GSP1152

Overview

Enterprise Search on Vertex AI Agent Builder (Agent Builder) brings together the power of deep information retrieval, state-of-the-art natural language processing, and the latest in large language processing to understand user intent and return the most relevant results for the user.

In this lab you will learn how to create a search application based on:

• websites
• structured data
• unstructured data

then configure, visualize, and analyze the search results that are returned from the search app.

Objectives

In this lab, you will learn how to perform the following tasks:

• Index public website data, structured and unstructured data.
• Perform search on your indexed data.
• Configure the display of your search results.
• View analytics on your search.
• Integrate Enterprise Search with your web application.

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. Enable APIs for Vertex AI API

1. In Cloud console, from the Navigation menu go to APIs & Services > Enabled APIs & services.

2. Click on the +Enable APIs and services button at the top fo the screen.

3. Search for Discovery Engine API, then choose the first entry and click on Enable.

Click Check my progress to verify the objective. Enable required API

Task 2. Create and Preview a website search app

A website search app makes it easier for users to find the information they are looking for on your website.

Create a search engine and data store

1. Navigate to Artificial Intelligence and click on Agent Builder in the left menu of Cloud console. If asked to activate APIs on the resulting page click the button to do so.

2. On the welcome page, click Continue and Activate the API.

3. On the Create App page, make sure Search is selected, leave all settings as is and enter the following for the Your app name and Company Name fields:

Google Cloud docs

Click Continue.

4. On the Create a data store for your app page, click +CREATE DATA STORE then select Website Content as data source.

5. On the Specify the websites for your data store page, in the Sites to include field, enter:

cloud.google.com/*

Click Continue.

6. On the Configure your data store page, in the Data store name field, enter:

Website

Click CREATE.

7. On the data page, make sure Website is selected, and then click Create.

Click Check my progress to verify the objective. Create a website search app

Preview the website search app

8. In the side panel, go to Preview, type Document AI and press Enter.

9. Click the view icons to switch between mobile view and desktop view.

You created a search engine and a data store where you indexed a website and then performed a search across that website.

Task 3. Create and Preview a structured data search app

Structured data can be used to make website content more visible to search engines. A structured data search app improves the discoverablity of website content and provides users with a more relavant seach experience.

1. Click the Agent Builder logo to navigate back to the Apps page.

2. Click +CREATE APP.

3. On the Create App page, make sure Search is selected, for Your app name and Company Name fields enter:

Movies

Click Continue.

4. On the Select a data store for your app page, click +CREATE DATA STORE then select Cloud Storage as data source.

5. In the Import data from Cloud Storage pane, enter the following value, make sure to select FILE as the import type:

cloud-samples-data/gen-app-builder/search/kaggle_movies/movie_metadata.ndjson

This Cloud Storage bucket contains an NDJSON-formatted dataset of movies made available by Kaggle.

6. Select the Structured data (JSONL) radio option and then click CONTINUE.

7. On Review schema and assign key properties page, click CONTINUE.

8. On the Configure your data store page, in the Data store name field, enter:

Structured data

Then click CREATE.

9. On the data page for your app, click Structured data , and then click CREATE.

10. Click ACTIVITY.

Note: Please wait until the documents import before proceeding. This process may take several minutes to complete.

Upon success you will see the Status column change to Succeeded as shown in the image below:

11. Click the DOCUMENTS tab to see the number of documents imported.

12. Click the Schema tab to see the auto-generated schema for your dataset. Notice that for auto-genared schemas all fields are retrievable, indexable, facetable and searchable.

Note: Click on the image to zoom further.

Preview the Movies search app and Configure the search results display

13. In the navigation menu, click Preview to test the search app.

14. In the search bar, enter:

Google

Then press Enter to view the results.

Notice that the full schema is returned. Often times you will not need to display all of the items returned by the full schema. To customize the values to display, Vertex AI Agent Builder allows you to configure only the values you want to display. You will see how this is achieved in the next steps.

15. In the side panel, click Configurations.

16. Open the Configure fields in results drop down and map fields in your data store to the attributes to be displayed in search results:

Key	Value
Title	title
Thumbnail	poster_path
URL	homepage
Tex 1	tagline
Tex 2	release_date

17. Click SAVE AND PUBLISH.

Click Check my progress to verify the objective. Create a structured data search app

18. In the search bar under Preview write:

Harry Potter

And press Enter.

The output results have been formatted according to the fields you configured and should look similar to the results pictured below.

Integration

In this section you will review available methods of integrating configured search capabilities into your web or server based applications.

Web

19. In the side panel, click Integration. The resulting landing page is for Web based integrations.

You will notice that you can copy and paste the provided HTML code snippet into a webpage to consume the search capability confgured in the previous sections.

You can also select the Authentication mechanism used to allow users to interact with the search widget. Select JWT or OAuth Based or Public Access depending on your needs. If using JWT or OAuth Based you will need to configure your application to provide a JSON Web Token or an OAuth token provided by your backend. See Add a widget with an authorization token for more details.

You can also restrict the widget's usage to specific domains specified in the Add allowed domains for the widget list.

20. Next, click on the API tab.

Task 4. Create and Preview an unstructured data search app

Unstructured data is data that does not have a predefined format. This type of data can be difficult to search for using traditional search engines. An unstructured data search app can be used to make this data more accessible to use and gain insights that can be used to improve business operations.

1. From the Navigation Menu go to Agent Builder.

2. Click +CREATE APP.

3. On the Create App page, make sure Search is selected, for Your app name and Company Name fields enter:

Alphabet Investor PDFs

Then click Continue.

4. On the Select a data store for your app page, click +CREATE DATA STORE then select Cloud Storage as data source.

5. In the Import data from Cloud Storage pane, enter the following value:

cloud-samples-data/gen-app-builder/search/alphabet-investor-pdfs

This Cloud Storage bucket contains earnings report PDFs from the Alphabet investor site.

6. Make sure to select Unstructured documents and then click CONTINUE.

7. On the Configure your data store page, in the Data store name field, enter:

Unstructured data

Then, click CREATE.

8. On the Data page for your app, select Unstructured data then click CREATE.

9. Click ACTIVITY.

Import completed displays in the Status column when the import process is finished. You might need to click Refresh to see Import completed.

Note: It may take a few minutes to index all of the unstructured data found in the PDF documents before completing the section below. You may choose to run the Activity Tracking step below or end the lab if desired.

10. Click the DOCUMENTS tab to see the number of documents imported.

Preview the Alphabet Investor PDFs search app

11. In the navigation menu, click Preview to test the search app.

12. In the search bar, enter Google revenue in 2008, and then press Enter to view your results. Notice the summary as well as the results.

Below is an example of search results for the query provided.

Click Check my progress to verify the objective. Create an unstructured data search app

Congratulations!

You learned how to create different type of data stores in Enterprise Search for Vertex AI Agent Builder. You also configured how the search outputs look like. Finally, you saw how to create integrations with your web applications and saw the performance and usage of the search engine via Analytics.

Next steps

• Learn more about Vertex AI on the Google Cloud Tech YouTube channel.

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Manual Last Updated September 06, 2024

Lab Last Tested September 06, 2024

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