commonMain.aws.sdk.kotlin.services.neptunegraph.model.VectorSearchConfiguration.kt Maven / Gradle / Ivy

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// Code generated by smithy-kotlin-codegen. DO NOT EDIT!

package aws.sdk.kotlin.services.neptunegraph.model

import aws.smithy.kotlin.runtime.SdkDsl

/**
 * Specifies the number of dimensions for vector embeddings loaded into the graph. Max = 65535
 */
public class VectorSearchConfiguration private constructor(builder: Builder) {
    /**
     * The number of dimensions.
     */
    public val dimension: kotlin.Int = requireNotNull(builder.dimension) { "A non-null value must be provided for dimension" }

    public companion object {
        public operator fun invoke(block: Builder.() -> kotlin.Unit): aws.sdk.kotlin.services.neptunegraph.model.VectorSearchConfiguration = Builder().apply(block).build()
    }

    override fun toString(): kotlin.String = buildString {
        append("VectorSearchConfiguration(")
        append("dimension=$dimension")
        append(")")
    }

    override fun hashCode(): kotlin.Int {
        var result = dimension
        return result
    }

    override fun equals(other: kotlin.Any?): kotlin.Boolean {
        if (this === other) return true
        if (other == null || this::class != other::class) return false

        other as VectorSearchConfiguration

        if (dimension != other.dimension) return false

        return true
    }

    public inline fun copy(block: Builder.() -> kotlin.Unit = {}): aws.sdk.kotlin.services.neptunegraph.model.VectorSearchConfiguration = Builder(this).apply(block).build()

    @SdkDsl
    public class Builder {
        /**
         * The number of dimensions.
         */
        public var dimension: kotlin.Int? = null

        @PublishedApi
        internal constructor()
        @PublishedApi
        internal constructor(x: aws.sdk.kotlin.services.neptunegraph.model.VectorSearchConfiguration) : this() {
            this.dimension = x.dimension
        }

        @PublishedApi
        internal fun build(): aws.sdk.kotlin.services.neptunegraph.model.VectorSearchConfiguration = VectorSearchConfiguration(this)

        internal fun correctErrors(): Builder {
            if (dimension == null) dimension = 0
            return this
        }
    }
}