/**
 * Generative AI Service Inference API
 * OCI Generative AI is a fully managed service that provides a set of state-of-the-art, customizable large language models (LLMs) that cover a wide range of use cases for text generation, summarization, and text embeddings.

Use the Generative AI service inference API to access your custom model endpoints, or to try the out-of-the-box models to {@link #eNGenerative-ai-inferenceLatestChatResultChat(ENGenerative-ai-inferenceLatestChatResultChatRequest) eNGenerative-ai-inferenceLatestChatResultChat}, {@link #eNGenerative-ai-inferenceLatestGenerateTextResultGenerateText(ENGenerative-ai-inferenceLatestGenerateTextResultGenerateTextRequest) eNGenerative-ai-inferenceLatestGenerateTextResultGenerateText}, {@link #eNGenerative-ai-inferenceLatestSummarizeTextResultSummarizeText(ENGenerative-ai-inferenceLatestSummarizeTextResultSummarizeTextRequest) eNGenerative-ai-inferenceLatestSummarizeTextResultSummarizeText}, and {@link #eNGenerative-ai-inferenceLatestEmbedTextResultEmbedText(ENGenerative-ai-inferenceLatestEmbedTextResultEmbedTextRequest) eNGenerative-ai-inferenceLatestEmbedTextResultEmbedText}.

To use a Generative AI custom model for inference, you must first create an endpoint for that model. Use the {@link #eNGenerative-aiLatest(ENGenerative-aiLatestRequest) eNGenerative-aiLatest} to {@link #eNGenerative-aiLatestModel(ENGenerative-aiLatestModelRequest) eNGenerative-aiLatestModel} by fine-tuning an out-of-the-box model, or a previous version of a custom model, using your own data. Fine-tune the custom model on a {@link #eNGenerative-aiLatestDedicatedAiCluster(ENGenerative-aiLatestDedicatedAiClusterRequest) eNGenerative-aiLatestDedicatedAiCluster}. Then, create a {@link #eNGenerative-aiLatestDedicatedAiCluster(ENGenerative-aiLatestDedicatedAiClusterRequest) eNGenerative-aiLatestDedicatedAiCluster} with an {@link Endpoint} to host your custom model. For resource management in the Generative AI service, use the {@link #eNGenerative-aiLatest(ENGenerative-aiLatestRequest) eNGenerative-aiLatest}.

To learn more about the service, see the [Generative AI documentation](https://docs.oracle.com/iaas/Content/generative-ai/home.htm).

**Important:** The IP addresses behind each DNS endpoint might change over time. Always use the DNS hostname listed under the following **API Endpoints** section and avoid using hard-coded fixed IP addresses.

 * OpenAPI spec version: 20231130
 *
 *
 * NOTE: This class is auto generated by OracleSDKGenerator.
 * Do not edit the class manually.
 *
 * Copyright (c) 2020, 2026, Oracle and/or its affiliates.  All rights reserved.
 * This software is dual-licensed to you under the Universal Permissive License (UPL) 1.0 as shown at https://oss.oracle.com/licenses/upl or Apache License 2.0 as shown at http://www.apache.org/licenses/LICENSE-2.0. You may choose either license.
 */
/**
 * Breakdown of tokens used in a completion.
 */
export interface CompletionTokensDetails {
    /**
     * When using Predicted Outputs, the number of tokens in the prediction that appeared in the completion.
     *  Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
     */
    "acceptedPredictionTokens"?: number;
    /**
     * Tokens generated by the model for reasoning. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
     */
    "reasoningTokens"?: number;
    /**
     * When using Predicted Outputs, the number of tokens in the prediction that did not appear in the completion. However, like reasoning tokens, these tokens are still counted in the total completion tokens for purposes of billing, output, and context window limits. Note: Numbers greater than Number.MAX_SAFE_INTEGER will result in rounding issues.
     */
    "rejectedPredictionTokens"?: number;
}
export declare namespace CompletionTokensDetails {
    function getJsonObj(obj: CompletionTokensDetails): object;
    function getDeserializedJsonObj(obj: CompletionTokensDetails): object;
}