About media documents and data stores

This page provides information about documents and data stores for media. If you're using media recommendations or media search, review the schema requirements for your documents and data stores on this page before uploading your data.

Overview

A document is any item that you upload into a Vertex AI Agent Builder data store. For media, a document typically contains metadata information about media content, such as videos, news articles, music files, or podcasts. The Document object in the API captures this metadata information.

Your data store contains a collection of documents that you have uploaded. When you create a data store, you specify that it will contain media documents. Data stores for media can only be attached to media apps, not to other app types such as generic search and recommendations. Data stores are represented in the API by the DataStore resource.

The quality of the data that you upload has a direct effect on the quality of the results that media apps provide. In general, the more accurate and specific information you can provide, the higher quality your results.

The data that you upload to the data store must be formatted in a specific JSON schema. The data arranged in that schema must be in a BigQuery table, a file or set of files in Cloud Storage, or in a JSON object that can be uploaded directly using the Google Cloud console.

Google predefined schema versus custom schema

You have two options for your media data schema.

  • The Google predefined schema.If you haven't already designed a schema for your media data, the Google predefined schema is a good choice.

  • Your own schema.If you have your data already formatted in a schema, you can use your own schema, with the following requirement.

    You must have fields in your schema that can be mapped to the five key properties for media:

    • title
    • uri
    • category
    • media_available_time
    • media_duration This field is important for media recommendations apps where the business objective is to maximize the conversion rate (CVR) or the watch duration per visitor.

    There are additional key properties that are not required, but for quality results, map as many of these as you can to your schema. These media properties are as follows:

    • description (highly recommended)
    • image
    • image_name
    • image_uri
    • language-code
    • media_aggregated_rating
    • media_aggregated_rating_count
    • media_aggregated_rating_score
    • media_aggregated_rating_source
    • media_content_index
    • media_content_rating
    • media_country_of_origin
    • media_expire_time
    • media_filter_tag
    • media_hash_tag
    • media_in_language
    • media_organization
    • media_organization_custom_role
    • media_organization_name
    • media_organization_rank
    • media_organization_role
    • media_organization_uri
    • media_person
    • media_person_custom_role
    • media_person_name
    • media_person_rank
    • media_person_role
    • media_person_uri
    • media_production_year
    • media_type

    For more information about these properties, see Key properties . The names are similar but some vary slightly. (For example, some names are prefaced with media_ and some are pluralized.)

JSON Schema for Document

When using media, documents can use the Google predefined JSON schema for media.

Documents are uploaded with either a JSON or Struct data representation. Make sure the document JSON or Struct conforms to the following JSON schema. The JSON schema uses JSON Schema 2020-12 for validation. For more about JSON Schema, also see the JSON Schema specification documentation at json-schema.org.

 { 
  
 "$schema" 
 : 
  
 "https://json-schema.org/draft/2020-12/schema" 
 , 
  
 "type" 
 : 
  
 "object" 
 , 
  
 "properties" 
 : 
  
 { 
  
 "title" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "description" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "media_type" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "language_code" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "categories" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 "uri" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "images" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "object" 
 , 
  
 "properties" 
 : 
  
 { 
  
 "uri" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "name" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 } 
  
 }, 
  
 "in_languages" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 "country_of_origin" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "content_index" 
 : 
  
 { 
  
 "type" 
 : 
  
 "integer" 
 , 
  
 }, 
  
 "persons" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "object" 
 , 
  
 "properties" 
 : 
  
 { 
  
 "name" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "role" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "custom_role" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "rank" 
 : 
  
 { 
  
 "type" 
 : 
  
 "integer" 
 , 
  
 }, 
  
 "uri" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 "required" 
 : 
  
 [ 
 "name" 
 , 
  
 "role" 
 ], 
  
 } 
  
 }, 
  
 "organizations" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "object" 
 , 
  
 "properties" 
 : 
  
 { 
  
 "name" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "role" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "custom_role" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "rank" 
 : 
  
 { 
  
 "type" 
 : 
  
 "integer" 
 , 
  
 }, 
  
 "uri" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 "required" 
 : 
  
 [ 
 "name" 
 , 
  
 "role" 
 ], 
  
 } 
  
 }, 
  
 "hash_tags" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 "filter_tags" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 "duration" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "content_rating" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 } 
  
 }, 
  
 "aggregate_ratings" 
 : 
  
 { 
  
 "type" 
 : 
  
 "array" 
 , 
  
 "items" 
 : 
  
 { 
  
 "type" 
 : 
  
 "object" 
 , 
  
 "properties" 
 : 
  
 { 
  
 "rating_source" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "rating_score" 
 : 
  
 { 
  
 "type" 
 : 
  
 "number" 
 , 
  
 }, 
  
 "rating_count" 
 : 
  
 { 
  
 "type" 
 : 
  
 "integer" 
 , 
  
 } 
  
 }, 
  
 "required" 
 : 
  
 [ 
 "rating_source" 
 ], 
  
 } 
  
 }, 
  
 "available_time" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "expire_time" 
 : 
  
 { 
  
 "type" 
 : 
  
 "string" 
 , 
  
 }, 
  
 "production_year" 
 : 
  
 { 
  
 "type" 
 : 
  
 "integer" 
 , 
  
 } 
  
 }, 
  
 "required" 
 : 
  
 [ 
 "title" 
 , 
  
 "categories" 
 , 
  
 "uri" 
 , 
  
 "available_time" 
 ], 
 } 

Sample JSON Document object

The following example shows an example of a JSON Document object.

 { 
  
 "title" 
 : 
  
 "Test document title" 
 , 
  
 "description" 
 : 
  
 "Test document description" 
 , 
  
 "media_type" 
 : 
  
 "sports-game" 
 , 
  
 "in_languages" 
 : 
  
 [ 
  
 "en-US" 
  
 ], 
  
 "language_code" 
 : 
  
 "en-US" 
 , 
  
 "categories" 
 : 
  
 [ 
  
 "sports > clip" 
 , 
  
 "sports > highlight" 
  
 ], 
  
 "uri" 
 : 
  
 "http://www.example.com" 
 , 
  
 "images" 
 : 
  
 [ 
  
 { 
  
 "uri" 
 : 
  
 "http://example.com/img1" 
 , 
  
 "name" 
 : 
  
 "image_1" 
  
 } 
  
 ], 
  
 "country_of_origin" 
 : 
  
 "US" 
 , 
  
 "content_index" 
 : 
  
 0 
 , 
  
 "persons" 
 : 
  
 [ 
  
 { 
  
 "name" 
 : 
  
 "sports person" 
 , 
  
 "role" 
 : 
  
 "player" 
 , 
  
 "rank" 
 : 
  
 0 
 , 
  
 "uri" 
 : 
  
 "http://example.com/person" 
  
 }, 
  
 ], 
  
 "organizations" 
 : 
  
 [ 
  
 { 
  
 "name" 
 : 
  
 "sports team" 
 , 
  
 "role" 
 : 
  
 "team" 
 , 
  
 "rank" 
 : 
  
 0 
 , 
  
 "uri" 
 : 
  
 "http://example.com/team" 
  
 }, 
  
 ], 
  
 "hash_tags" 
 : 
  
 [ 
  
 "tag1" 
  
 ], 
  
 "filter_tags" 
 : 
  
 [ 
  
 "filter_tag" 
  
 ], 
  
 "duration" 
 : 
  
 "100s" 
 , 
  
 "production_year" 
 : 
  
 1900 
 , 
  
 "content_rating" 
 : 
  
 [ 
  
 "PG-13" 
  
 ], 
  
 "aggregate_ratings" 
 : 
  
 [ 
  
 { 
  
 "rating_source" 
 : 
  
 "imdb" 
 , 
  
 "rating_score" 
 : 
  
 4.5 
 , 
  
 "rating_count" 
 : 
  
 1250 
  
 } 
  
 ], 
  
 "available_time" 
 : 
  
 "2022-08-26T23:00:17Z" 
 } 

Document fields

This section lists the field values you provide when you create documents for your data store. The values should correspond to the values used in your internal document database, and should accurately reflect the item represented.

Document object fields

The following fields are top-level fields for the Document object. Also refer to these fields on the Document reference page .

Field Notes
name The full, unique resource name of the document. Required for all Document methods except for create and import . During import, the name is automatically generated and does not need to be manually provided.
id The document ID used by your internal database. The ID field must be unique across your entire data store. The same value is used when you record a user event, and is also returned by the recommend and search methods.
schemaId Required. The identifier of the schema located in the same data store. Should be set as "default_schema", which is automatically created when the default data store is created.
parentDocumentId The ID of the parent document. For top-level (root) documents, parent_document_id can be empty or can point to itself. For child documents, parent_document_id should point to a valid root document.

Key properties

The following properties are defined using the predefined JSON Schema format for media.

For more information about JSON properties, see the Understanding JSON Schema documentation for properties at json-schema.org.

The following table defines flat key properties.

Field name Notes
title

String - required

Document title from your database. A UTF-8 encoded string. Limited to 1000 characters.

categories

String - required

Document categories. This property is repeated for supporting one document belonging to several parallel categories. Use the full category path for higher quality results.

To represent the full path of a category, use the > symbol to separate hierarchies. If > is part of the category name, replace it with another character(s).

For example:

"categories": [ "sports > highlight" ]

A document can contain at most 250 categories. Each category is a UTF-8 encoded string with a length limit of 5000 characters.

uri

String - required

URI of the document. Length limit of 5000 characters.

description

String - highly recommended

Description of the document. Length limit of 5000 characters.

media_type

String - this field is required for movies and shows

Top-level category.

Supported types: movie , show , concert , event , live-event , broadcast , tv-series , episode , video-game , clip , vlog , audio , audio-book , music , album , articles , news , radio , podcast , book , and sports-game .

The values movie and show have special significance. They cause documents to be enriched in a way that improves ranking and helps users making title searches to find alternate content they might be interested in.

language_code

String - optional

Language of the title/description and other string attributes. Use language tags defined by BCP 47 .

For document recommendation, this field is ignored and the text language is detected automatically. The document can include text in different languages, but duplicating documents to provide text in multiple languages can result in degraded performance.

For document search this field is in use. It defaults to "en-US" if unset. For example, "language_code": "en-US" .

duration

String - required for media recommendations apps where the business objective is click-through rate (CVR) or watch duration per session.

Duration of the media content. Duration should be encoded as a string. Encoding should be the same as the google::protobuf::Duration JSON string encoding. For example: "5s", "1m"

available_time

String - required

The time that the content is available to the end-users. This field identifies the freshness of a content for end-users. The timestamp should conform to RFC 3339 standard.

For example:

"2022-08-26T23:00:17Z"

expire_time

String - optional

The time that the content will expire for the end-users. This field identifies the freshness of a content for end-users. The timestamp should conform to RFC 3339 standard.

For example:

"2032-12-31T23:00:17Z"

in_languages

String - optional - repeated

Language of the media contents. Use language tags defined by BCP 47 .

For example: "in_languages": [ "en-US"]

country_of_origin

String - optional

Media document country of origin. Length limit of 128 characters.

For example: "country_of_origin": "US"

content_index

Int - optional

Content index of the media document. Content index field can be used to order the documents relative to others. For example, episode number can be used as the content index.

Content index should be a non-negative integer.

For example: "content_index": 0

filter_tags

String - optional - repeated

Filter tags for the document. At most 250 values are allowed per document with a length limit of 1000 characters. Otherwise, an INVALID_ARGUMENT error is returned.

This tag can be used for filtering recommendation results by passing the tag as part of the RecommendRequest.filter .

For example: "filter_tags": [ "filter_tag"]

hash_tags

String - optional - repeated

Hashtags for the document. At most 100 values are allowed per document, with a length limit of 5000 characters.

For example: "hash_tags": [ "soccer", "world cup"]

content_rating

String - optional - repeated

The content rating, used for content advisory systems and content filtering based on the audience. At most 100 values are allowed per document with a length limit of 128 characters.

This tag can be used for filtering recommendation results by passing the tag as part of the RecommendRequest.filter .

For example: content_rating: ["PG-13"]

The following table defines hierarchical key properties.

Field name Notes
images

Object - optional - repeated

Root key property for encapsulating image-related properties.

images.uri

String - optional

URI of the image. Length limit of 5,000 characters.

images.name

String - optional

Name of the image. Length limit of 128 characters.

persons

Object - optional - repeated

Root key property for encapsulating the person-related properties.

For example: "persons":[{"name":"sports person","role":"player","rank":0,"uri":"http://example.com/person"}]

persons.name

String - required

Name of the person.

persons.role

String - required

The role of the person in the media item.

Supported values: director, actor, player, team, league, editor, author, character, contributor, creator, editor, funder, producer, provider, publisher, sponsor, translator, music-by, channel, custom-role

If none of the supported values are applied to role , set role to custom-role and provide the value in the custom_role field.

persons.custom_role

String - optional

custom_role is set if and only if the role is set to be a custom-role . Must be a UTF-8 encoded string with a length limit of 128 characters. Must match the pattern: [a-zA-Z0-9][a-zA-Z0-9_]* .

persons.rank

Int - optional

Used for role ranking. For example, for first actor, role = "actor", rank = 1

persons.uri

String - optional

URI of the person.

organizations

Object - optional - repeated

Root key property for encapsulating the organization -related properties.

For example: "organizations ":[{"name":"sports team","role":"team","rank":0,"uri":"http://example.com/team"}]

organizations.name

String - required

Name of the organization.

organizations.role

String - required

The role of the organization in the media item.

Supported values: director, actor, player, team, league, editor, author, character, contributor, creator, editor, funder, producer, provider, publisher, sponsor, translator, music-by, channel, custom-role

If none of the supported values are applied to role , set role to custom-role and provide the value in the custom_role field.

organizations.custom_role

String - optional

custom_role is set if and only if the role is set to be a custom-role . Must be a UTF-8 encoded string with a length limit of 128 characters. Must match the pattern: [a-zA-Z0-9][a-zA-Z0-9_]* .

organizations.rank

String - optional

Used for role ranking. For example, for first publisher: role = "publisher", rank = 1 .

organizations.uri

String - optional

URI of the organization.

aggregate_ratings

Object - optional - repeated

Root key property for encapsulating the aggregate_rating related properties.

aggregate_ratings.rating_source

String - required

The source for rating. For example, imdb or rotten_tomatoes . Must be a UTF-8 encoded string with a length limit of 128 characters. Must match the pattern: [a-zA-Z0-9][a-zA-Z0-9_]* .

aggregate_ratings.rating_score

Double - optional

The aggregated rating. The rating should be normalized to the [1, 5] range.

aggregate_ratings.rating_count

Int - optional

The number of individual reviews. Should be a non-negative value.

Document levels

Document levels determine the hierarchy in your data store. Typically, you should have a single-level data store or a two-level data store. Only two layers are supported.

For example, you can have a single-level data store where each document is an individual item. Alternatively, you might choose a two-level data store that contains both groups of items and individual items.

Document level types

There are two document level types:

  • Parent.Parent documents are what Vertex AI Search returns in recommendations and searches. Parents can be individual documents or groups of similar documents. This level type is recommended.

  • Child.Child documents are versions of a group's parent document. Children can only be individual documents. For example, if the parent document is "Example TV Show", children could be "Episode 1" and "Episode 2". This level type can be difficult to configure and maintain, and is not recommended.

About data store hierarchy

When planning your data store hierarchy, decide if your data store should contain only parents or parents and children. The key point to remember is that recommendations and searches only return parent documents.

For example, a parent-only data store might work well for audiobooks, where a recommendations panel returns a selection of individual audiobooks. On the other hand, if you uploaded TV show episodes as parent documents to a parent-only data store, several out-of-order episodes could be recommended in the same panel.

A TV show data store could work with both parents and children, where each parent document represents a TV show with child documents that represent the episodes of that TV show. This two-level data store allows the recommendation panel to show a range of similar TV shows. The end-user can click a particular show to select an episode to watch.

Because parent-child hierarchies can be difficult to configure and maintain, parent-only data stores are recommended.

For example, a TV show data store can work well as a parent-only data store where each parent document represents a TV show that can be recommended, and individual episodes are not included (and therefore not recommended).

If you determine that your data store needs to have both parents and children, that is, groups and singular items, but you only have singular items now, you need to create parents for the groups. The minimum information that you need to provide for a parent is id , title , and categories . For more information, see the section Document fields .

BigQuery schema for media

If you plan to import your documents from BigQuery, use the predefined BigQuery schema to create a BigQuery table with the correct format and load it with your documents data before you import your documents .

 [ 
  
 { 
  
 "name" 
 : 
  
 "id" 
 , 
  
 "mode" 
 : 
  
 "REQUIRED" 
 , 
  
 "type" 
 : 
  
 "STRING" 
 , 
  
 "fields" 
 : 
  
 [] 
  
 }, 
  
 { 
  
 "name" 
 : 
  
 "schemaId" 
 , 
  
 "mode" 
 : 
  
 "REQUIRED" 
 , 
  
 "type" 
 : 
  
 "STRING" 
 , 
  
 "fields" 
 : 
  
 [] 
  
 }, 
  
 { 
  
 "name" 
 : 
  
 "parentDocumentId" 
 , 
  
 "mode" 
 : 
  
 "NULLABLE" 
 , 
  
 "type" 
 : 
  
 "STRING" 
 , 
  
 "fields" 
 : 
  
 [] 
  
 }, 
  
 { 
  
 "name" 
 : 
  
 "jsonData" 
 , 
  
 "mode" 
 : 
  
 "NULLABLE" 
 , 
  
 "type" 
 : 
  
 "STRING" 
 , 
  
 "fields" 
 : 
  
 [] 
  
 } 
 ]