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/*
 * 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.
 */
/*
 * This code was generated by https://github.com/googleapis/google-api-java-client-services/
 * Modify at your own risk.
 */

package com.google.api.services.retail.v2.model;

/**
 * Metadata that describes the training and serving parameters of a Model. A Model can be associated
 * with a ServingConfig and then queried through the Predict API.
 *
 * 

This is the Java data model class that specifies how to parse/serialize into the JSON that is * transmitted over HTTP when working with the Vertex AI Search for Retail API. For a detailed * explanation see: * https://developers.google.com/api-client-library/java/google-http-java-client/json *

* * @author Google, Inc. */ @SuppressWarnings("javadoc") public final class GoogleCloudRetailV2alphaModel extends com.google.api.client.json.GenericJson { /** * Output only. Timestamp the Recommendation Model was created at. * The value may be {@code null}. */ @com.google.api.client.util.Key private String createTime; /** * Output only. The state of data requirements for this model: `DATA_OK` and `DATA_ERROR`. * Recommendation model cannot be trained if the data is in `DATA_ERROR` state. Recommendation * model can have `DATA_ERROR` state even if serving state is `ACTIVE`: models were trained * successfully before, but cannot be refreshed because model no longer has sufficient data for * training. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String dataState; /** * Required. The display name of the model. Should be human readable, used to display * Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of * 1024 characters. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String displayName; /** * Optional. If `RECOMMENDATIONS_FILTERING_ENABLED`, recommendation filtering by attributes is * enabled for the model. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String filteringOption; /** * Output only. The timestamp when the latest successful tune finished. * The value may be {@code null}. */ @com.google.api.client.util.Key private String lastTuneTime; /** * Optional. Additional model features config. * The value may be {@code null}. */ @com.google.api.client.util.Key private GoogleCloudRetailV2alphaModelModelFeaturesConfig modelFeaturesConfig; /** * Required. The fully qualified resource name of the model. Format: * `projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}` * catalog_id has char limit of 50. recommendation_model_id has char limit of 40. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String name; /** * Optional. The optimization objective e.g. `cvr`. Currently supported values: `ctr`, `cvr`, * `revenue-per-order`. If not specified, we choose default based on model type. Default depends * on type of recommendation: `recommended-for-you` => `ctr` `others-you-may-like` => `ctr` * `frequently-bought-together` => `revenue_per_order` This field together with * optimization_objective describe model metadata to use to control model training and serving. * See https://cloud.google.com/retail/docs/models for more details on what the model metadata * control and which combination of parameters are valid. For invalid combinations of parameters * (e.g. type = `frequently-bought-together` and optimization_objective = `ctr`), you receive an * error 400 if you try to create/update a recommendation with this set of knobs. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String optimizationObjective; /** * Optional. The page optimization config. * The value may be {@code null}. */ @com.google.api.client.util.Key private GoogleCloudRetailV2alphaModelPageOptimizationConfig pageOptimizationConfig; /** * Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune * earlier use the `TuneModel` method. Default value is `PERIODIC_TUNING_ENABLED`. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String periodicTuningState; /** * Output only. The list of valid serving configs associated with the PageOptimizationConfig. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.util.List servingConfigLists; /** * Output only. The serving state of the model: `ACTIVE`, `NOT_ACTIVE`. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String servingState; /** * Optional. The training state that the model is in (e.g. `TRAINING` or `PAUSED`). Since part of * the cost of running the service is frequency of training - this can be used to determine when * to train model in order to control cost. If not specified: the default value for `CreateModel` * method is `TRAINING`. The default value for `UpdateModel` method is to keep the state the same * as before. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String trainingState; /** * Output only. The tune operation associated with the model. Can be used to determine if there is * an ongoing tune for this recommendation. Empty field implies no tune is goig on. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String tuningOperation; /** * Required. The type of model e.g. `home-page`. Currently supported values: `recommended-for- * you`, `others-you-may-like`, `frequently-bought-together`, `page-optimization`, `similar- * items`, `buy-it-again`, `on-sale-items`, and `recently-viewed`(readonly value). This field * together with optimization_objective describe model metadata to use to control model training * and serving. See https://cloud.google.com/retail/docs/models for more details on what the model * metadata control and which combination of parameters are valid. For invalid combinations of * parameters (e.g. type = `frequently-bought-together` and optimization_objective = `ctr`), you * receive an error 400 if you try to create/update a recommendation with this set of knobs. * The value may be {@code null}. */ @com.google.api.client.util.Key private java.lang.String type; /** * Output only. Timestamp the Recommendation Model was last updated. E.g. if a Recommendation * Model was paused - this would be the time the pause was initiated. * The value may be {@code null}. */ @com.google.api.client.util.Key private String updateTime; /** * Output only. Timestamp the Recommendation Model was created at. * @return value or {@code null} for none */ public String getCreateTime() { return createTime; } /** * Output only. Timestamp the Recommendation Model was created at. * @param createTime createTime or {@code null} for none */ public GoogleCloudRetailV2alphaModel setCreateTime(String createTime) { this.createTime = createTime; return this; } /** * Output only. The state of data requirements for this model: `DATA_OK` and `DATA_ERROR`. * Recommendation model cannot be trained if the data is in `DATA_ERROR` state. Recommendation * model can have `DATA_ERROR` state even if serving state is `ACTIVE`: models were trained * successfully before, but cannot be refreshed because model no longer has sufficient data for * training. * @return value or {@code null} for none */ public java.lang.String getDataState() { return dataState; } /** * Output only. The state of data requirements for this model: `DATA_OK` and `DATA_ERROR`. * Recommendation model cannot be trained if the data is in `DATA_ERROR` state. Recommendation * model can have `DATA_ERROR` state even if serving state is `ACTIVE`: models were trained * successfully before, but cannot be refreshed because model no longer has sufficient data for * training. * @param dataState dataState or {@code null} for none */ public GoogleCloudRetailV2alphaModel setDataState(java.lang.String dataState) { this.dataState = dataState; return this; } /** * Required. The display name of the model. Should be human readable, used to display * Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of * 1024 characters. * @return value or {@code null} for none */ public java.lang.String getDisplayName() { return displayName; } /** * Required. The display name of the model. Should be human readable, used to display * Recommendation Models in the Retail Cloud Console Dashboard. UTF-8 encoded string with limit of * 1024 characters. * @param displayName displayName or {@code null} for none */ public GoogleCloudRetailV2alphaModel setDisplayName(java.lang.String displayName) { this.displayName = displayName; return this; } /** * Optional. If `RECOMMENDATIONS_FILTERING_ENABLED`, recommendation filtering by attributes is * enabled for the model. * @return value or {@code null} for none */ public java.lang.String getFilteringOption() { return filteringOption; } /** * Optional. If `RECOMMENDATIONS_FILTERING_ENABLED`, recommendation filtering by attributes is * enabled for the model. * @param filteringOption filteringOption or {@code null} for none */ public GoogleCloudRetailV2alphaModel setFilteringOption(java.lang.String filteringOption) { this.filteringOption = filteringOption; return this; } /** * Output only. The timestamp when the latest successful tune finished. * @return value or {@code null} for none */ public String getLastTuneTime() { return lastTuneTime; } /** * Output only. The timestamp when the latest successful tune finished. * @param lastTuneTime lastTuneTime or {@code null} for none */ public GoogleCloudRetailV2alphaModel setLastTuneTime(String lastTuneTime) { this.lastTuneTime = lastTuneTime; return this; } /** * Optional. Additional model features config. * @return value or {@code null} for none */ public GoogleCloudRetailV2alphaModelModelFeaturesConfig getModelFeaturesConfig() { return modelFeaturesConfig; } /** * Optional. Additional model features config. * @param modelFeaturesConfig modelFeaturesConfig or {@code null} for none */ public GoogleCloudRetailV2alphaModel setModelFeaturesConfig(GoogleCloudRetailV2alphaModelModelFeaturesConfig modelFeaturesConfig) { this.modelFeaturesConfig = modelFeaturesConfig; return this; } /** * Required. The fully qualified resource name of the model. Format: * `projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}` * catalog_id has char limit of 50. recommendation_model_id has char limit of 40. * @return value or {@code null} for none */ public java.lang.String getName() { return name; } /** * Required. The fully qualified resource name of the model. Format: * `projects/{project_number}/locations/{location_id}/catalogs/{catalog_id}/models/{model_id}` * catalog_id has char limit of 50. recommendation_model_id has char limit of 40. * @param name name or {@code null} for none */ public GoogleCloudRetailV2alphaModel setName(java.lang.String name) { this.name = name; return this; } /** * Optional. The optimization objective e.g. `cvr`. Currently supported values: `ctr`, `cvr`, * `revenue-per-order`. If not specified, we choose default based on model type. Default depends * on type of recommendation: `recommended-for-you` => `ctr` `others-you-may-like` => `ctr` * `frequently-bought-together` => `revenue_per_order` This field together with * optimization_objective describe model metadata to use to control model training and serving. * See https://cloud.google.com/retail/docs/models for more details on what the model metadata * control and which combination of parameters are valid. For invalid combinations of parameters * (e.g. type = `frequently-bought-together` and optimization_objective = `ctr`), you receive an * error 400 if you try to create/update a recommendation with this set of knobs. * @return value or {@code null} for none */ public java.lang.String getOptimizationObjective() { return optimizationObjective; } /** * Optional. The optimization objective e.g. `cvr`. Currently supported values: `ctr`, `cvr`, * `revenue-per-order`. If not specified, we choose default based on model type. Default depends * on type of recommendation: `recommended-for-you` => `ctr` `others-you-may-like` => `ctr` * `frequently-bought-together` => `revenue_per_order` This field together with * optimization_objective describe model metadata to use to control model training and serving. * See https://cloud.google.com/retail/docs/models for more details on what the model metadata * control and which combination of parameters are valid. For invalid combinations of parameters * (e.g. type = `frequently-bought-together` and optimization_objective = `ctr`), you receive an * error 400 if you try to create/update a recommendation with this set of knobs. * @param optimizationObjective optimizationObjective or {@code null} for none */ public GoogleCloudRetailV2alphaModel setOptimizationObjective(java.lang.String optimizationObjective) { this.optimizationObjective = optimizationObjective; return this; } /** * Optional. The page optimization config. * @return value or {@code null} for none */ public GoogleCloudRetailV2alphaModelPageOptimizationConfig getPageOptimizationConfig() { return pageOptimizationConfig; } /** * Optional. The page optimization config. * @param pageOptimizationConfig pageOptimizationConfig or {@code null} for none */ public GoogleCloudRetailV2alphaModel setPageOptimizationConfig(GoogleCloudRetailV2alphaModelPageOptimizationConfig pageOptimizationConfig) { this.pageOptimizationConfig = pageOptimizationConfig; return this; } /** * Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune * earlier use the `TuneModel` method. Default value is `PERIODIC_TUNING_ENABLED`. * @return value or {@code null} for none */ public java.lang.String getPeriodicTuningState() { return periodicTuningState; } /** * Optional. The state of periodic tuning. The period we use is 3 months - to do a one-off tune * earlier use the `TuneModel` method. Default value is `PERIODIC_TUNING_ENABLED`. * @param periodicTuningState periodicTuningState or {@code null} for none */ public GoogleCloudRetailV2alphaModel setPeriodicTuningState(java.lang.String periodicTuningState) { this.periodicTuningState = periodicTuningState; return this; } /** * Output only. The list of valid serving configs associated with the PageOptimizationConfig. * @return value or {@code null} for none */ public java.util.List getServingConfigLists() { return servingConfigLists; } /** * Output only. The list of valid serving configs associated with the PageOptimizationConfig. * @param servingConfigLists servingConfigLists or {@code null} for none */ public GoogleCloudRetailV2alphaModel setServingConfigLists(java.util.List servingConfigLists) { this.servingConfigLists = servingConfigLists; return this; } /** * Output only. The serving state of the model: `ACTIVE`, `NOT_ACTIVE`. * @return value or {@code null} for none */ public java.lang.String getServingState() { return servingState; } /** * Output only. The serving state of the model: `ACTIVE`, `NOT_ACTIVE`. * @param servingState servingState or {@code null} for none */ public GoogleCloudRetailV2alphaModel setServingState(java.lang.String servingState) { this.servingState = servingState; return this; } /** * Optional. The training state that the model is in (e.g. `TRAINING` or `PAUSED`). Since part of * the cost of running the service is frequency of training - this can be used to determine when * to train model in order to control cost. If not specified: the default value for `CreateModel` * method is `TRAINING`. The default value for `UpdateModel` method is to keep the state the same * as before. * @return value or {@code null} for none */ public java.lang.String getTrainingState() { return trainingState; } /** * Optional. The training state that the model is in (e.g. `TRAINING` or `PAUSED`). Since part of * the cost of running the service is frequency of training - this can be used to determine when * to train model in order to control cost. If not specified: the default value for `CreateModel` * method is `TRAINING`. The default value for `UpdateModel` method is to keep the state the same * as before. * @param trainingState trainingState or {@code null} for none */ public GoogleCloudRetailV2alphaModel setTrainingState(java.lang.String trainingState) { this.trainingState = trainingState; return this; } /** * Output only. The tune operation associated with the model. Can be used to determine if there is * an ongoing tune for this recommendation. Empty field implies no tune is goig on. * @return value or {@code null} for none */ public java.lang.String getTuningOperation() { return tuningOperation; } /** * Output only. The tune operation associated with the model. Can be used to determine if there is * an ongoing tune for this recommendation. Empty field implies no tune is goig on. * @param tuningOperation tuningOperation or {@code null} for none */ public GoogleCloudRetailV2alphaModel setTuningOperation(java.lang.String tuningOperation) { this.tuningOperation = tuningOperation; return this; } /** * Required. The type of model e.g. `home-page`. Currently supported values: `recommended-for- * you`, `others-you-may-like`, `frequently-bought-together`, `page-optimization`, `similar- * items`, `buy-it-again`, `on-sale-items`, and `recently-viewed`(readonly value). This field * together with optimization_objective describe model metadata to use to control model training * and serving. See https://cloud.google.com/retail/docs/models for more details on what the model * metadata control and which combination of parameters are valid. For invalid combinations of * parameters (e.g. type = `frequently-bought-together` and optimization_objective = `ctr`), you * receive an error 400 if you try to create/update a recommendation with this set of knobs. * @return value or {@code null} for none */ public java.lang.String getType() { return type; } /** * Required. The type of model e.g. `home-page`. Currently supported values: `recommended-for- * you`, `others-you-may-like`, `frequently-bought-together`, `page-optimization`, `similar- * items`, `buy-it-again`, `on-sale-items`, and `recently-viewed`(readonly value). This field * together with optimization_objective describe model metadata to use to control model training * and serving. See https://cloud.google.com/retail/docs/models for more details on what the model * metadata control and which combination of parameters are valid. For invalid combinations of * parameters (e.g. type = `frequently-bought-together` and optimization_objective = `ctr`), you * receive an error 400 if you try to create/update a recommendation with this set of knobs. * @param type type or {@code null} for none */ public GoogleCloudRetailV2alphaModel setType(java.lang.String type) { this.type = type; return this; } /** * Output only. Timestamp the Recommendation Model was last updated. E.g. if a Recommendation * Model was paused - this would be the time the pause was initiated. * @return value or {@code null} for none */ public String getUpdateTime() { return updateTime; } /** * Output only. Timestamp the Recommendation Model was last updated. E.g. if a Recommendation * Model was paused - this would be the time the pause was initiated. * @param updateTime updateTime or {@code null} for none */ public GoogleCloudRetailV2alphaModel setUpdateTime(String updateTime) { this.updateTime = updateTime; return this; } @Override public GoogleCloudRetailV2alphaModel set(String fieldName, Object value) { return (GoogleCloudRetailV2alphaModel) super.set(fieldName, value); } @Override public GoogleCloudRetailV2alphaModel clone() { return (GoogleCloudRetailV2alphaModel) super.clone(); } }




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