191 lines
8.1 KiB
Protocol Buffer
191 lines
8.1 KiB
Protocol Buffer
// Copyright 2020 Google LLC
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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syntax = "proto3";
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package google.cloud.retail.v2;
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import "google/api/annotations.proto";
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import "google/api/client.proto";
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import "google/api/field_behavior.proto";
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import "google/cloud/retail/v2/user_event.proto";
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import "google/protobuf/struct.proto";
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option csharp_namespace = "Google.Cloud.Retail.V2";
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option go_package = "google.golang.org/genproto/googleapis/cloud/retail/v2;retail";
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option java_multiple_files = true;
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option java_outer_classname = "PredictionServiceProto";
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option java_package = "com.google.cloud.retail.v2";
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option objc_class_prefix = "RETAIL";
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option php_namespace = "Google\\Cloud\\Retail\\V2";
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option ruby_package = "Google::Cloud::Retail::V2";
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// Service for making recommendation prediction.
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service PredictionService {
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option (google.api.default_host) = "retail.googleapis.com";
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option (google.api.oauth_scopes) =
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"https://www.googleapis.com/auth/cloud-platform";
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// Makes a recommendation prediction.
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rpc Predict(PredictRequest) returns (PredictResponse) {
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option (google.api.http) = {
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post: "/v2/{placement=projects/*/locations/*/catalogs/*/placements/*}:predict"
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body: "*"
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};
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}
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}
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// Request message for Predict method.
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message PredictRequest {
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// Required. Full resource name of the format:
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// {name=projects/*/locations/global/catalogs/default_catalog/placements/*}
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// The id of the recommendation engine placement. This id is used to identify
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// the set of models that will be used to make the prediction.
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//
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// We currently support three placements with the following IDs by default:
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//
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// * `shopping_cart`: Predicts products frequently bought together with one or
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// more products in the same shopping session. Commonly displayed after
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// `add-to-cart` events, on product detail pages, or on the shopping cart
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// page.
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//
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// * `home_page`: Predicts the next product that a user will most likely
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// engage with or purchase based on the shopping or viewing history of the
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// specified `userId` or `visitorId`. For example - Recommendations for you.
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//
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// * `product_detail`: Predicts the next product that a user will most likely
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// engage with or purchase. The prediction is based on the shopping or
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// viewing history of the specified `userId` or `visitorId` and its
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// relevance to a specified `CatalogItem`. Typically used on product detail
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// pages. For example - More products like this.
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//
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// * `recently_viewed_default`: Returns up to 75 products recently viewed by
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// the specified `userId` or `visitorId`, most recent ones first. Returns
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// nothing if neither of them has viewed any products yet. For example -
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// Recently viewed.
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//
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// The full list of available placements can be seen at
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// https://console.cloud.google.com/recommendation/catalogs/default_catalog/placements
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string placement = 1 [(google.api.field_behavior) = REQUIRED];
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// Required. Context about the user, what they are looking at and what action
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// they took to trigger the predict request. Note that this user event detail
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// won't be ingested to userEvent logs. Thus, a separate userEvent write
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// request is required for event logging.
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UserEvent user_event = 2 [(google.api.field_behavior) = REQUIRED];
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// Maximum number of results to return per page. Set this property
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// to the number of prediction results needed. If zero, the service will
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// choose a reasonable default. The maximum allowed value is 100. Values
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// above 100 will be coerced to 100.
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int32 page_size = 3;
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// The previous PredictResponse.next_page_token.
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string page_token = 4;
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// Filter for restricting prediction results with a length limit of 5,000
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// characters. Accepts values for tags and the `filterOutOfStockItems` flag.
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//
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// * Tag expressions. Restricts predictions to products that match all of the
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// specified tags. Boolean operators `OR` and `NOT` are supported if the
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// expression is enclosed in parentheses, and must be separated from the
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// tag values by a space. `-"tagA"` is also supported and is equivalent to
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// `NOT "tagA"`. Tag values must be double quoted UTF-8 encoded strings
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// with a size limit of 1,000 characters.
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//
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// * filterOutOfStockItems. Restricts predictions to products that do not
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// have a
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// stockState value of OUT_OF_STOCK.
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//
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// Examples:
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//
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// * tag=("Red" OR "Blue") tag="New-Arrival" tag=(NOT "promotional")
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// * filterOutOfStockItems tag=(-"promotional")
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// * filterOutOfStockItems
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//
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// If your filter blocks all prediction results, nothing will be returned. If
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// you want generic (unfiltered) popular products to be returned instead, set
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// `strictFiltering` to false in `PredictRequest.params`.
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string filter = 5;
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// Use validate only mode for this prediction query. If set to true, a
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// dummy model will be used that returns arbitrary products.
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// Note that the validate only mode should only be used for testing the API,
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// or if the model is not ready.
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bool validate_only = 6;
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// Additional domain specific parameters for the predictions.
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//
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// Allowed values:
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//
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// * `returnProduct`: Boolean. If set to true, the associated product
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// object will be returned in the `results.metadata` field in the
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// prediction response.
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// * `returnScore`: Boolean. If set to true, the prediction 'score'
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// corresponding to each returned product will be set in the
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// `results.metadata` field in the prediction response. The given
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// 'score' indicates the probability of an product being clicked/purchased
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// given the user's context and history.
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// * `strictFiltering`: Boolean. True by default. If set to false, the service
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// will return generic (unfiltered) popular products instead of empty if
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// your filter blocks all prediction results.
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map<string, google.protobuf.Value> params = 7;
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// The labels for the predict request.
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//
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// * Label keys can contain lowercase letters, digits and hyphens, must start
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// with a letter, and must end with a letter or digit.
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// * Non-zero label values can contain lowercase letters, digits and hyphens,
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// must start with a letter, and must end with a letter or digit.
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// * No more than 64 labels can be associated with a given request.
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//
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// See https://goo.gl/xmQnxf for more information on and examples of labels.
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map<string, string> labels = 8;
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}
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// Response message for predict method.
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message PredictResponse {
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// PredictionResult represents the recommendation prediction results.
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message PredictionResult {
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// ID of the recommended product
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string id = 1;
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// Additional product metadata / annotations.
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//
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// Possible values:
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//
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// * `product`: JSON representation of the product. Will be set if
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// `returnProduct` is set to true in `PredictRequest.params`.
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// * `score`: Prediction score in double value. Will be set if
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// `returnScore` is set to true in `PredictRequest.params`.
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map<string, google.protobuf.Value> metadata = 2;
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}
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// A list of recommended products. The order represents the ranking (from the
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// most relevant product to the least).
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repeated PredictionResult results = 1;
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// A unique attribution token. This should be included in the
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// [UserEvent][google.cloud.retail.v2.UserEvent] logs resulting from this
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// recommendation, which enables accurate attribution of recommendation model
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// performance.
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string attribution_token = 2;
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// IDs of products in the request that were missing from the inventory.
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repeated string missing_ids = 3;
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// True if the validateOnly property was set in the request.
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bool validate_only = 4;
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}
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