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feat: add pin_control_metadata to SearchResponse docs: keep the API doc up-to-date with recent changes PiperOrigin-RevId: 751590638
277 lines
11 KiB
Protocol Buffer
277 lines
11 KiB
Protocol Buffer
// Copyright 2025 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.v2beta;
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import "google/api/field_behavior.proto";
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import "google/api/resource.proto";
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import "google/cloud/retail/v2beta/common.proto";
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import "google/protobuf/timestamp.proto";
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option csharp_namespace = "Google.Cloud.Retail.V2Beta";
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option go_package = "cloud.google.com/go/retail/apiv2beta/retailpb;retailpb";
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option java_multiple_files = true;
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option java_outer_classname = "ModelProto";
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option java_package = "com.google.cloud.retail.v2beta";
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option objc_class_prefix = "RETAIL";
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option php_namespace = "Google\\Cloud\\Retail\\V2beta";
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option ruby_package = "Google::Cloud::Retail::V2beta";
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// Metadata that describes the training and serving parameters of a
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// [Model][google.cloud.retail.v2beta.Model]. A
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// [Model][google.cloud.retail.v2beta.Model] can be associated with a
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// [ServingConfig][google.cloud.retail.v2beta.ServingConfig] and then queried
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// through the Predict API.
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message Model {
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option (google.api.resource) = {
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type: "retail.googleapis.com/Model"
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pattern: "projects/{project}/locations/{location}/catalogs/{catalog}/models/{model}"
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};
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// Represents an ordered combination of valid serving configs, which
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// can be used for `PAGE_OPTIMIZATION` recommendations.
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message ServingConfigList {
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// Optional. A set of valid serving configs that may be used for
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// `PAGE_OPTIMIZATION`.
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repeated string serving_config_ids = 1
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[(google.api.field_behavior) = OPTIONAL];
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}
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// Additional configs for the frequently-bought-together model type.
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message FrequentlyBoughtTogetherFeaturesConfig {
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// Optional. Specifies the context of the model when it is used in predict
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// requests. Can only be set for the `frequently-bought-together` type. If
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// it isn't specified, it defaults to
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// [MULTIPLE_CONTEXT_PRODUCTS][google.cloud.retail.v2beta.Model.ContextProductsType.MULTIPLE_CONTEXT_PRODUCTS].
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ContextProductsType context_products_type = 2
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[(google.api.field_behavior) = OPTIONAL];
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}
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// Additional model features config.
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message ModelFeaturesConfig {
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oneof type_dedicated_config {
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// Additional configs for frequently-bought-together models.
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FrequentlyBoughtTogetherFeaturesConfig frequently_bought_together_config =
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1;
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}
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}
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// The serving state of the model.
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enum ServingState {
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// Unspecified serving state.
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SERVING_STATE_UNSPECIFIED = 0;
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// The model is not serving.
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INACTIVE = 1;
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// The model is serving and can be queried.
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ACTIVE = 2;
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// The model is trained on tuned hyperparameters and can be
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// queried.
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TUNED = 3;
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}
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// The training state of the model.
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enum TrainingState {
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// Unspecified training state.
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TRAINING_STATE_UNSPECIFIED = 0;
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// The model training is paused.
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PAUSED = 1;
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// The model is training.
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TRAINING = 2;
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}
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// Describes whether periodic tuning is enabled for this model
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// or not. Periodic tuning is scheduled at most every three months. You can
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// start a tuning process manually by using the `TuneModel`
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// method, which starts a tuning process immediately and resets the quarterly
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// schedule. Enabling or disabling periodic tuning does not affect any
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// current tuning processes.
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enum PeriodicTuningState {
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// Unspecified default value, should never be explicitly set.
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PERIODIC_TUNING_STATE_UNSPECIFIED = 0;
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// The model has periodic tuning disabled. Tuning
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// can be reenabled by calling the `EnableModelPeriodicTuning`
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// method or by calling the `TuneModel` method.
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PERIODIC_TUNING_DISABLED = 1;
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// The model cannot be tuned with periodic tuning OR the
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// `TuneModel` method. Hide the options in customer UI and
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// reject any requests through the backend self serve API.
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ALL_TUNING_DISABLED = 3;
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// The model has periodic tuning enabled. Tuning
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// can be disabled by calling the `DisableModelPeriodicTuning`
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// method.
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PERIODIC_TUNING_ENABLED = 2;
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}
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// Describes whether this model have sufficient training data
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// to be continuously trained.
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enum DataState {
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// Unspecified default value, should never be explicitly set.
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DATA_STATE_UNSPECIFIED = 0;
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// The model has sufficient training data.
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DATA_OK = 1;
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// The model does not have sufficient training data. Error
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// messages can be queried via Stackdriver.
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DATA_ERROR = 2;
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}
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// Use single or multiple context products for recommendations.
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enum ContextProductsType {
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// Unspecified default value, should never be explicitly set.
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// Defaults to
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// [MULTIPLE_CONTEXT_PRODUCTS][google.cloud.retail.v2beta.Model.ContextProductsType.MULTIPLE_CONTEXT_PRODUCTS].
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CONTEXT_PRODUCTS_TYPE_UNSPECIFIED = 0;
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// Use only a single product as context for the recommendation. Typically
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// used on pages like add-to-cart or product details.
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SINGLE_CONTEXT_PRODUCT = 1;
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// Use one or multiple products as context for the recommendation. Typically
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// used on shopping cart pages.
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MULTIPLE_CONTEXT_PRODUCTS = 2;
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}
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// Required. The fully qualified resource name of the model.
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//
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// Format:
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// `projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}`
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// catalog_id has char limit of 50.
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// recommendation_model_id has char limit of 40.
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string name = 1 [(google.api.field_behavior) = REQUIRED];
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// Required. The display name of the model.
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//
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// Should be human readable, used to display Recommendation Models in the
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// Retail Cloud Console Dashboard. UTF-8 encoded string with limit of 1024
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// characters.
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string display_name = 2 [(google.api.field_behavior) = REQUIRED];
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// Optional. The training state that the model is in (e.g.
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// `TRAINING` or `PAUSED`).
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//
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// Since part of the cost of running the service
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// is frequency of training - this can be used to determine when to train
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// model in order to control cost. If not specified: the default value for
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// `CreateModel` method is `TRAINING`. The default value for
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// `UpdateModel` method is to keep the state the same as before.
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TrainingState training_state = 3 [(google.api.field_behavior) = OPTIONAL];
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// Output only. The serving state of the model: `ACTIVE`, `NOT_ACTIVE`.
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ServingState serving_state = 4 [(google.api.field_behavior) = OUTPUT_ONLY];
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// Output only. Timestamp the Recommendation Model was created at.
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google.protobuf.Timestamp create_time = 5
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[(google.api.field_behavior) = OUTPUT_ONLY];
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// Output only. Timestamp the Recommendation Model was last updated. E.g.
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// if a Recommendation Model was paused - this would be the time the pause was
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// initiated.
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google.protobuf.Timestamp update_time = 6
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[(google.api.field_behavior) = OUTPUT_ONLY];
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// Required. The type of model e.g. `home-page`.
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//
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// Currently supported values: `recommended-for-you`, `others-you-may-like`,
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// `frequently-bought-together`, `page-optimization`, `similar-items`,
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// `buy-it-again`, `on-sale-items`, and `recently-viewed`(readonly value).
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//
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// This field together with
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// [optimization_objective][google.cloud.retail.v2beta.Model.optimization_objective]
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// describe model metadata to use to control model training and serving.
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// See https://cloud.google.com/retail/docs/models
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// for more details on what the model metadata control and which combination
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// of parameters are valid. For invalid combinations of parameters (e.g. type
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// = `frequently-bought-together` and optimization_objective = `ctr`), you
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// receive an error 400 if you try to create/update a recommendation with
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// this set of knobs.
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string type = 7 [(google.api.field_behavior) = REQUIRED];
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// Optional. The optimization objective e.g. `cvr`.
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//
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// Currently supported
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// values: `ctr`, `cvr`, `revenue-per-order`.
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//
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// If not specified, we choose default based on model type.
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// Default depends on type of recommendation:
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//
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// `recommended-for-you` => `ctr`
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//
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// `others-you-may-like` => `ctr`
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//
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// `frequently-bought-together` => `revenue_per_order`
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//
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// This field together with
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// [optimization_objective][google.cloud.retail.v2beta.Model.type]
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// describe model metadata to use to control model training and serving.
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// See https://cloud.google.com/retail/docs/models
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// for more details on what the model metadata control and which combination
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// of parameters are valid. For invalid combinations of parameters (e.g. type
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// = `frequently-bought-together` and optimization_objective = `ctr`), you
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// receive an error 400 if you try to create/update a recommendation with
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// this set of knobs.
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string optimization_objective = 8 [(google.api.field_behavior) = OPTIONAL];
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// Optional. The state of periodic tuning.
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//
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// The period we use is 3 months - to do a
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// one-off tune earlier use the `TuneModel` method. Default value
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// is `PERIODIC_TUNING_ENABLED`.
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PeriodicTuningState periodic_tuning_state = 11
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[(google.api.field_behavior) = OPTIONAL];
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// Output only. The timestamp when the latest successful tune finished.
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google.protobuf.Timestamp last_tune_time = 12
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[(google.api.field_behavior) = OUTPUT_ONLY];
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// Output only. The tune operation associated with the model.
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//
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// Can be used to determine if there is an ongoing tune for this
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// recommendation. Empty field implies no tune is goig on.
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string tuning_operation = 15 [(google.api.field_behavior) = OUTPUT_ONLY];
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// Output only. The state of data requirements for this model: `DATA_OK` and
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// `DATA_ERROR`.
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//
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// Recommendation model cannot be trained if the data is in
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// `DATA_ERROR` state. Recommendation model can have `DATA_ERROR` state even
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// if serving state is `ACTIVE`: models were trained successfully before, but
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// cannot be refreshed because model no longer has sufficient
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// data for training.
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DataState data_state = 16 [(google.api.field_behavior) = OUTPUT_ONLY];
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// Optional. If `RECOMMENDATIONS_FILTERING_ENABLED`, recommendation filtering
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// by attributes is enabled for the model.
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RecommendationsFilteringOption filtering_option = 18
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[(google.api.field_behavior) = OPTIONAL];
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// Output only. The list of valid serving configs associated with the
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// PageOptimizationConfig.
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repeated ServingConfigList serving_config_lists = 19
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[(google.api.field_behavior) = OUTPUT_ONLY];
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// Optional. Additional model features config.
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ModelFeaturesConfig model_features_config = 22
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[(google.api.field_behavior) = OPTIONAL];
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}
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