Struct google_api_proto::google::cloud::retail::v2::PredictRequest

pub struct PredictRequest {
    pub placement: String,
    pub user_event: Option<UserEvent>,
    pub page_size: i32,
    pub page_token: String,
    pub filter: String,
    pub validate_only: bool,
    pub params: BTreeMap<String, Value>,
    pub labels: BTreeMap<String, String>,
}

Request message for Predict method.

Fields

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] (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

user_event: Option<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][google.cloud.retail.v2.UserEvent.visitor_id] or [UserInfo.user_id][google.cloud.retail.v2.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][google.cloud.retail.v2.UserEvent.visitor_id] to a random unique ID and leave [UserInfo.user_id][google.cloud.retail.v2.UserInfo.user_id] unset.

page_size: i32

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.

page_token: String

👎Deprecated

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.

validate_only: 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: BTreeMap<String, Value>

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: BTreeMap<String, String>

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.

Trait Implementations

impl Clone for PredictRequest

fn clone(&self) -> PredictRequest

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for PredictRequest

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for PredictRequest

fn default() -> Self

Returns the “default value” for a type.

impl Message for PredictRequest

fn encoded_len(&self) -> usize

Returns the encoded length of the message without a length delimiter.

fn clear(&mut self)

Clears the message, resetting all fields to their default.

fn encode(&self, buf: &mut impl BufMut) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message to a buffer.

fn encode_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message to a newly allocated buffer.

fn encode_length_delimited( &self, buf: &mut impl BufMut, ) -> Result<(), EncodeError>

where Self: Sized,

Encodes the message with a length-delimiter to a buffer.

fn encode_length_delimited_to_vec(&self) -> Vec<u8>

where Self: Sized,

Encodes the message with a length-delimiter to a newly allocated buffer.

fn decode(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes an instance of the message from a buffer.

fn decode_length_delimited(buf: impl Buf) -> Result<Self, DecodeError>

where Self: Default,

Decodes a length-delimited instance of the message from the buffer.

fn merge(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes an instance of the message from a buffer, and merges it into self.

fn merge_length_delimited(&mut self, buf: impl Buf) -> Result<(), DecodeError>

where Self: Sized,

Decodes a length-delimited instance of the message from buffer, and merges it into self.

impl PartialEq for PredictRequest

fn eq(&self, other: &PredictRequest) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for PredictRequest