Class PredictRequest (1.6.0)

Request message for Predict method.

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.

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.

Maximum number of results to return per page. 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.

The previous PredictResponse.next_page_token.

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.

Required. Full resource name of the format: {name=projects//locations/global/catalogs/default_catalog/placements/} The ID of the Recommendations AI placement. Before you can request predictions from your model, you must create at least one placement for it. For more information, see Managing placements.

The full list of available placements can be seen at https://console.cloud.google.com/recommendation/catalogs/default_catalog/placements

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.

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.