Configure field settings

This page shows you how to configure the schema fields to set up an app for structured data, for unstructured data with metadata, or for website data with custom, structured attributes.

Field settings help determine how Vertex AI Search uses fields in its results. You can use the Schematab in the Google Cloud console to configure field settings.

Configuring field settings is available only for apps with data stores containing either structured data or unstructured data with metadata.

Field settings

The following field settings are available for many field types in your search or recommendations data, but not for all data types. A schema contains multiple field settings for individual fields, and the next table contains settings which can be applied to a field within a schema. Using structured data is highly recommended for these field settings:

Setting

Definition

Purpose

Use case example

Indexable

Setting fields to indexable allows for operations like filtering, boosting, and faceting on structured fields within a document.

Fields of type Object can't be set to Indexable .

Marking a field as Indexable allows quicker lookups.

Note that marking a field as Indexable increases the size of the search index and can slow down indexing.

In a hotel data store, you can set a field, such as hotel_chain , as indexable. This lets you apply ranking, filtering, and boosting operations on hotel_chain . For example, you can apply a filter so that the search will turn up only search results containing the filtered hotel chain.

Searchable

Fields that are most likely to be related to searches are designated as Searchable . A field can be searchable without being indexable or retrievable.

Only fields with text values can be marked searchable. Thus, a numeric price field can be indexable (for filtering or faceting) but cannot be searchable as full text.

Setting a field to Searchable improves recall for that field in search queries, allowing users to find content, such as web pages, by querying the text within these fields. Marking a field as searchable allows ranking to be applied. Consequently, marking an excessive number of fields as searchable can negatively affect search precision by oversaturating the ranking algorithm and returning too many results. This could lead to irrelevant search returns.

An internet service provider's support ticket system stores each ticket as a structured document. If these documents contain Searchable text fields, such as issue_description or resolution_notes , a support agent can perform a query related to the content in those fields, such as how to fix slow internet speeds after modem reset. The system would then surface the documents that contain any of those search terms, including modem , internet , speed , in either one or both issue_description or resolution_notes fields.

Dynamic facetable

Provides context-aware filters to better target the user in a search. Setting a field as Dynamic Facetable allows the system to automatically generate interactive filters (facets) based on the unique values present in the field.

Setting a field to

Dynamic
    facetable

enables users to dynamically refine search results by selecting categories or attributes directly derived from your ingested data, without having to manually pre-define every possible filter option. This allows the user to narrow down their search to highly specific web content.

Pages in an internal corporate knowledge base, such as HR policies, are ingested with data like department , document_type , or last_modified_date . If these fields are tagged as dynamic facetable , an employee search for a term like expense reimbursement dynamically generates interactive filters based on the relevant results found. In such case, the web interface could display facets for Department: Finance, Travel, Document Type: Policy, FAQ, or Last Modified Date: This Quarter, Last Year.

Retrievable

When a search query hits matching content, the search engine can pull the values of retrievable fields to display or for use in the application, meaning that information from the original document is displayed as part of the search results. Key fields (unique identifiers for documents) are set up as retrievable.

Retrievable fields provide search context by distinguishing fields whose values can be displayed from those that are only to be used in the search logic but whose raw values are not meant to be shown to the end-user.

For a product search on a merchant site, product_id , name , price , and an image_url are typical fields that you want to set as retrievable. On the other hand, the internal_tracking_code can be indexed and filterable for administrative purposes only, but not retrievable in public search results.

Completable

Allows a field's contents to used for search query suggestions. For more information, see Configure autocomplete .

This setting enables values within that field to be used for providing real-time query suggestions as users type. This feature helps guide your users to relevant content and accelerates the search process. Certain factors such as use of natural language filtering can impact this performance.

If the completable field is set for product_name , brand , and category , when the user types Tech, the autocomplete suggestions can show:

TechCo(from the brand field)
TechCoUltraBook X1 (from the product_name field)
TechnologyGameMaster Pro (another product from the category field)

Filterable

Allows recommendations to use a field to filter recommended results, determining which search results your users see. For information about filtering recommendations, see Filter recommendations .

Setting a field to Filterable helps customize recommendations for users. Note that filtering limits apply.

A filter setting by language and drama could look like: language_code: ANY("en", "fr") OR categories: ANY("drama") .

Differences between commonly used settings

There are key differences between the indexable, searchable, and retrievable field settings. The table summarizes these differences.

Feature	Indexable	Searchable	Retrievable
Primary Role	Makes field content available to search engine	Allows full-text querying against field content	Allows field's value to be returned in search results
Analysis	Content is processed and put into an index.	Typically undergoes extensive lexical analysis.	Value is stored as-is for display.
Can it be...
...Searchable?	Yes (often a prerequisite)	N/A	Not necessarily (can be retrievable without being searchable)
...Retrievable?	Not necessarily	Not necessarily	N/A
...Filterable/Sortable/Facetable?	Yes (generally a prerequisite for these too)	Not directly; these are separate attributes often built on an indexable field.	Not directly; these attributes relate to how the field is indexed and queried, not just displayed.

In practice, many fields that are crucial for user experience (such as titles, descriptions, and identifying information) are often set to be indexable , searchable , and retrievable .

Limitations

Field settings have the following limitations:

You can configure up to 50 fields as indexable, searchable, or dynamic facetable.
You can configure up to 30 fields as retrievable.
To configure a field as dynamic facetable, it must first be configured as indexable.
Changing the indexable setting requires re-indexing the data, which can take hours, especially for large data stores.

If you are configuring fields for a media search app and want detailed information about the fields in the schema, see About media documents and data stores .

Update field settings

To update field settings:

In the Google Cloud console, go to the AI Applicationspage.

AI Applications
Click the name of the app that you want to edit.
Click Data.
Click the Schematab. This tab shows current field settings.
Click Edit.
Select or clear field settings that you need to update. Some field settings are not supported. For example, numerical fields cannot be set to Searchable.
Click Saveto apply your changes.