GSP1150

Overview

Gemini 2.5 Pro is Google's strongest model for coding and world knowledge and features a 2M long context window. Gemini 2.5 Pro is available as an experimental model in Vertex AI and is an upgrade path for Gemini 2.5 Pro users who want better quality, or who are particularly invested in long context and code.

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 learn how to use the Gemini API in Vertex AI and the Google Gen AI SDK for Python with the Gemini 2.5 Pro model.

You will complete the following tasks:

• Generate text from text prompts
  • Generate streaming text
  • Start multi-turn chats
  • Use asynchronous methods
• Configure model parameters
• Set system instructions
• Use safety filters
• Use controlled generation
• Count tokens
• Process multimodal (audio, code, documents, images, video) data
• Use automatic and manual function calling
• Code execution

Setup and requirements

Before you click the Start Lab button

Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources are made available to you.

This hands-on lab lets you do the lab activities in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials you use to sign in and access Google Cloud for the duration of the lab.

To complete this lab, you need:

• Access to a standard internet browser (Chrome browser recommended).

Note: Use an Incognito (recommended) or private browser window to run this lab. This prevents conflicts between your personal account and the student account, which may cause extra charges incurred to your personal account.

• Time to complete the lab—remember, once you start, you cannot pause a lab.

Note: Use only the student account for this lab. If you use a different Google Cloud account, you may incur charges to that account.

How to start your lab and sign in to the Google Cloud console

1. Click the Start Lab button. If you need to pay for the lab, a dialog opens for you to select your payment method. On the left is the Lab Details pane with the following:

   • The Open Google Cloud console button
   • Time remaining
   • The temporary credentials that you must use for this lab
   • Other information, if needed, to step through this lab

2. Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).

   The lab spins up resources, and then opens another tab that shows the Sign in page.

   Tip: Arrange the tabs in separate windows, side-by-side.

   Note: If you see the Choose an account dialog, click Use Another Account.

3. If necessary, copy the Username below and paste it into the Sign in dialog.

   {{{user_0.username | "Username"}}}

   You can also find the Username in the Lab Details pane.

4. Click Next.

5. Copy the Password below and paste it into the Welcome dialog.

   {{{user_0.password | "Password"}}}

   You can also find the Password in the Lab Details pane.

6. Click Next.

   Important: You must use the credentials the lab provides you. Do not use your Google Cloud account credentials. Note: Using your own Google Cloud account for this lab may incur extra charges.

7. Click through the subsequent pages:

   • Accept the terms and conditions.
   • Do not add recovery options or two-factor authentication (because this is a temporary account).
   • Do not sign up for free trials.

After a few moments, the Google Cloud console opens in this tab.

Note: To access Google Cloud products and services, click the Navigation menu or type the service or product name in the Search field.

Task 1. Open the notebook in Vertex AI Workbench

1. In the Google Cloud console, on the Navigation menu (), click Vertex AI > Workbench.

2. Find the instance and click on the Open JupyterLab button.

The JupyterLab interface for your Workbench instance opens in a new browser tab.

Note: If you do not see notebooks in JupyterLab, please follow these additional steps to reset the instance:

1. Close the browser tab for JupyterLab, and return to the Workbench home page.

2. Select the checkbox next to the instance name, and click Reset.

3. After the Open JupyterLab button is enabled again, wait one minute, and then click Open JupyterLab.

Task 2. Set up the notebook

1. Open the file.

2. In the Select Kernel dialog, choose Python 3 from the list of available kernels.

3. Run through the Getting Started and the Import libraries sections of the notebook.

   • For Project ID, use , and for Location, use .

Note: You can skip any notebook cells that are noted Colab only. If you experience a 429 response from any of the notebook cell executions, wait 1 minute before running the cell again to proceed.

Click Check my progress to verify the objective. Install packages and import libraries.

Task 3. Use the Gemini 2.5 Pro model

1. Run through the Use the Gemini 2.5 Pro model section of the notebook.

Click Check my progress to verify the objective. Run the Gemini 2.5 Pro model cell in notebook.

Task 4. Configure model parameters

1. Run through the Configure model parameters section of the notebook.

Click Check my progress to verify the objective. Run Configure model parameters cell in notebook.

Task 5. Set system instructions

1. Run through the Set system instructions section of the notebook.

Click Check my progress to verify the objective. Run Set system instructions cell in notebook.

Task 6. Safety filters

1. Run through the Safety filters section of the notebook.

Click Check my progress to verify the objective. Run Safety filters cell in notebook.

Task 7. Send multimodal prompts

1. Run through the Send multimodal prompts section of the notebook.

Click Check my progress to verify the objective. Run Send multimodal prompts cell in notebook.

Task 8. Control generated output

1. Run through the Control generated output section of the notebook.

Click Check my progress to verify the objective. Run Control generated output cell in notebook.

Task 9. Count tokens and compute tokens

1. Run through the Count tokens and compute tokens section of the notebook.

Click Check my progress to verify the objective. Run Count tokens and compute tokens cell in notebook.

Task 10. Search as a tool (Grounding)

1. Run through the Search as a tool (Grounding) section of the notebook.

Click Check my progress to verify the objective. Run Search as a tool (Grounding) cell in notebook.

Task 11. Function calling

1. Run through the Function calling section of the notebook.

Click Check my progress to verify the objective. Run Function calling cell in notebook.

Task 12. Code Execution

1. Run through the Code Execution section of the notebook.

Click Check my progress to verify the objective. Run Code Execution cell in notebook.

Congratulations!

You have now completed the lab! In this lab, you worked with the Gemini 2.5 Pro model in a Jupyter notebook using the Gemini API and Gen AI SDK for Generative AI.

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.

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Manual Last Updated June 25, 2025

Lab Last Tested June 25, 2025

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