com.pulumi.awsnative.bedrock.kotlin.inputs.KnowledgeBaseRdsFieldMappingArgs.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.awsnative.bedrock.kotlin.inputs

import com.pulumi.awsnative.bedrock.inputs.KnowledgeBaseRdsFieldMappingArgs.builder
import com.pulumi.core.Output
import com.pulumi.core.Output.of
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiNullFieldException
import com.pulumi.kotlin.PulumiTagMarker
import kotlin.String
import kotlin.Suppress
import kotlin.jvm.JvmName

/**
 * Contains the names of the fields to which to map information about the vector store.
 * @property metadataField The name of the field in which Amazon Bedrock stores metadata about the vector store.
 * @property primaryKeyField The name of the field in which Amazon Bedrock stores the ID for each entry.
 * @property textField The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
 * @property vectorField The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
 */
public data class KnowledgeBaseRdsFieldMappingArgs(
    public val metadataField: Output,
    public val primaryKeyField: Output,
    public val textField: Output,
    public val vectorField: Output,
) : ConvertibleToJava {
    override fun toJava(): com.pulumi.awsnative.bedrock.inputs.KnowledgeBaseRdsFieldMappingArgs =
        com.pulumi.awsnative.bedrock.inputs.KnowledgeBaseRdsFieldMappingArgs.builder()
            .metadataField(metadataField.applyValue({ args0 -> args0 }))
            .primaryKeyField(primaryKeyField.applyValue({ args0 -> args0 }))
            .textField(textField.applyValue({ args0 -> args0 }))
            .vectorField(vectorField.applyValue({ args0 -> args0 })).build()
}

/**
 * Builder for [KnowledgeBaseRdsFieldMappingArgs].
 */
@PulumiTagMarker
public class KnowledgeBaseRdsFieldMappingArgsBuilder internal constructor() {
    private var metadataField: Output? = null

    private var primaryKeyField: Output? = null

    private var textField: Output? = null

    private var vectorField: Output? = null

    /**
     * @param value The name of the field in which Amazon Bedrock stores metadata about the vector store.
     */
    @JvmName("rfpisupbnnreyvcq")
    public suspend fun metadataField(`value`: Output) {
        this.metadataField = value
    }

    /**
     * @param value The name of the field in which Amazon Bedrock stores the ID for each entry.
     */
    @JvmName("gxghabyhtdnjnipa")
    public suspend fun primaryKeyField(`value`: Output) {
        this.primaryKeyField = value
    }

    /**
     * @param value The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
     */
    @JvmName("vgniinrxwvmgepfg")
    public suspend fun textField(`value`: Output) {
        this.textField = value
    }

    /**
     * @param value The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
     */
    @JvmName("gumyooiavpvqifwr")
    public suspend fun vectorField(`value`: Output) {
        this.vectorField = value
    }

    /**
     * @param value The name of the field in which Amazon Bedrock stores metadata about the vector store.
     */
    @JvmName("jururyhceftpxbcl")
    public suspend fun metadataField(`value`: String) {
        val toBeMapped = value
        val mapped = toBeMapped.let({ args0 -> of(args0) })
        this.metadataField = mapped
    }

    /**
     * @param value The name of the field in which Amazon Bedrock stores the ID for each entry.
     */
    @JvmName("whvktngoyeygcshr")
    public suspend fun primaryKeyField(`value`: String) {
        val toBeMapped = value
        val mapped = toBeMapped.let({ args0 -> of(args0) })
        this.primaryKeyField = mapped
    }

    /**
     * @param value The name of the field in which Amazon Bedrock stores the raw text from your data. The text is split according to the chunking strategy you choose.
     */
    @JvmName("oqvnnwolsnraebek")
    public suspend fun textField(`value`: String) {
        val toBeMapped = value
        val mapped = toBeMapped.let({ args0 -> of(args0) })
        this.textField = mapped
    }

    /**
     * @param value The name of the field in which Amazon Bedrock stores the vector embeddings for your data sources.
     */
    @JvmName("vukgyjnitauhvsgy")
    public suspend fun vectorField(`value`: String) {
        val toBeMapped = value
        val mapped = toBeMapped.let({ args0 -> of(args0) })
        this.vectorField = mapped
    }

    internal fun build(): KnowledgeBaseRdsFieldMappingArgs = KnowledgeBaseRdsFieldMappingArgs(
        metadataField = metadataField ?: throw PulumiNullFieldException("metadataField"),
        primaryKeyField = primaryKeyField ?: throw PulumiNullFieldException("primaryKeyField"),
        textField = textField ?: throw PulumiNullFieldException("textField"),
        vectorField = vectorField ?: throw PulumiNullFieldException("vectorField"),
    )
}