import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { LLM, type BaseLLMParams } from "@langchain/core/language_models/llms";
import { GenerationChunk } from "@langchain/core/outputs";
/**
 * Interface defining the parameters for configuring the Hugging Face
 * model for text generation.
 */
export interface HFInput {
    /** Model to use */
    model: string;
    /** Custom inference endpoint URL to use */
    endpointUrl?: string;
    /** Sampling temperature to use */
    temperature?: number;
    /**
     * Maximum number of tokens to generate in the completion.
     */
    maxTokens?: number;
    /**
     * The model will stop generating text when one of the strings in the list is generated.
     */
    stopSequences?: string[];
    /** Total probability mass of tokens to consider at each step */
    topP?: number;
    /** Integer to define the top tokens considered within the sample operation to create new text. */
    topK?: number;
    /** Penalizes repeated tokens according to frequency */
    frequencyPenalty?: number;
    /** API key to use. */
    apiKey?: string;
    /**
     * Credentials to use for the request. If this is a string, it will be passed straight on. If it's a boolean, true will be "include" and false will not send credentials at all.
     */
    includeCredentials?: string | boolean;
}
/**
 * Class implementing the Large Language Model (LLM) interface using the
 * Hugging Face Inference API for text generation.
 * @example
 * ```typescript
 * const model = new HuggingFaceInference({
 *   model: "gpt2",
 *   temperature: 0.7,
 *   maxTokens: 50,
 * });
 *
 * const res = await model.invoke(
 *   "Question: What would be a good company name for a company that makes colorful socks?\nAnswer:"
 * );
 * console.log({ res });
 * ```
 */
export declare class HuggingFaceInference extends LLM implements HFInput {
    lc_serializable: boolean;
    get lc_secrets(): {
        [key: string]: string;
    } | undefined;
    model: string;
    temperature: number | undefined;
    maxTokens: number | undefined;
    stopSequences: string[] | undefined;
    topP: number | undefined;
    topK: number | undefined;
    frequencyPenalty: number | undefined;
    apiKey: string | undefined;
    endpointUrl: string | undefined;
    includeCredentials: string | boolean | undefined;
    constructor(fields?: Partial<HFInput> & BaseLLMParams);
    _llmType(): string;
    invocationParams(options?: this["ParsedCallOptions"]): {
        model: string;
        parameters: {
            return_full_text: boolean;
            temperature: number | undefined;
            max_new_tokens: number | undefined;
            stop: string[] | undefined;
            top_p: number | undefined;
            top_k: number | undefined;
            repetition_penalty: number | undefined;
        };
    };
    _streamResponseChunks(prompt: string, options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<GenerationChunk>;
    /** @ignore */
    _call(prompt: string, options: this["ParsedCallOptions"]): Promise<string>;
    /** @ignore */
    private _prepareHFInference;
    /** @ignore */
    static imports(): Promise<{
        HfInference: typeof import("@huggingface/inference").HfInference;
    }>;
}