commonMain.com.xebia.functional.openai.generated.model.CreateChatCompletionFunctionResponseChoicesInner.kt Maven / Gradle / Ivy

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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 com.xebia.functional.openai.generated.model.ChatCompletionResponseMessage



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

/**
* 
*
    * @param finishReason The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, `length` if the maximum number of tokens specified in the request was reached, `content_filter` if content was omitted due to a flag from our content filters, or `function_call` if the model called a function. 
    * @param index The index of the choice in the list of choices.
    * @param message 
*/
@Serializable


data class CreateChatCompletionFunctionResponseChoicesInner (
        /* The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, `length` if the maximum number of tokens specified in the request was reached, `content_filter` if content was omitted due to a flag from our content filters, or `function_call` if the model called a function.  */
    @SerialName(value = "finish_reason") val finishReason: CreateChatCompletionFunctionResponseChoicesInner.FinishReason,
        /* The index of the choice in the list of choices. */
    @SerialName(value = "index") val index: kotlin.Int,
        @SerialName(value = "message") val message: ChatCompletionResponseMessage
) {

            /**
            * The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, `length` if the maximum number of tokens specified in the request was reached, `content_filter` if content was omitted due to a flag from our content filters, or `function_call` if the model called a function. 
            *
            * Values: stop,length,function_call,content_filter
            */
            @Serializable
            enum class FinishReason(val value: kotlin.String) {
                @SerialName(value = "stop") stop("stop"),
                @SerialName(value = "length") @JsName("length_type") length("length"),
                @SerialName(value = "function_call") function_call("function_call"),
                @SerialName(value = "content_filter") content_filter("content_filter");
                }
}