google-native.retail/v2beta.getModel

func LookupModel(ctx *Context, args *LookupModelArgs, opts ...InvokeOption) (*LookupModelResult, error)
func LookupModelOutput(ctx *Context, args *LookupModelOutputArgs, opts ...InvokeOption) LookupModelResultOutput

> Note: This function is named LookupModel in the Go SDK.

CatalogId string

Location string

ModelId string

Project string

CatalogId string

Location string

ModelId string

Project string

catalogId String

location String

modelId String

project String

catalogId string

location string

modelId string

project string

catalog_id str

location str

model_id str

project str

catalogId String

location String

modelId String

project String

CreateTime string

Timestamp the Recommendation Model was created at.

DataState string

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.

DisplayName string

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.

FilteringOption string

Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.

LastTuneTime string

The timestamp when the latest successful tune finished.

ModelFeaturesConfig Pulumi.GoogleNative.Retail.V2Beta.Outputs.GoogleCloudRetailV2betaModelModelFeaturesConfigResponse

Optional. Additional model features config.

Name string

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.

OptimizationObjective string

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.

PeriodicTuningState string

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.

ServingConfigLists List<Pulumi.GoogleNative.Retail.V2Beta.Outputs.GoogleCloudRetailV2betaModelServingConfigListResponse>

The list of valid serving configs associated with the PageOptimizationConfig.

ServingState string

The serving state of the model: ACTIVE, NOT_ACTIVE.

TrainingState string

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.

TuningOperation string

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.

Type string

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.

UpdateTime string

Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.

CreateTime string

Timestamp the Recommendation Model was created at.

DataState string

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.

DisplayName string

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.

FilteringOption string

Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.

LastTuneTime string

The timestamp when the latest successful tune finished.

ModelFeaturesConfig GoogleCloudRetailV2betaModelModelFeaturesConfigResponse

Optional. Additional model features config.

Name string

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.

OptimizationObjective string

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.

PeriodicTuningState string

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.

ServingConfigLists []GoogleCloudRetailV2betaModelServingConfigListResponse

The list of valid serving configs associated with the PageOptimizationConfig.

ServingState string

The serving state of the model: ACTIVE, NOT_ACTIVE.

TrainingState string

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.

TuningOperation string

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.

Type string

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.

UpdateTime string

Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.

createTime String

Timestamp the Recommendation Model was created at.

dataState String

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.

displayName String

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.

filteringOption String

Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.

lastTuneTime String

The timestamp when the latest successful tune finished.

modelFeaturesConfig GoogleCloudRetailV2betaModelModelFeaturesConfigResponse

Optional. Additional model features config.

name String

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.

optimizationObjective String

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.

periodicTuningState String

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.

servingConfigLists List<GoogleCloudRetailV2betaModelServingConfigListResponse>

The list of valid serving configs associated with the PageOptimizationConfig.

servingState String

The serving state of the model: ACTIVE, NOT_ACTIVE.

trainingState String

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.

tuningOperation String

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.

type String

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.

updateTime String

Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.

createTime string

Timestamp the Recommendation Model was created at.

dataState string

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.

displayName string

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.

filteringOption string

Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.

lastTuneTime string

The timestamp when the latest successful tune finished.

modelFeaturesConfig GoogleCloudRetailV2betaModelModelFeaturesConfigResponse

Optional. Additional model features config.

name string

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.

optimizationObjective string

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.

periodicTuningState string

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.

servingConfigLists GoogleCloudRetailV2betaModelServingConfigListResponse[]

The list of valid serving configs associated with the PageOptimizationConfig.

servingState string

The serving state of the model: ACTIVE, NOT_ACTIVE.

trainingState string

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.

tuningOperation string

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.

type string

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.

updateTime string

Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.

create_time str

Timestamp the Recommendation Model was created at.

data_state str

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.

display_name str

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.

filtering_option str

Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.

last_tune_time str

The timestamp when the latest successful tune finished.

model_features_config GoogleCloudRetailV2betaModelModelFeaturesConfigResponse

Optional. Additional model features config.

name str

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.

optimization_objective str

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.

periodic_tuning_state str

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.

serving_config_lists Sequence[GoogleCloudRetailV2betaModelServingConfigListResponse]

The list of valid serving configs associated with the PageOptimizationConfig.

serving_state str

The serving state of the model: ACTIVE, NOT_ACTIVE.

training_state str

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.

tuning_operation str

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.

type str

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.

update_time str

Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.

createTime String

Timestamp the Recommendation Model was created at.

dataState String

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.

displayName String

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.

filteringOption String

Optional. If RECOMMENDATIONS_FILTERING_ENABLED, recommendation filtering by attributes is enabled for the model.

lastTuneTime String

The timestamp when the latest successful tune finished.

modelFeaturesConfig Property Map

Optional. Additional model features config.

name String

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.

optimizationObjective String

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.

periodicTuningState String

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.

servingConfigLists List<Property Map>

The list of valid serving configs associated with the PageOptimizationConfig.

servingState String

The serving state of the model: ACTIVE, NOT_ACTIVE.

trainingState String

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.

tuningOperation String

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.

type String

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.

updateTime String

Timestamp the Recommendation Model was last updated. E.g. if a Recommendation Model was paused - this would be the time the pause was initiated.

ContextProductsType string

Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

ContextProductsType string

Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

contextProductsType String

Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

contextProductsType string

Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

context_products_type str

Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

contextProductsType String

Optional. Specifies the context of the model when it is used in predict requests. Can only be set for the frequently-bought-together type. If it isn't specified, it defaults to MULTIPLE_CONTEXT_PRODUCTS.

FrequentlyBoughtTogetherConfig Pulumi.GoogleNative.Retail.V2Beta.Inputs.GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigResponse

Additional configs for frequently-bought-together models.

FrequentlyBoughtTogetherConfig GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigResponse

Additional configs for frequently-bought-together models.

frequentlyBoughtTogetherConfig GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigResponse

Additional configs for frequently-bought-together models.

frequentlyBoughtTogetherConfig GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigResponse

Additional configs for frequently-bought-together models.

frequently_bought_together_config GoogleCloudRetailV2betaModelFrequentlyBoughtTogetherFeaturesConfigResponse

Additional configs for frequently-bought-together models.

frequentlyBoughtTogetherConfig Property Map

Additional configs for frequently-bought-together models.

ServingConfigIds List<string>

Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.

ServingConfigIds []string

Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.

servingConfigIds List<String>

Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.

servingConfigIds string[]

Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.

serving_config_ids Sequence[str]

Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.

servingConfigIds List<String>

Optional. A set of valid serving configs that may be used for PAGE_OPTIMIZATION.