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Building applications with LLMs through composability in Kotlin

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/**
 *
 * Please note:
 * This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
 * Do not edit this file manually.
 *
 */

@file:Suppress(
    "ArrayInDataClass",
    "EnumEntryName",
    "RemoveRedundantQualifierName",
    "UnusedImport"
)

package com.xebia.functional.openai.generated.model




import kotlinx.serialization.Serializable
import kotlinx.serialization.SerialName
import kotlinx.serialization.Contextual
import kotlin.js.JsName
import kotlinx.serialization.json.*

/**
* Represents an embedding vector returned by embedding endpoint. 
*
    * @param index The index of the embedding in the list of embeddings.
    * @param embedding The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](/docs/guides/embeddings). 
    * @param `object` The object type, which is always \"embedding\".
*/
@Serializable


data class Embedding (
        /* The index of the embedding in the list of embeddings. */
    @SerialName(value = "index") val index: kotlin.Int,
        /* The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](/docs/guides/embeddings).  */
    @SerialName(value = "embedding") val embedding: kotlin.collections.List<@Contextual kotlin.Double>,
        /* The object type, which is always \"embedding\". */
    @SerialName(value = "object") val `object`: Embedding.`Object`
) {

            /**
            * The object type, which is always \"embedding\".
            *
            * Values: embedding
            */
            @Serializable
            enum class `Object`(val value: kotlin.String) {
                @SerialName(value = "embedding") embedding("embedding");
                }
}