googleapis/google/cloud/retail/v2/prediction_service.proto

191 lines
8.1 KiB
Protocol Buffer

// Copyright 2020 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
syntax = "proto3";
package google.cloud.retail.v2;
import "google/api/annotations.proto";
import "google/api/client.proto";
import "google/api/field_behavior.proto";
import "google/cloud/retail/v2/user_event.proto";
import "google/protobuf/struct.proto";
option csharp_namespace = "Google.Cloud.Retail.V2";
option go_package = "google.golang.org/genproto/googleapis/cloud/retail/v2;retail";
option java_multiple_files = true;
option java_outer_classname = "PredictionServiceProto";
option java_package = "com.google.cloud.retail.v2";
option objc_class_prefix = "RETAIL";
option php_namespace = "Google\\Cloud\\Retail\\V2";
option ruby_package = "Google::Cloud::Retail::V2";
// Service for making recommendation prediction.
service PredictionService {
option (google.api.default_host) = "retail.googleapis.com";
option (google.api.oauth_scopes) =
"https://www.googleapis.com/auth/cloud-platform";
// Makes a recommendation prediction.
rpc Predict(PredictRequest) returns (PredictResponse) {
option (google.api.http) = {
post: "/v2/{placement=projects/*/locations/*/catalogs/*/placements/*}:predict"
body: "*"
};
}
}
// Request message for Predict method.
message PredictRequest {
// Required. Full resource name of the format:
// {name=projects/*/locations/global/catalogs/default_catalog/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 products frequently bought together with one or
// more products 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 products like this.
//
// * `recently_viewed_default`: Returns up to 75 products recently viewed by
// the specified `userId` or `visitorId`, most recent ones first. Returns
// nothing if neither of them has viewed any products yet. For example -
// Recently viewed.
//
// The full list of available placements can be seen at
// https://console.cloud.google.com/recommendation/catalogs/default_catalog/placements
string placement = 1 [(google.api.field_behavior) = REQUIRED];
// 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.
UserEvent user_event = 2 [(google.api.field_behavior) = REQUIRED];
// 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.
int32 page_size = 3;
// The previous PredictResponse.next_page_token.
string page_token = 4;
// 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.
//
// * 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, nothing will be returned. If
// you want generic (unfiltered) popular products to be returned instead, set
// `strictFiltering` to false in `PredictRequest.params`.
string filter = 5;
// 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.
bool validate_only = 6;
// 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.
map<string, google.protobuf.Value> params = 7;
// 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.
map<string, string> labels = 8;
}
// Response message for predict method.
message PredictResponse {
// PredictionResult represents the recommendation prediction results.
message PredictionResult {
// ID of the recommended product
string id = 1;
// Additional product metadata / annotations.
//
// Possible values:
//
// * `product`: JSON representation of the product. Will be set if
// `returnProduct` is set to true in `PredictRequest.params`.
// * `score`: Prediction score in double value. Will be set if
// `returnScore` is set to true in `PredictRequest.params`.
map<string, google.protobuf.Value> metadata = 2;
}
// A list of recommended products. The order represents the ranking (from the
// most relevant product to the least).
repeated PredictionResult results = 1;
// A unique attribution token. This should be included in the
// [UserEvent][google.cloud.retail.v2.UserEvent] logs resulting from this
// recommendation, which enables accurate attribution of recommendation model
// performance.
string attribution_token = 2;
// IDs of products in the request that were missing from the inventory.
repeated string missing_ids = 3;
// True if the validateOnly property was set in the request.
bool validate_only = 4;
}