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Building applications with LLMs through composability in Kotlin

There is a newer version: 0.0.5-alpha.118

/**
 *
 * 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 com.xebia.functional.openai.generated.model.CreateEmbeddingRequestInput
import com.xebia.functional.openai.generated.model.CreateEmbeddingRequestModel



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

/**
* 
*
    * @param input 
    * @param model 
    * @param encodingFormat The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).
    * @param dimensions The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models. 
    * @param user A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids). 
*/
@Serializable


data class CreateEmbeddingRequest (
        @SerialName(value = "input") val input: CreateEmbeddingRequestInput,
        @SerialName(value = "model") val model: CreateEmbeddingRequestModel,
        /* The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/). */
    @SerialName(value = "encoding_format") val encodingFormat: CreateEmbeddingRequest.EncodingFormat? = EncodingFormat.float,
        /* The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.  */
    @SerialName(value = "dimensions") val dimensions: kotlin.Int? = null,
        /* A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).  */
    @SerialName(value = "user") val user: kotlin.String? = null
) {

            /**
            * The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).
            *
            * Values: float,base64
            */
            @Serializable
            enum class EncodingFormat(val value: kotlin.String) {
                @SerialName(value = "float") float("float"),
                @SerialName(value = "base64") base64("base64");
                }
}