Eval SDK Colab notebooks for evaluating agents and refined notebook guidance for reasoning engine ID input to improve onboarding and accuracy of agent evaluations. These efforts establish a repeatable, user-friendly evaluation workflow for data scientists and ML engineers, accelerating adoption of Gen AI Eval tooling in the Google Cloud Platform generative AI project.

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