com.pulumi.googlenative.retail.v2alpha.kotlin.ModelArgs.kt Maven / Gradle / Ivy

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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
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@file:Suppress("NAME_SHADOWING", "DEPRECATION")

package com.pulumi.googlenative.retail.v2alpha.kotlin

import com.pulumi.core.Output
import com.pulumi.core.Output.of
import com.pulumi.googlenative.retail.v2alpha.ModelArgs.builder
import com.pulumi.googlenative.retail.v2alpha.kotlin.enums.ModelFilteringOption
import com.pulumi.googlenative.retail.v2alpha.kotlin.enums.ModelPeriodicTuningState
import com.pulumi.googlenative.retail.v2alpha.kotlin.enums.ModelTrainingState
import com.pulumi.googlenative.retail.v2alpha.kotlin.inputs.GoogleCloudRetailV2alphaModelModelFeaturesConfigArgs
import com.pulumi.googlenative.retail.v2alpha.kotlin.inputs.GoogleCloudRetailV2alphaModelModelFeaturesConfigArgsBuilder
import com.pulumi.googlenative.retail.v2alpha.kotlin.inputs.GoogleCloudRetailV2alphaModelPageOptimizationConfigArgs
import com.pulumi.googlenative.retail.v2alpha.kotlin.inputs.GoogleCloudRetailV2alphaModelPageOptimizationConfigArgsBuilder
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiTagMarker
import com.pulumi.kotlin.applySuspend
import kotlin.Boolean
import kotlin.String
import kotlin.Suppress
import kotlin.Unit
import kotlin.jvm.JvmName

/**
 * Creates a new model.
 * @property catalogId
 * @property displayName 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.
 * @property dryRun Optional. Whether to run a dry run to validate the request (without actually creating the model).
 * @property filteringOption Optional. If `RECOMMENDATIONS_FILTERING_ENABLED`, recommendation filtering by attributes is enabled for the model.
 * @property location
 * @property modelFeaturesConfig Optional. Additional model features config.
 * @property name 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.
 * @property 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.
 * @property pageOptimizationConfig Optional. The page optimization config.
 * @property 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`.
 * @property project
 * @property 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.
 * @property type 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.
 */
public data class ModelArgs(
    public val catalogId: Output? = null,
    public val displayName: Output? = null,
    public val dryRun: Output? = null,
    public val filteringOption: Output? = null,
    public val location: Output? = null,
    public val modelFeaturesConfig: Output? =
        null,
    public val name: Output? = null,
    public val optimizationObjective: Output? = null,
    public val pageOptimizationConfig: Output? = null,
    public val periodicTuningState: Output? = null,
    public val project: Output? = null,
    public val trainingState: Output? = null,
    public val type: Output? = null,
) : ConvertibleToJava {
    override fun toJava(): com.pulumi.googlenative.retail.v2alpha.ModelArgs =
        com.pulumi.googlenative.retail.v2alpha.ModelArgs.builder()
            .catalogId(catalogId?.applyValue({ args0 -> args0 }))
            .displayName(displayName?.applyValue({ args0 -> args0 }))
            .dryRun(dryRun?.applyValue({ args0 -> args0 }))
            .filteringOption(filteringOption?.applyValue({ args0 -> args0.let({ args0 -> args0.toJava() }) }))
            .location(location?.applyValue({ args0 -> args0 }))
            .modelFeaturesConfig(
                modelFeaturesConfig?.applyValue({ args0 ->
                    args0.let({ args0 ->
                        args0.toJava()
                    })
                }),
            )
            .name(name?.applyValue({ args0 -> args0 }))
            .optimizationObjective(optimizationObjective?.applyValue({ args0 -> args0 }))
            .pageOptimizationConfig(
                pageOptimizationConfig?.applyValue({ args0 ->
                    args0.let({ args0 ->
                        args0.toJava()
                    })
                }),
            )
            .periodicTuningState(
                periodicTuningState?.applyValue({ args0 ->
                    args0.let({ args0 ->
                        args0.toJava()
                    })
                }),
            )
            .project(project?.applyValue({ args0 -> args0 }))
            .trainingState(trainingState?.applyValue({ args0 -> args0.let({ args0 -> args0.toJava() }) }))
            .type(type?.applyValue({ args0 -> args0 })).build()
}

/**
 * Builder for [ModelArgs].
 */
@PulumiTagMarker
public class ModelArgsBuilder internal constructor() {
    private var catalogId: Output? = null

    private var displayName: Output? = null

    private var dryRun: Output? = null

    private var filteringOption: Output? = null

    private var location: Output? = null

    private var modelFeaturesConfig: Output? =
        null

    private var name: Output? = null

    private var optimizationObjective: Output? = null

    private var pageOptimizationConfig:
        Output? = null

    private var periodicTuningState: Output? = null

    private var project: Output? = null

    private var trainingState: Output? = null

    private var type: Output? = null

    /**
     * @param value
     */
    @JvmName("tckouvwifdyrxkbo")
    public suspend fun catalogId(`value`: Output) {
        this.catalogId = value
    }

    /**
     * @param value 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.
     */
    @JvmName("xafywfhyvbnlpwfp")
    public suspend fun displayName(`value`: Output) {
        this.displayName = value
    }

    /**
     * @param value Optional. Whether to run a dry run to validate the request (without actually creating the model).
     */
    @JvmName("mrppsiwijseryfxm")
    public suspend fun dryRun(`value`: Output) {
        this.dryRun = value
    }

    /**
     * @param value Optional. If `RECOMMENDATIONS_FILTERING_ENABLED`, recommendation filtering by attributes is enabled for the model.
     */
    @JvmName("avaefgnjtupotsam")
    public suspend fun filteringOption(`value`: Output) {
        this.filteringOption = value
    }

    /**
     * @param value
     */
    @JvmName("rdvxcaiaomvvdevm")
    public suspend fun location(`value`: Output) {
        this.location = value
    }

    /**
     * @param value Optional. Additional model features config.
     */
    @JvmName("luiqqbrwfomccnqp")
    public suspend fun modelFeaturesConfig(`value`: Output) {
        this.modelFeaturesConfig = value
    }

    /**
     * @param value 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.
     */
    @JvmName("ckbdwinvkfxsvaiw")
    public suspend fun name(`value`: Output) {
        this.name = value
    }

    /**
     * @param value 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.
     */
    @JvmName("thcpwvjdlefvjals")
    public suspend fun optimizationObjective(`value`: Output) {
        this.optimizationObjective = value
    }

    /**
     * @param value Optional. The page optimization config.
     */
    @JvmName("dsvhlfaasrygaypn")
    public suspend fun pageOptimizationConfig(`value`: Output) {
        this.pageOptimizationConfig = value
    }

    /**
     * @param value 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`.
     */
    @JvmName("myndbnosppykfcwy")
    public suspend fun periodicTuningState(`value`: Output) {
        this.periodicTuningState = value
    }

    /**
     * @param value
     */
    @JvmName("unipccbotnjdsxkb")
    public suspend fun project(`value`: Output) {
        this.project = value
    }

    /**
     * @param value 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.
     */
    @JvmName("xorhfmbgmyolrmbi")
    public suspend fun trainingState(`value`: Output) {
        this.trainingState = value
    }

    /**
     * @param value 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.
     */
    @JvmName("ftbhhadghtucqbit")
    public suspend fun type(`value`: Output) {
        this.type = value
    }

    /**
     * @param value
     */
    @JvmName("nyhapdgvnsjyvvcx")
    public suspend fun catalogId(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.catalogId = mapped
    }

    /**
     * @param value 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.
     */
    @JvmName("bgayuwmsourfapux")
    public suspend fun displayName(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.displayName = mapped
    }

    /**
     * @param value Optional. Whether to run a dry run to validate the request (without actually creating the model).
     */
    @JvmName("lxnqhurjvpddxcje")
    public suspend fun dryRun(`value`: Boolean?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.dryRun = mapped
    }

    /**
     * @param value Optional. If `RECOMMENDATIONS_FILTERING_ENABLED`, recommendation filtering by attributes is enabled for the model.
     */
    @JvmName("cmfghvitfxiltvuy")
    public suspend fun filteringOption(`value`: ModelFilteringOption?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.filteringOption = mapped
    }

    /**
     * @param value
     */
    @JvmName("ertakncpheycytqi")
    public suspend fun location(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.location = mapped
    }

    /**
     * @param value Optional. Additional model features config.
     */
    @JvmName("jxwarvmykitvhile")
    public suspend fun modelFeaturesConfig(`value`: GoogleCloudRetailV2alphaModelModelFeaturesConfigArgs?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.modelFeaturesConfig = mapped
    }

    /**
     * @param argument Optional. Additional model features config.
     */
    @JvmName("mlxhnobojoxuekkg")
    public suspend fun modelFeaturesConfig(argument: suspend GoogleCloudRetailV2alphaModelModelFeaturesConfigArgsBuilder.() -> Unit) {
        val toBeMapped = GoogleCloudRetailV2alphaModelModelFeaturesConfigArgsBuilder().applySuspend {
            argument()
        }.build()
        val mapped = of(toBeMapped)
        this.modelFeaturesConfig = mapped
    }

    /**
     * @param value 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.
     */
    @JvmName("sjhnbifyvoyonten")
    public suspend fun name(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.name = mapped
    }

    /**
     * @param value 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.
     */
    @JvmName("yykupqttawfxgfdh")
    public suspend fun optimizationObjective(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.optimizationObjective = mapped
    }

    /**
     * @param value Optional. The page optimization config.
     */
    @JvmName("jukohdxbqoxtdnyf")
    public suspend fun pageOptimizationConfig(`value`: GoogleCloudRetailV2alphaModelPageOptimizationConfigArgs?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.pageOptimizationConfig = mapped
    }

    /**
     * @param argument Optional. The page optimization config.
     */
    @JvmName("dbwnjfrxalaqchrt")
    public suspend fun pageOptimizationConfig(argument: suspend GoogleCloudRetailV2alphaModelPageOptimizationConfigArgsBuilder.() -> Unit) {
        val toBeMapped = GoogleCloudRetailV2alphaModelPageOptimizationConfigArgsBuilder().applySuspend {
            argument()
        }.build()
        val mapped = of(toBeMapped)
        this.pageOptimizationConfig = mapped
    }

    /**
     * @param value 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`.
     */
    @JvmName("uremrpjxkhoaffra")
    public suspend fun periodicTuningState(`value`: ModelPeriodicTuningState?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.periodicTuningState = mapped
    }

    /**
     * @param value
     */
    @JvmName("qftambrnvskxdhkm")
    public suspend fun project(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.project = mapped
    }

    /**
     * @param value 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.
     */
    @JvmName("cdkqojjodqoweurg")
    public suspend fun trainingState(`value`: ModelTrainingState?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.trainingState = mapped
    }

    /**
     * @param value 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.
     */
    @JvmName("mwwfxtfxdqjiygrg")
    public suspend fun type(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.type = mapped
    }

    internal fun build(): ModelArgs = ModelArgs(
        catalogId = catalogId,
        displayName = displayName,
        dryRun = dryRun,
        filteringOption = filteringOption,
        location = location,
        modelFeaturesConfig = modelFeaturesConfig,
        name = name,
        optimizationObjective = optimizationObjective,
        pageOptimizationConfig = pageOptimizationConfig,
        periodicTuningState = periodicTuningState,
        project = project,
        trainingState = trainingState,
        type = type,
    )
}