Website search checklist

Set up a Google Cloud project, turn on Vertex AI Agent Builder, and set up access control for your project. You can use an existing Google Cloud project if you already have one.

Actions

1. Review the Before you begin page and confirm that you have completed the steps.

Understand how a website search app (a type of generic search app) behaves and the prerequisites to include websites in a website data store.

Actions

1. Review the information about the relationship between generic apps and data stores in About apps and data stores and what constitutes website data. When advanced website indexing is turned on for a data store, you can use that data store for blended search, where multiple data stores are connected to an app.

2. Prepare your website data according to the requirements in Website data.

Create a data store by providing the website URL patterns to include and the URL patterns to exclude. The data store creation process involves steps to turn on advanced website indexing, which requires domain verification.

Actions

1. Follow the instructions for your data source in Create a data store using website URLs.

   If the data store creation and the domain verification are successful, Vertex AI Agent Builder generates an initial index, which is automatically refreshed on a best-effort basis. This process might take several hours.

Create your website search app and connect it to your new data store.

Actions

1. Create a search app. Ensure to turn on enterprise edition.

Vertex AI Search provides many configuration options. Some options depend on whether you plan to deploy a search widget.

Actions

Depending on your use case and whether you plan to deploy the out-of-the-box search widget or integrate search API calls into your own code, Vertex AI Search provides several options for configuration.

• You can embed a search widget into your website that automatically provides a search bar and expandable search interface. If you plan to deploy the search widget, configure the following:

  • Search widget results. See Configure results for the search widget.

  • Search widget facets (Preview). See Configure facets for the search widget.

  • Autocomplete. See Update autocomplete settings.

  • Search tuning (Preview). See Improve search results with search tuning.

• If you plan to integrate search API calls into your server or application instead of using the widget, you can configure your search settings using the following options:

  • Autocomplete. Depending on your data, set up autocomplete suggestions based on document content, fields, search history, or user events. See Configure autocomplete.

  • Serving controls (Preview with allowlist). Control when search results are boosted, buried, filtered, or redirected, or whether certain queries are synonyms of other queries. See Configure serving controls.

  • Search tuning (Preview). Tune the search model with your own training data. See Improve search results with search tuning.

If you plan to deploy your app by integrating search API calls into your own code, Vertex AI Search provides additional options for configuring how your search results are returned.

Actions

1. Configure your search results with the following options:

   • Filter website search.

   • Boost search results.

   • Order web search results.

   • Get snippets.

You can preview your search results to check if your app configurations are working as expected.

Actions

1. To preview your search results, use the console or the API.

   • Console. Use the Vertex AI Agent Builder console Preview page to preview how search widget configurations affect your results. See the Console instructions in Get search results.

   • API. If you're integrating API calls into your application, you can make curl calls to preview your search configurations. See the REST instructions in Get search results.

Enrich your data store's index by leveraging the structured data that's added to your web pages.

Actions

Addition of structured data to your web pages is an iterative process:

1. Modify the structured data on the web pages. For more information, see Use structured data for advanced website indexing.
2. Update your data store schema with the structured data attributes as necessary.
3. Reconfigure your search results. See Step 6 of this checklist.
4. Preview the search results. See Step 7 of this checklist.
5. Repeat this process as necessary to achieve the required search behaviour before you deploy you search app.

When you're happy with the preview version of your search app, share it with your users by deploying it to your website.

Actions

1. You can deploy your search app in either of the following ways:

   • Embed the search widget into your website. Vertex AI Search provides code that you can copy into your website or web application. This deploys the search widget. You can preview search results in the console. See Add the search widget to a webpage.

   • Integrate search API calls into your server or application. For full control over how your search results are displayed, you can integrate API calls into your server or applications. For more information about making API calls, see Get search results. For client library resources, see Vertex AI Agent Builder client libraries.

You can maintain your app to ensure that latest and necessary data is available in your data store.

Actions

1. Refresh your data.