Google Cloud Retail V2 Client - Class PredictionServiceClient (1.4.2)

Reference documentation and code samples for the Google Cloud Retail V2 Client class PredictionServiceClient.

Service Description: Service for making recommendation prediction.

This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:

$predictionServiceClient = new PredictionServiceClient();
try {
    $placement = 'placement';
    $userEvent = new UserEvent();
    $response = $predictionServiceClient->predict($placement, $userEvent);
} finally {
    $predictionServiceClient->close();
}

Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parseName method to extract the individual identifiers contained within formatted names that are returned by the API.

This service has a new (beta) implementation. See Google\Cloud\Retail\V2\Client\PredictionServiceClient to use the new surface.

Namespace

Google \ Cloud \ Retail \ V2

Methods

__construct

Constructor.

Parameters
NameDescription
options array

Optional. Options for configuring the service API wrapper.

↳ apiEndpoint string

The address of the API remote host. May optionally include the port, formatted as "

↳ credentials string|array|FetchAuthTokenInterface|CredentialsWrapper

The credentials to be used by the client to authorize API calls. This option accepts either a path to a credentials file, or a decoded credentials file as a PHP array. Advanced usage: In addition, this option can also accept a pre-constructed Google\Auth\FetchAuthTokenInterface object or Google\ApiCore\CredentialsWrapper object. Note that when one of these objects are provided, any settings in $credentialsConfig will be ignored.

↳ credentialsConfig array

Options used to configure credentials, including auth token caching, for the client. For a full list of supporting configuration options, see Google\ApiCore\CredentialsWrapper::build() .

↳ disableRetries bool

Determines whether or not retries defined by the client configuration should be disabled. Defaults to false.

↳ clientConfig string|array

Client method configuration, including retry settings. This option can be either a path to a JSON file, or a PHP array containing the decoded JSON data. By default this settings points to the default client config file, which is provided in the resources folder.

↳ transport string|TransportInterface

The transport used for executing network requests. May be either the string rest or grpc. Defaults to grpc if gRPC support is detected on the system. Advanced usage: Additionally, it is possible to pass in an already instantiated Google\ApiCore\Transport\TransportInterface object. Note that when this object is provided, any settings in $transportConfig, and any $apiEndpoint setting, will be ignored.

↳ transportConfig array

Configuration options that will be used to construct the transport. Options for each supported transport type should be passed in a key for that transport. For example: $transportConfig = [ 'grpc' => [...], 'rest' => [...], ]; See the Google\ApiCore\Transport\GrpcTransport::build() and Google\ApiCore\Transport\RestTransport::build() methods for the supported options.

↳ clientCertSource callable

A callable which returns the client cert as a string. This can be used to provide a certificate and private key to the transport layer for mTLS.

predict

Makes a recommendation prediction.

Parameters
NameDescription
placement string

Required. Full resource name of the format: {placement=projects/*/locations/global/catalogs/default_catalog/servingConfigs/*} or {placement=projects/*/locations/global/catalogs/default_catalog/placements/*}. We recommend using the servingConfigs resource. placements is a legacy resource. The ID of the Recommendations AI serving config or placement. Before you can request predictions from your model, you must create at least one serving config or placement for it. For more information, see Manage serving configs.

The full list of available serving configs can be seen at https://console.cloud.google.com/ai/retail/catalogs/default_catalog/configs

userEvent Google\Cloud\Retail\V2\UserEvent

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.

Don't set UserEvent.visitor_id or UserInfo.user_id to the same fixed ID for different users. If you are trying to receive non-personalized recommendations (not recommended; this can negatively impact model performance), instead set UserEvent.visitor_id to a random unique ID and leave UserInfo.user_id unset.

optionalArgs array

Optional.

↳ pageSize int

Maximum number of results to return. Set this property to the number of prediction results needed. If zero, the service will choose a reasonable default. The maximum allowed value is 100. Values above 100 will be coerced to 100.

↳ pageToken string

This field is not used; leave it unset.

↳ filter string

Filter for restricting prediction results with a length limit of 5,000 characters. Accepts values for tags and the filterOutOfStockItems flag. * Tag expressions. Restricts predictions to products 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 1,000 characters. Note: "Recently viewed" models don't support tag filtering at the moment. * filterOutOfStockItems. Restricts predictions to products 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 If your filter blocks all prediction results, the API will return no results. If instead you want empty result sets to return generic (unfiltered) popular products, set strictFiltering to False in PredictRequest.params. Note that the API will never return items with storageStatus of "EXPIRED" or "DELETED" regardless of filter choices. If filterSyntaxV2 is set to true under the params field, then attribute-based expressions are expected instead of the above described tag-based syntax. Examples: * (colors: ANY("Red", "Blue")) AND NOT (categories: ANY("Phones")) * (availability: ANY("IN_STOCK")) AND (colors: ANY("Red") OR categories: ANY("Phones")) For more information, see Filter recommendations.

↳ validateOnly bool

Use validate only mode for this prediction query. If set to true, a dummy model will be used that returns arbitrary products. Note that the validate only mode should only be used for testing the API, or if the model is not ready.

↳ params array

Additional domain specific parameters for the predictions. Allowed values: * returnProduct: Boolean. If set to true, the associated product object will be returned in the results.metadata field in the prediction response. * returnScore: Boolean. If set to true, the prediction 'score' corresponding to each returned product will be set in the results.metadata field in the prediction response. The given 'score' indicates the probability of a product being clicked/purchased given the user's context and history. * strictFiltering: Boolean. True by default. If set to false, the service will return generic (unfiltered) popular products instead of empty if your filter blocks all prediction results. * priceRerankLevel: String. Default empty. If set to be non-empty, then it needs to be one of {'no-price-reranking', 'low-price-reranking', 'medium-price-reranking', 'high-price-reranking'}. This gives request-level control and adjusts prediction results based on product price. * diversityLevel: String. Default empty. If set to be non-empty, then it needs to be one of {'no-diversity', 'low-diversity', 'medium-diversity', 'high-diversity', 'auto-diversity'}. This gives request-level control and adjusts prediction results based on product category. * filterSyntaxV2: Boolean. False by default. If set to true, the filter field is interpreteted according to the new, attribute-based syntax.

↳ labels array

The labels applied to a resource must meet the following requirements: * Each resource can have multiple labels, up to a maximum of 64. * Each label must be a key-value pair. * Keys have a minimum length of 1 character and a maximum length of 63 characters and cannot be empty. Values can be empty and have a maximum length of 63 characters. * Keys and values can contain only lowercase letters, numeric characters, underscores, and dashes. All characters must use UTF-8 encoding, and international characters are allowed. * The key portion of a label must be unique. However, you can use the same key with multiple resources. * Keys must start with a lowercase letter or international character. See Google Cloud Document for more details.

↳ retrySettings RetrySettings|array

Retry settings to use for this call. Can be a Google\ApiCore\RetrySettings object, or an associative array of retry settings parameters. See the documentation on Google\ApiCore\RetrySettings for example usage.

Returns
TypeDescription
Google\Cloud\Retail\V2\PredictResponse
Example
use Google\ApiCore\ApiException;
use Google\Cloud\Retail\V2\PredictResponse;
use Google\Cloud\Retail\V2\PredictionServiceClient;
use Google\Cloud\Retail\V2\UserEvent;

/**
 * @param string $placement          Full resource name of the format:
 *                                   `{placement=projects/*/locations/global/catalogs/default_catalog/servingConfigs/*}`
 *                                   or
 *                                   `{placement=projects/*/locations/global/catalogs/default_catalog/placements/*}`.
 *                                   We recommend using the `servingConfigs` resource. `placements` is a legacy
 *                                   resource.
 *                                   The ID of the Recommendations AI serving config or placement.
 *                                   Before you can request predictions from your model, you must create at
 *                                   least one serving config or placement for it. For more information, see
 *                                   [Manage serving configs]
 *                                   (https://cloud.google.com/retail/docs/manage-configs).
 *
 *                                   The full list of available serving configs can be seen at
 *                                   https://console.cloud.google.com/ai/retail/catalogs/default_catalog/configs
 * @param string $userEventEventType User event type. Allowed values are:
 *
 *                                   * `add-to-cart`: Products being added to cart.
 *                                   * `category-page-view`: Special pages such as sale or promotion pages
 *                                   viewed.
 *                                   * `detail-page-view`: Products detail page viewed.
 *                                   * `home-page-view`: Homepage viewed.
 *                                   * `promotion-offered`: Promotion is offered to a user.
 *                                   * `promotion-not-offered`: Promotion is not offered to a user.
 *                                   * `purchase-complete`: User finishing a purchase.
 *                                   * `search`: Product search.
 *                                   * `shopping-cart-page-view`: User viewing a shopping cart.
 * @param string $userEventVisitorId A unique identifier for tracking visitors.
 *
 *                                   For example, this could be implemented with an HTTP cookie, which should be
 *                                   able to uniquely identify a visitor on a single device. This unique
 *                                   identifier should not change if the visitor log in/out of the website.
 *
 *                                   Don't set the field to the same fixed ID for different users. This mixes
 *                                   the event history of those users together, which results in degraded model
 *                                   quality.
 *
 *                                   The field must be a UTF-8 encoded string with a length limit of 128
 *                                   characters. Otherwise, an INVALID_ARGUMENT error is returned.
 *
 *                                   The field should not contain PII or user-data. We recommend to use Google
 *                                   Analytics [Client
 *                                   ID](https://developers.google.com/analytics/devguides/collection/analyticsjs/field-reference#clientId)
 *                                   for this field.
 */
function predict_sample(
    string $placement,
    string $userEventEventType,
    string $userEventVisitorId
): void {
    // Create a client.
    $predictionServiceClient = new PredictionServiceClient();

    // Prepare any non-scalar elements to be passed along with the request.
    $userEvent = (new UserEvent())
        ->setEventType($userEventEventType)
        ->setVisitorId($userEventVisitorId);

    // Call the API and handle any network failures.
    try {
        /** @var PredictResponse $response */
        $response = $predictionServiceClient->predict($placement, $userEvent);
        printf('Response data: %s' . PHP_EOL, $response->serializeToJsonString());
    } catch (ApiException $ex) {
        printf('Call failed with message: %s' . PHP_EOL, $ex->getMessage());
    }
}

/**
 * Helper to execute the sample.
 *
 * This sample has been automatically generated and should be regarded as a code
 * template only. It will require modifications to work:
 *  - It may require correct/in-range values for request initialization.
 *  - It may require specifying regional endpoints when creating the service client,
 *    please see the apiEndpoint client configuration option for more details.
 */
function callSample(): void
{
    $placement = '[PLACEMENT]';
    $userEventEventType = '[EVENT_TYPE]';
    $userEventVisitorId = '[VISITOR_ID]';

    predict_sample($placement, $userEventEventType, $userEventVisitorId);
}

static::productName

Formats a string containing the fully-qualified path to represent a product resource.

Parameters
NameDescription
project string
location string
catalog string
branch string
product string
Returns
TypeDescription
stringThe formatted product resource.

static::parseName

Parses a formatted name string and returns an associative array of the components in the name.

The following name formats are supported: Template: Pattern

  • product: projects/{project}/locations/{location}/catalogs/{catalog}/branches/{branch}/products/{product}

The optional $template argument can be supplied to specify a particular pattern, and must match one of the templates listed above. If no $template argument is provided, or if the $template argument does not match one of the templates listed, then parseName will check each of the supported templates, and return the first match.

Parameters
NameDescription
formattedName string

The formatted name string

template string

Optional name of template to match

Returns
TypeDescription
arrayAn associative array from name component IDs to component values.

Constants

SERVICE_NAME

Value: 'google.cloud.retail.v2.PredictionService'

The name of the service.

SERVICE_ADDRESS

Value: 'retail.googleapis.com'

The default address of the service.

DEFAULT_SERVICE_PORT

Value: 443

The default port of the service.

CODEGEN_NAME

Value: 'gapic'

The name of the code generator, to be included in the agent header.