GSP1232

Overview

Gemini is a family of generative AI models developed by Google DeepMind that is designed for multimodal use cases. The Gemini API gives you access to the Gemini Pro Vision and Gemini Pro models.

In this lab, you will learn how to use the Vertex AI Gemini API with the Vertex AI SDK for Python to interact with the Gemini Pro (gemini-pro) model and the Gemini Pro Vision (gemini-pro-vision) model.

Vertex AI Gemini API

The Vertex AI Gemini API provides a unified interface for interacting with Gemini models. There are currently two models available in the Gemini API:

1. Gemini Pro model (gemini-pro): Designed to handle natural language tasks, multiturn text and code chat, and code generation.
2. Gemini Pro Vision model (gemini-pro-vision): Supports multimodal prompts. You can include text, images, and video in your prompt requests and get text or code responses.

You can interact with the Gemini API using the following methods:

• Use the Vertex AI Studio for quick testing and command generation
• Use cURL commands
• Use the Vertex AI SDK

This lab focuses on using the Vertex AI SDK for Python to call the Vertex AI Gemini API.

For more information, see the Generative AI on Vertex A documentation.

Objectives

In this lab, you will learn how to:

• Install the Vertex AI SDK for Python
• Using the Vertex AI Gemini API
  • Using a text model (gemini-pro)
    • Reasoning at different levels
    • Reasoning on text
    • Reasoning on numbers
  • Using a multimodal model (gemini-pro-vision)
    • Reasoning on a single image
    • Reasoning on multiple images
    • Reasoning on a video

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 will be made available to you.

This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that 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 or private browser window to run this lab. This prevents any 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: If you already have your own personal Google Cloud account or project, do not use it for this lab to avoid extra charges to your 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 pop-up opens for you to select your payment method. On the left is the Lab Details panel 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 panel.

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 panel.

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 view a menu with a list of Google Cloud products and services, click the Navigation menu at the top-left.

Task 1. Open the notebook in Vertex AI Workbench

1. In the Google Cloud Console, on the Navigation menu, click Vertex AI > Workbench.

2. On the User-Managed Notebooks page, find the generative-ai-jupyterlab notebook and click on the Open JupyterLab button.

The JupyterLab interface opens in a new browser tab.

Task 2. Open the generative-ai folder

1. Navigate to the generative-ai folder on the left hand side of the notebook.

2. Navigate to the gemini/use-cases/education folder.

3. Open the use_cases_for_education.ipynb file.

4. Run through the Getting Started, Import libraries, Define Google Cloud project information, and Define helper functions sections of the notebook.

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

Note: you can skip any notebook cells that are noted Colab only.

In the following sections, you run through the notebook cells to see how to use the Gemini API to build a multimodal RAG system.

Click Check my progress below to check your lab progress.

Install Vertex AI SDK for Python.

Task 3. Use the Gemini Pro model

The Gemini Pro (gemini-pro) model is designed to handle natural language tasks, multiturn text and code chat, and code generation. In this section, you will use the gemini-pro model to reason at different levels, reason on text, and reason on numbers.

Reasoning at different levels

1. In this task, run through the notebook cells to see how to use the gemini-pro model to reason at different levels.

Reasoning on text

1. In this task, run through the notebook cells to see how to use the gemini-pro model to reason on text.

Reasoning on numbers

1. In this task, run through the notebook cells to see how to use the gemini-pro model to reason on numbers.

Click Check my progress below to check your lab progress.

Use the Gemini Pro model to reason at different levels, text and numbers.

Task 4. Use the Gemini Pro Vision model

The Gemini Pro Vision model (gemini-pro-vision) is a multimodal model that supports adding image and video in text or chat prompts for a text response.

Reasoning on a single image

1. In this task, run through the notebook cells to see how to use the gemini-pro-vision model to reason on a single image.

Reasoning on multiple images

1. In this task, run through the notebook cells to see how to use the gemini-pro-vision model to reason on multiple images.

Click Check my progress below to check your lab progress.

Use the Gemini Pro Vision model to reason on single and multiple images.

Reasoning on a video

1. In this task, run through the notebook cells to see how to use the gemini-pro-vision model to reason on a video.

Congratulations!

In this lab, you've how you can use Gemini for education and benefit from text and multimodal models to generate content from text, images, and videos.

Next steps / learn more

• Check out the Generative AI on Vertex AI documentation.
• Learn more about Generative AI on the Google Cloud Tech YouTube channel.
• Google Cloud Generative AI official repo
• Example Gemini notebooks

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Manual Last April 03, 2024

Lab Last Tested April 03, 2024

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