Reference documentation and code samples for the Google Cloud Recommendation Engine V1beta1 Client class PredictRequest.
Request message for Predict method.
Generated from protobuf message google.cloud.recommendationengine.v1beta1.PredictRequest
Namespace
Google \ Cloud \ RecommendationEngine \ V1beta1
Methods
__construct
Constructor.
Parameters
Name
Description
data
array
Optional. Data for populating the Message object.
↳ name
string
Required. Full resource name of the format: {name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*} The id of the recommendation engine placement. This id is used to identify the set of models that will be used to make the prediction. We currently support three placements with the following IDs by default: * * shopping_cart: Predicts items frequently bought together with one or more catalog items in the same shopping session. Commonly displayed after add-to-cart events, on product detail pages, or on the shopping cart page. * * home_page: Predicts the next product that a user will most likely engage with or purchase based on the shopping or viewing history of the specified userId or visitorId. For example - Recommendations for you. * * product_detail: Predicts the next product that a user will most likely engage with or purchase. The prediction is based on the shopping or viewing history of the specified userId or visitorId and its relevance to a specified CatalogItem. Typically used on product detail pages. For example - More items like this. * * recently_viewed_default: Returns up to 75 items recently viewed by the specified userId or visitorId, most recent ones first. Returns nothing if neither of them has viewed any items yet. For example - Recently viewed. The full list of available placements can be seen at https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
Required. Context about the user, what they are looking at and what action they took to trigger the predict request. Note that this user event detail won't be ingested to userEvent logs. Thus, a separate userEvent write request is required for event logging.
↳ page_size
int
Optional. Maximum number of results to return per page. Set this property to the number of prediction results required. If zero, the service will choose a reasonable default.
↳ page_token
string
Optional. The previous PredictResponse.next_page_token.
↳ filter
string
Optional. Filter for restricting prediction results. Accepts values for tags and the filterOutOfStockItems flag. * * Tag expressions. Restricts predictions to items that match all of the specified tags. Boolean operators OR and NOT are supported if the expression is enclosed in parentheses, and must be separated from the tag values by a space. -"tagA" is also supported and is equivalent to NOT "tagA". Tag values must be double quoted UTF-8 encoded strings with a size limit of 1 KiB. * * filterOutOfStockItems. Restricts predictions to items that do not have a stockState value of OUT_OF_STOCK. Examples: * * tag=("Red" OR "Blue") tag="New-Arrival" tag=(NOT "promotional") * * filterOutOfStockItems tag=(-"promotional") * * filterOutOfStockItems
↳ dry_run
bool
Optional. Use dryRun mode for this prediction query. If set to true, a dummy model will be used that returns arbitrary catalog items. Note that the dryRun mode should only be used for testing the API, or if the model is not ready.
Optional. Additional domain specific parameters for the predictions. Allowed values: * * returnCatalogItem: Boolean. If set to true, the associated catalogItem object will be returned in the PredictResponse.PredictionResult.itemMetadata object in the method response. * * returnItemScore: Boolean. If set to true, the prediction 'score' corresponding to each returned item will be set in the metadata field in the prediction response. The given 'score' indicates the probability of an item being clicked/purchased given the user's context and history.
Optional. The labels for the predict request. * * Label keys can contain lowercase letters, digits and hyphens, must start with a letter, and must end with a letter or digit. * * Non-zero label values can contain lowercase letters, digits and hyphens, must start with a letter, and must end with a letter or digit. * * No more than 64 labels can be associated with a given request. See https://goo.gl/xmQnxf for more information on and examples of labels.
getName
Required. Full resource name of the format:
{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}
The id of the recommendation engine placement. This id is used to identify
the set of models that will be used to make the prediction.
We currently support three placements with the following IDs by default:
shopping_cart: Predicts items frequently bought together with one or
more catalog items in the same shopping session. Commonly displayed after
add-to-cart events, on product detail pages, or on the shopping cart
page.
home_page: Predicts the next product that a user will most likely
engage with or purchase based on the shopping or viewing history of the
specified userId or visitorId. For example - Recommendations for you.
product_detail: Predicts the next product that a user will most likely
engage with or purchase. The prediction is based on the shopping or
viewing history of the specified userId or visitorId and its
relevance to a specified CatalogItem. Typically used on product detail
pages. For example - More items like this.
recently_viewed_default: Returns up to 75 items recently viewed by the
specified userId or visitorId, most recent ones first. Returns
nothing if neither of them has viewed any items yet. For example -
Recently viewed.
The full list of available placements can be seen at
https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
Returns
Type
Description
string
setName
Required. Full resource name of the format:
{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}
The id of the recommendation engine placement. This id is used to identify
the set of models that will be used to make the prediction.
We currently support three placements with the following IDs by default:
shopping_cart: Predicts items frequently bought together with one or
more catalog items in the same shopping session. Commonly displayed after
add-to-cart events, on product detail pages, or on the shopping cart
page.
home_page: Predicts the next product that a user will most likely
engage with or purchase based on the shopping or viewing history of the
specified userId or visitorId. For example - Recommendations for you.
product_detail: Predicts the next product that a user will most likely
engage with or purchase. The prediction is based on the shopping or
viewing history of the specified userId or visitorId and its
relevance to a specified CatalogItem. Typically used on product detail
pages. For example - More items like this.
recently_viewed_default: Returns up to 75 items recently viewed by the
specified userId or visitorId, most recent ones first. Returns
nothing if neither of them has viewed any items yet. For example -
Recently viewed.
The full list of available placements can be seen at
https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
Parameter
Name
Description
var
string
Returns
Type
Description
$this
getUserEvent
Required. Context about the user, what they are looking at and what action
they took to trigger the predict request. Note that this user event detail
won't be ingested to userEvent logs. Thus, a separate userEvent write
request is required for event logging.
Required. Context about the user, what they are looking at and what action
they took to trigger the predict request. Note that this user event detail
won't be ingested to userEvent logs. Thus, a separate userEvent write
request is required for event logging.
Optional. Maximum number of results to return per page. Set this property
to the number of prediction results required. If zero, the service will
choose a reasonable default.
Returns
Type
Description
int
setPageSize
Optional. Maximum number of results to return per page. Set this property
to the number of prediction results required. If zero, the service will
choose a reasonable default.
Parameter
Name
Description
var
int
Returns
Type
Description
$this
getPageToken
Optional. The previous PredictResponse.next_page_token.
Returns
Type
Description
string
setPageToken
Optional. The previous PredictResponse.next_page_token.
Parameter
Name
Description
var
string
Returns
Type
Description
$this
getFilter
Optional. Filter for restricting prediction results. Accepts values for
tags and the filterOutOfStockItems flag.
Tag expressions. Restricts predictions to items that match all of the
specified tags. Boolean operators OR and NOT are supported if the
expression is enclosed in parentheses, and must be separated from the
tag values by a space. -"tagA" is also supported and is equivalent to
NOT "tagA". Tag values must be double quoted UTF-8 encoded strings
with a size limit of 1 KiB.
filterOutOfStockItems. Restricts predictions to items that do not have a
stockState value of OUT_OF_STOCK.
Examples:
tag=("Red" OR "Blue") tag="New-Arrival" tag=(NOT "promotional")
filterOutOfStockItems tag=(-"promotional")
filterOutOfStockItems
Returns
Type
Description
string
setFilter
Optional. Filter for restricting prediction results. Accepts values for
tags and the filterOutOfStockItems flag.
Tag expressions. Restricts predictions to items that match all of the
specified tags. Boolean operators OR and NOT are supported if the
expression is enclosed in parentheses, and must be separated from the
tag values by a space. -"tagA" is also supported and is equivalent to
NOT "tagA". Tag values must be double quoted UTF-8 encoded strings
with a size limit of 1 KiB.
filterOutOfStockItems. Restricts predictions to items that do not have a
stockState value of OUT_OF_STOCK.
Examples:
tag=("Red" OR "Blue") tag="New-Arrival" tag=(NOT "promotional")
filterOutOfStockItems tag=(-"promotional")
filterOutOfStockItems
Parameter
Name
Description
var
string
Returns
Type
Description
$this
getDryRun
Optional. Use dryRun mode for this prediction query. If set to true, a
dummy model will be used that returns arbitrary catalog items.
Note that the dryRun mode should only be used for testing the API, or if
the model is not ready.
Returns
Type
Description
bool
setDryRun
Optional. Use dryRun mode for this prediction query. If set to true, a
dummy model will be used that returns arbitrary catalog items.
Note that the dryRun mode should only be used for testing the API, or if
the model is not ready.
Parameter
Name
Description
var
bool
Returns
Type
Description
$this
getParams
Optional. Additional domain specific parameters for the predictions.
Allowed values:
returnCatalogItem: Boolean. If set to true, the associated catalogItem
object will be returned in the
PredictResponse.PredictionResult.itemMetadata object in the method
response.
returnItemScore: Boolean. If set to true, the prediction 'score'
corresponding to each returned item will be set in the metadata
field in the prediction response. The given 'score' indicates the
probability of an item being clicked/purchased given the user's context
and history.
Optional. Additional domain specific parameters for the predictions.
Allowed values:
returnCatalogItem: Boolean. If set to true, the associated catalogItem
object will be returned in the
PredictResponse.PredictionResult.itemMetadata object in the method
response.
returnItemScore: Boolean. If set to true, the prediction 'score'
corresponding to each returned item will be set in the metadata
field in the prediction response. The given 'score' indicates the
probability of an item being clicked/purchased given the user's context
and history.
Required. Full resource name of the format:
{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}
The id of the recommendation engine placement. This id is used to identify
the set of models that will be used to make the prediction.
We currently support three placements with the following IDs by default:
shopping_cart: Predicts items frequently bought together with one or
more catalog items in the same shopping session. Commonly displayed after
add-to-cart events, on product detail pages, or on the shopping cart
page.
home_page: Predicts the next product that a user will most likely
engage with or purchase based on the shopping or viewing history of the
specified userId or visitorId. For example - Recommendations for you.
product_detail: Predicts the next product that a user will most likely
engage with or purchase. The prediction is based on the shopping or
viewing history of the specified userId or visitorId and its
relevance to a specified CatalogItem. Typically used on product detail
pages. For example - More items like this.
recently_viewed_default: Returns up to 75 items recently viewed by the
specified userId or visitorId, most recent ones first. Returns
nothing if neither of them has viewed any items yet. For example -
Recently viewed.
Required. Context about the user, what they are looking at and what action
they took to trigger the predict request. Note that this user event detail
won't be ingested to userEvent logs. Thus, a separate userEvent write
request is required for event logging.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-07 UTC."],[],[],null,["# Google Cloud Recommendation Engine V1beta1 Client - Class PredictRequest (0.8.2)\n\nVersion latestkeyboard_arrow_down\n\n- [0.8.2 (latest)](/php/docs/reference/cloud-recommendations-ai/latest/V1beta1.PredictRequest)\n- [0.8.1](/php/docs/reference/cloud-recommendations-ai/0.8.1/V1beta1.PredictRequest)\n- [0.7.7](/php/docs/reference/cloud-recommendations-ai/0.7.7/V1beta1.PredictRequest)\n- [0.6.4](/php/docs/reference/cloud-recommendations-ai/0.6.4/V1beta1.PredictRequest)\n- [0.5.0](/php/docs/reference/cloud-recommendations-ai/0.5.0/V1beta1.PredictRequest)\n- [0.4.12](/php/docs/reference/cloud-recommendations-ai/0.4.12/V1beta1.PredictRequest) \n| **Beta**\n|\n|\n| This library is covered by the [Pre-GA Offerings Terms](/terms/service-terms#1)\n| of the Terms of Service. Pre-GA libraries might have limited support,\n| and changes to pre-GA libraries might not be compatible with other pre-GA versions.\n| For more information, see the\n[launch stage descriptions](/products#product-launch-stages). \nReference documentation and code samples for the Google Cloud Recommendation Engine V1beta1 Client class PredictRequest.\n\nRequest message for Predict method.\n\nGenerated from protobuf message `google.cloud.recommendationengine.v1beta1.PredictRequest`\n\nNamespace\n---------\n\nGoogle \\\\ Cloud \\\\ RecommendationEngine \\\\ V1beta1\n\nMethods\n-------\n\n### __construct\n\nConstructor.\n\n### getName\n\nRequired. Full resource name of the format:\n`{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}`\nThe id of the recommendation engine placement. This id is used to identify\nthe set of models that will be used to make the prediction.\n\nWe currently support three placements with the following IDs by default:\n\n- `shopping_cart`: Predicts items frequently bought together with one or more catalog items in the same shopping session. Commonly displayed after `add-to-cart` events, on product detail pages, or on the shopping cart page.\n- `home_page`: Predicts the next product that a user will most likely engage with or purchase based on the shopping or viewing history of the specified `userId` or `visitorId`. For example - Recommendations for you.\n- `product_detail`: Predicts the next product that a user will most likely engage with or purchase. The prediction is based on the shopping or viewing history of the specified `userId` or `visitorId` and its relevance to a specified `CatalogItem`. Typically used on product detail pages. For example - More items like this.\n- `recently_viewed_default`: Returns up to 75 items recently viewed by the specified `userId` or `visitorId`, most recent ones first. Returns nothing if neither of them has viewed any items yet. For example - Recently viewed. The full list of available placements can be seen at \u003chttps://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard\u003e\n\n### setName\n\nRequired. Full resource name of the format:\n`{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}`\nThe id of the recommendation engine placement. This id is used to identify\nthe set of models that will be used to make the prediction.\n\nWe currently support three placements with the following IDs by default:\n\n- `shopping_cart`: Predicts items frequently bought together with one or more catalog items in the same shopping session. Commonly displayed after `add-to-cart` events, on product detail pages, or on the shopping cart page.\n- `home_page`: Predicts the next product that a user will most likely engage with or purchase based on the shopping or viewing history of the specified `userId` or `visitorId`. For example - Recommendations for you.\n- `product_detail`: Predicts the next product that a user will most likely engage with or purchase. The prediction is based on the shopping or viewing history of the specified `userId` or `visitorId` and its relevance to a specified `CatalogItem`. Typically used on product detail pages. For example - More items like this.\n- `recently_viewed_default`: Returns up to 75 items recently viewed by the specified `userId` or `visitorId`, most recent ones first. Returns nothing if neither of them has viewed any items yet. For example - Recently viewed. The full list of available placements can be seen at \u003chttps://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard\u003e\n\n### getUserEvent\n\nRequired. Context about the user, what they are looking at and what action\nthey took to trigger the predict request. Note that this user event detail\nwon't be ingested to userEvent logs. Thus, a separate userEvent write\nrequest is required for event logging.\n\n### hasUserEvent\n\n### clearUserEvent\n\n### setUserEvent\n\nRequired. Context about the user, what they are looking at and what action\nthey took to trigger the predict request. Note that this user event detail\nwon't be ingested to userEvent logs. Thus, a separate userEvent write\nrequest is required for event logging.\n\n### getPageSize\n\nOptional. Maximum number of results to return per page. Set this property\nto the number of prediction results required. If zero, the service will\nchoose a reasonable default.\n\n### setPageSize\n\nOptional. Maximum number of results to return per page. Set this property\nto the number of prediction results required. If zero, the service will\nchoose a reasonable default.\n\n### getPageToken\n\nOptional. The previous PredictResponse.next_page_token.\n\n### setPageToken\n\nOptional. The previous PredictResponse.next_page_token.\n\n### getFilter\n\nOptional. Filter for restricting prediction results. Accepts values for\ntags and the `filterOutOfStockItems` flag.\n\n- Tag expressions. Restricts predictions to items that match all of the specified tags. Boolean operators `OR` and `NOT` are supported if the expression is enclosed in parentheses, and must be separated from the tag values by a space. `-\"tagA\"` is also supported and is equivalent to `NOT \"tagA\"`. Tag values must be double quoted UTF-8 encoded strings with a size limit of 1 KiB.\n - filterOutOfStockItems. Restricts predictions to items that do not have a stockState value of OUT_OF_STOCK. Examples:\n - tag=(\"Red\" OR \"Blue\") tag=\"New-Arrival\" tag=(NOT \"promotional\")\n - filterOutOfStockItems tag=(-\"promotional\")\n - filterOutOfStockItems\n\n### setFilter\n\nOptional. Filter for restricting prediction results. Accepts values for\ntags and the `filterOutOfStockItems` flag.\n\n- Tag expressions. Restricts predictions to items that match all of the specified tags. Boolean operators `OR` and `NOT` are supported if the expression is enclosed in parentheses, and must be separated from the tag values by a space. `-\"tagA\"` is also supported and is equivalent to `NOT \"tagA\"`. Tag values must be double quoted UTF-8 encoded strings with a size limit of 1 KiB.\n - filterOutOfStockItems. Restricts predictions to items that do not have a stockState value of OUT_OF_STOCK. Examples:\n - tag=(\"Red\" OR \"Blue\") tag=\"New-Arrival\" tag=(NOT \"promotional\")\n - filterOutOfStockItems tag=(-\"promotional\")\n - filterOutOfStockItems\n\n### getDryRun\n\nOptional. Use dryRun mode for this prediction query. If set to true, a\ndummy model will be used that returns arbitrary catalog items.\n\nNote that the dryRun mode should only be used for testing the API, or if\nthe model is not ready.\n\n### setDryRun\n\nOptional. Use dryRun mode for this prediction query. If set to true, a\ndummy model will be used that returns arbitrary catalog items.\n\nNote that the dryRun mode should only be used for testing the API, or if\nthe model is not ready.\n\n### getParams\n\nOptional. Additional domain specific parameters for the predictions.\n\nAllowed values:\n\n- `returnCatalogItem`: Boolean. If set to true, the associated catalogItem object will be returned in the `PredictResponse.PredictionResult.itemMetadata` object in the method response.\n- `returnItemScore`: Boolean. If set to true, the prediction 'score' corresponding to each returned item will be set in the `metadata` field in the prediction response. The given 'score' indicates the probability of an item being clicked/purchased given the user's context and history.\n\n### setParams\n\nOptional. Additional domain specific parameters for the predictions.\n\nAllowed values:\n\n- `returnCatalogItem`: Boolean. If set to true, the associated catalogItem object will be returned in the `PredictResponse.PredictionResult.itemMetadata` object in the method response.\n- `returnItemScore`: Boolean. If set to true, the prediction 'score' corresponding to each returned item will be set in the `metadata` field in the prediction response. The given 'score' indicates the probability of an item being clicked/purchased given the user's context and history.\n\n### getLabels\n\nOptional. The labels for the predict request.\n\n- Label keys can contain lowercase letters, digits and hyphens, must start with a letter, and must end with a letter or digit.\n - Non-zero label values can contain lowercase letters, digits and hyphens, must start with a letter, and must end with a letter or digit.\n - No more than 64 labels can be associated with a given request. See \u003chttps://goo.gl/xmQnxf\u003e for more information on and examples of labels.\n\n### setLabels\n\nOptional. The labels for the predict request.\n\n- Label keys can contain lowercase letters, digits and hyphens, must start with a letter, and must end with a letter or digit.\n - Non-zero label values can contain lowercase letters, digits and hyphens, must start with a letter, and must end with a letter or digit.\n - No more than 64 labels can be associated with a given request. See \u003chttps://goo.gl/xmQnxf\u003e for more information on and examples of labels.\n\n### static::build"]]
