GSP1291

Overview

Gemini 2.5 Flash is a hybrid reasoning model that explicitly showcases its thoughts. Gemini 2.5 Flash can apply an extended amount of thinking across tasks and use tools to maximize response accuracy.

This lab demonstrates how to use the Gemini 2.5 Flash model to solve complex tasks that require multiple rounds of strategizing and iteratively solving.

Objectives

In this lab, you learn how to use the Gemini API and the Google Gen AI SDK for Python with the Gemini 2.5 Flash model to solve complex tasks. You will:

• Observe multiple tasks of Gemini 2.5 Flash in action, including configuring thinking budgets, starting multi-turn chats, counting tokens, and configuring model parameters.
• Process multimodal (audio, code, documents, images, video) data.
• Understand the thinking mode use cases for Gemini 2.5 Flash.

Gemini

Gemini is a family of powerful generative AI models developed by Google DeepMind, capable of understanding and generating various forms of content, including text, code, images, audio, and video.

Gemini API in Vertex AI

The Gemini API in Vertex AI provides a unified interface for interacting with Gemini models. This allows developers to easily integrate these powerful AI capabilities into their applications. For the most up-to-date details and specific features of the latest versions, please refer to the official Gemini documentation.

Gemini Models

• Gemini Pro: Designed for complex reasoning, including:
  • Analyzing and summarizing large amounts of information.
  • Sophisticated cross-modal reasoning (across text, code, images, etc.).
  • Effective problem-solving with complex codebases.
• Gemini Flash: Optimized for speed and efficiency, offering:
  • Sub-second response times and high throughput.
  • High quality at a lower cost for a wide range of tasks.
  • Enhanced multimodal capabilities, including improved spatial understanding, new output modalities (text, audio, images), and native tool use (Google Search, code execution, and third-party functions).

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.

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.

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.

Task 3. Use the Gemini 2.5 Flash model

The following examples showcase complex tasks that Gemini 2.5 Flash can solve.

Configure thinking budget

In this section, you use Gemini 2.5 Flash to dynamically think for a task or select how many tokens to use for reasoning for certain tasks.

• Run through the Configure thinking budget section of the notebook.

Click Check my progress to verify the objective. Configure thinking budget

Start a multi-turn chat

In this section, you use Gemini 2.5 Flash for freeform multi-turn conversations across multiple turns with back-and-forth interactions.

• Run through the Start a multi-turn chat section of the notebook.

Click Check my progress to verify the objective. Start a multi-turn chat

Send a document from Google Cloud Storage

In this section, you use Gemini 2.5 Flash for reading a specific PDF document hosted on Google Cloud Storage and performing document understanding.

• Run through the Send document from Google Cloud Storage section of the notebook.

Click Check my progress to verify the objective. Send document from Google Cloud Storage

Task 4. Explore Reasoning with Gemini 2.5 Flash

Gemini 2.5 Flash can provide reasoning for answers it supplies to prompts. You will explore examples of this in action in the tasks below.

Code generation

In this section, you will see how the Gemini 2.5 Flash model uses its reasoning capabilities to create a video game, using executable code from a single line prompt.

• Run through the Example 1: Code generation section of the notebook.

Click Check my progress to verify the objective. Example 1 - Code generation

Multimodal reasoning (Geometry)

In this section, you use the Gemini 2.5 Flash model's reasoning capabilities to reason across text and image.

• Run through the Example 2: Multimodal reasoning (Geometry) section of the notebook.

Click Check my progress to verify the objective. Example 2 - Multimodal reasoning (Geometry)

Example 3: Math and problem solving

In this section, you use Gemini 2.5 Flash to see how Gemini solves a brain teaser problem and its reasoning behind each decision it makes.

• Run through the Example 3: Math and problem solving section of the notebook.

Click Check my progress to verify the objective. Example 3 - Math and problem solving

Congratulations!

In this lab, you learned how to use Gemini 2.5 Flash to iteratively solve complex problems.

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 May 1, 2025

Lab Last Tested May 1, 2025

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