Google Cloud Retail V2 Client - Class PredictionServiceClient (1.0.1)

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();
}

Methods

__construct

Constructor.

Parameters
Name	Description
`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 {@see} object or {@see} 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 {@see} .
`↳ 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 {@see} 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 {@see} and {@see} 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
Name	Description
`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 Managing serving configurations. 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 generic (unfiltered) popular products. If you only want results strictly matching the filters, set `strictFiltering` to True in `PredictRequest.params` to receive empty results instead. 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"))
`↳ 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 an 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 {@see} object, or an associative array of retry settings parameters. See the documentation on {@see} for example usage.

Returns
Type	Description
`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/&#42;/locations/global/catalogs/default_catalog/servingConfigs/*}`
 *                                   or
 *                                   `{placement=projects/&#42;/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
 *                                   [Managing serving configurations]
 *                                   (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());
    }
}

/**
 * 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);
}

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.