GSP1308

Overview

The Gemini API empowers developers and creators across various fields by providing advanced natural language processing and code generation capabilities. It enables the creation of intelligent chatbots, automated content generation tools, insightful data analysis platforms, and personalized learning experiences. Its versatility stems from its ability to understand context, generate creative text, analyze complex data, and adapt to diverse applications.

There are two Gemini models, Gemini Pro and Gemini Flash. In this lab, you will use the model.

Prerequisites

Before starting this lab, you should be familiar with:

• Basic Python programming.
• General API concepts.
• Running Python code in a Jupyter notebook on Vertex AI Workbench.

Objectives

In this lab, you will learn how to:

• Set up and authenticate the Gemini API.
• Make basic API calls to interact with Gemini models.

Task 1. Set your API Key

1. In the Jupyter Notebook, copy the below API key into API_KEY variable.

Task 2. Run through the notebook cells

1. Once you have set your API_KEY variable, please replace the __GEMINI_FLASH_MODEL_ID__ placeholder in the notebook with and follow instructions directly in the Jupyter Notebook.

Click Check my progress to verify the objective. Generate Text from the Gemini API.

Click Check my progress to verify the objective. Multi-Turn Conversations.

Congratulations!

Congratulations! In this lab, you learned how to use the Gemini API and make basic API calls to interact with Gemini models.

Next steps / learn more

Check out the following resources to learn more about Gemini:

• Gemini Overview
• Generative AI on Vertex AI Documentation
• Generative AI on YouTube
• Explore the Vertex AI Cookbook for a curated, searchable gallery of notebooks for Generative AI.
• Explore other notebooks and samples in the Google Cloud Generative AI repository.

Google Cloud training and certification

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Manual Last Updated October 07, 2025

Lab Last Tested October 07, 2025

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