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Before you begin
- Labs create a Google Cloud project and resources for a fixed time
- Labs have a time limit and no pause feature. If you end the lab, you'll have to restart from the beginning.
- On the top left of your screen, click Start lab to begin
Image understanding across multiple images
/ 10
Understanding Screens and Interfaces
/ 10
Understanding entity relationships in technical diagrams
/ 10
Recommendations based on multiple images
/ 10
Similarity/Differences
/ 10
Generating a video description
/ 10
Extracting tags of objects throughout the video
/ 10
Asking more questions about a video
/ 10
Retrieving extra information beyond the video
/ 20
This lab introduces you to Gemini, a family of multimodal generative AI models developed by Google. You'll use the Gemini API to explore how Gemini Flash can understand and generate responses based on text, images, and video.
Gemini's multimodal capabilities enable it to:
You'll experiment with these features through hands-on tasks using the Gemini API in Vertex AI.
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.
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.
Before starting this lab, you should be familiar with:
In this lab, you will:
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:
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:
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.
If necessary, copy the Username below and paste it into the Sign in dialog.
You can also find the Username in the Lab Details pane.
Click Next.
Copy the Password below and paste it into the Welcome dialog.
You can also find the Password in the Lab Details pane.
Click Next.
Click through the subsequent pages:
After a few moments, the Google Cloud console opens in this tab.
In the Google Cloud console, on the Navigation menu (), click Vertex AI > Workbench.
Find the
The JupyterLab interface for your Workbench instance opens in a new browser tab.
Open the
In the Select Kernel dialog, choose Python 3 from the list of available kernels.
Run through the Getting Started and the Import libraries sections of the notebook.
Gemini Flash (gemini-1.5-flash
) is a multimodal model that supports multimodal prompts. You can include text, image(s), and video in your prompt requests and get text or code responses.
In this task, run through the notebook cells to see how to use the Gemini Flash model. Return here to check your progress as you complete the objectives.
One of the capabilities of Gemini is being able to reason across multiple images. In this example, you will use Gemini to calculate the total cost of groceries using an image of fruits and a price list.
Run through the Image understanding across multiple images section of the notebook.
Click Check my progress to verify the objective.
Gemini can also extract information from appliance screens, UIs, screenshots, icons, and layouts. In this example, you will use Gemini to extract information from a stove to help a user navigate the UI and respond in different languages:
Run through the Understanding Screens and Interfaces section of the notebook.
Click Check my progress to verify the objective.
Gemini has multimodal capabilities that enable it to understand diagrams and take actionable steps, such as optimization or code generation. In this example, you will see how Gemini can decipher an entity relationship (ER) diagram, understand the relationships between tables, identify requirements for optimization in a specific environment like BigQuery, and even generate corresponding code.
Run through the Understanding entity relationships in technical diagrams section of the notebook.
Click Check my progress to verify the objective.
Gemini is capable of image comparison and providing recommendations. This may be useful in industries like e-commerce and retail. In this example, you will use Gemini to recommend which pair of glasses would be better suited to an oval-shaped face.
Run through the Recommendations based on multiple images section of the notebook.
Click Check my progress to verify the objective.
Gemini can compare images and identify similarities or differences between objects. In this example, you will use Gemini to compare two images of the same location and identify the differences between them.
Run through the Similarity/Differences section of the notebook.
Click Check my progress to verify the objective.
Gemini can generate a description of a video. In this example, you will use Gemini to generate a description of a video of a video of a Mediterranean sea coast.
Run through the Generating a video description section of the notebook.
Click Check my progress to verify the objective.
Gemini can also extract tags throughout a video. In this example, you will use Gemini to extract tags of objects throughout a video of a photo shoot and generate hashtags.
Run through the Extracting tags of objects throughout the video section of the notebook.
Click Check my progress to verify the objective.
Gemini can answer questions about a video. In this example, you will use Gemini to answer questions about the video and return a JSON response.
Run through the Asking more questions about a video section of the notebook.
Click Check my progress to verify the objective.
Gemini can also retrieve extra information beyond the video. In this example, you will use Gemini to retrieve extra information about the video, such as asking specific questions about a train route.
Run through the Retrieving extra information beyond the video section of the notebook.
Click Check my progress to verify the objective.
You have now completed the lab! In this lab, you learned how to use the Gemini API in Vertex AI to generate text from text and image(s) prompts.
Check out the following resources to learn more about Gemini:
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Manual Last Updated December 13, 2024
Lab Last Tested December 13, 2024
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