/**
 * 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.
 */
import * as model from "../model";
/**
 * The generated embedded result to return.
 */
export interface EmbedTextResult {
    /**
     * A unique identifier for the generated result.
     */
    "id": string;
    /**
     * The original inputs. Only present if \"isEcho\" is set to true.
     */
    "inputs"?: Array<string>;
    /**
     * The original inputs. Only present if \"isEcho\" is set to true.
     */
    "embedContents"?: Array<model.EmbedContent>;
    /**
     * The embeddings corresponding to float.
     */
    "embeddings": Array<Array<number>>;
    /**
     * The embeddings corresponding to embedding types input.
     */
    "embeddingsByType"?: any;
    /**
     * The OCID of the model used in this inference request.
     */
    "modelId"?: string;
    /**
     * The version of the model.
     */
    "modelVersion"?: string;
    "usage"?: model.Usage;
}
export declare namespace EmbedTextResult {
    function getJsonObj(obj: EmbedTextResult): object;
    function getDeserializedJsonObj(obj: EmbedTextResult): object;
}