/**
 * Author: Srilal S. Siriwardhane
 * Email: SrilalS@99x.io
**/
import { AbstractLLMInferenceEngine } from "./AbstractLLMInferenceEngine.js";
import { AvailableModels } from "../types/AvailableModels.js";
import { ChatMessage } from "../types/ChatMessages.js";
import { TextGenerationOutput, TextGenerationPipeline } from '@huggingface/transformers';
import { Model } from "../types/Model.js";
import { LLMStatus } from "../types/LLMStatus.js";
/**
 * TransformerJSModel
 * This type is extended by the `Model` Enum to enforce the model type.
 */
type TransformerJSModel = Model | 'llama' | 'llama32' | 'gemma' | 'tinymistral';
/**
 * TransformerJSInferenceEngine class to handle the LLM Inference using the TransformerJS.
 * This class extends the LLMInferenceFactory to enforce the methods.
 */
export declare class TransformerJSInferenceEngine extends AbstractLLMInferenceEngine {
    private status;
    private statusEmitter;
    private localModelsMode;
    llmModel: TransformerJSModel;
    engine: TextGenerationPipeline;
    /**
     * constructor
     * @param model - The model to be used for inference. should be one of allowed models.
     * Allowed Models: 'llama', 'gemma', 'tinyllama'
     * This list of models will be updated as more models are added in the future releases.
     *
     * the `env.remoteHost` and `env.remotePathTemplate` can be used to set the
     * remote host and the path template.
     *
     * the commented out code can be used to set the local model repos.
    **/
    constructor(model: TransformerJSModel);
    static init(model: TransformerJSModel, localMode?: boolean): Promise<TransformerJSInferenceEngine>;
    createEngine(): Promise<void>;
    availableModels: AvailableModels;
    runChatInference(chat: ChatMessage[]): Promise<ChatMessage[]>;
    /**
     * processChatOutput
     * @param chatOutput - The output from the chat inference.
     * @returns Promise<ChatMessage[]>
     *
     * This function is used to process the chat output and return the ChatMessage[].
     * All the models have different output formats, so this function is used to process the output.
     * If the variation between the models is too high, then this function will be
     * Moved to a separate class and will be extended by the main class.
     * @throws Error - If the chatOutput is not in the expected format.
     * */
    protected processChatOutput(chatOutput: TextGenerationOutput): Promise<ChatMessage[]>;
    runCompletionInference(prompt: string): Promise<string>;
    progressCallback(progress: any): void;
    /**
     * getModel
     * @returns string
     *
     * This function is used to get the model name from the available models.
     *
     * @throws Error - If the model is not found or not supported.
     * */
    protected getModel(): string;
    /**
     * onStatusChange
     * @param listener - The listener to be used for status change.
     *
     * This function is used to listen to the status change of the inference.
     *
     */
    onStatusChange(listener: (status: LLMStatus) => void): void;
}
export {};