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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");
}
}