import { BaseChatModel, type BaseChatModelParams } from "@langchain/core/language_models/chat_models";
import { type BaseMessage } from "@langchain/core/messages";
import { type ChatResult } from "@langchain/core/outputs";
import { type CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
export type MoonshotMessageRole = "system" | "assistant" | "user";
interface MoonshotMessage {
    role: MoonshotMessageRole;
    content: string;
}
/**
 * Interface representing a request for a chat completion.
 *
 * See https://platform.moonshot.cn/docs/intro#%E6%A8%A1%E5%9E%8B%E5%88%97%E8%A1%A8
 */
type ModelName = (string & NonNullable<unknown>) | "moonshot-v1-8k" | "moonshot-v1-32k" | "moonshot-v1-128k";
interface ChatCompletionRequest {
    model: ModelName;
    messages?: MoonshotMessage[];
    stream?: boolean;
    max_tokens?: number | null;
    top_p?: number | null;
    temperature?: number | null;
    stop?: string[];
    presence_penalty?: number;
    frequency_penalty?: number;
    n?: number;
}
/**
 * Interface defining the input to the MoonshotChatInput class.
 */
export interface ChatMoonshotParams {
    /**
     * @default "moonshot-v1-8k"
     * Alias for `model`
     */
    modelName: ModelName;
    /**
     * @default "moonshot-v1-8k"
     */
    model: ModelName;
    /** Whether to stream the results or not. Defaults to false. */
    streaming?: boolean;
    /** Messages to pass as a prefix to the prompt */
    messages?: MoonshotMessage[];
    /**
     * API key to use when making requests. Defaults to the value of
     * `MOONSHOT_API_KEY` environment variable.
     */
    apiKey?: string;
    /**
     * Amount of randomness injected into the response. Ranges
     * from 0 to 1 (0 is not included). Use temp closer to 0 for analytical /
     * multiple choice, and temp closer to 1 for creative and generative tasks.
     * Defaults to 0, recommended 0.3
     */
    temperature?: number;
    /**
     * Total probability mass of tokens to consider at each step. Range
     * from 0 to 1. Defaults to 1
     */
    topP?: number;
    /**
     * Different models have different maximum values. For example, the maximum
     * value of moonshot-v1-8k is 8192. Defaults to 1024
     */
    maxTokens?: number;
    stop?: string[];
    /**
     * There is a penalty, a number between -2.0 and 2.0. Positive values
     * penalize the newly generated words based on whether they appear in the
     * text, increasing the likelihood that the model will discuss new topics.
     * The default value is 0
     */
    presencePenalty?: number;
    /**
     * Frequency penalty, a number between -2.0 and 2.0. Positive values
     * penalize the newly generated words based on their existing frequency in the
     * text, making the model less likely to repeat the same words verbatim.
     * The default value is 0
     */
    frequencyPenalty?: number;
    /**
     * The default value is 1 and cannot be greater than 5. In particular,
     * when temperature is very small and close to 0, we can only return 1 result.
     * If n is already set and > 1, Moonshot will return an invalid input parameter
     * (invalid_request_error).
     */
    n?: number;
}
export declare class ChatMoonshot extends BaseChatModel implements ChatMoonshotParams {
    static lc_name(): string;
    get callKeys(): string[];
    get lc_secrets(): {
        apiKey: string;
    };
    get lc_aliases(): undefined;
    apiKey?: string;
    streaming: boolean;
    messages?: MoonshotMessage[];
    modelName: ChatCompletionRequest["model"];
    model: ChatCompletionRequest["model"];
    apiUrl: string;
    maxTokens?: number | undefined;
    temperature?: number | undefined;
    topP?: number | undefined;
    stop?: string[];
    presencePenalty?: number;
    frequencyPenalty?: number;
    n?: number;
    constructor(fields?: Partial<ChatMoonshotParams> & BaseChatModelParams);
    /**
     * Get the parameters used to invoke the model
     */
    invocationParams(): Omit<ChatCompletionRequest, "messages">;
    /**
     * Get the identifying parameters for the model
     */
    identifyingParams(): Omit<ChatCompletionRequest, "messages">;
    /** @ignore */
    _generate(messages: BaseMessage[], options?: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): Promise<ChatResult>;
    /** @ignore */
    completionWithRetry(request: ChatCompletionRequest, stream: boolean, signal?: AbortSignal, onmessage?: (event: MessageEvent) => void): Promise<any>;
    _llmType(): string;
    /** @ignore */
    _combineLLMOutput(): never[];
}
export {};