import type { BaseLanguageModelCallOptions } from "@langchain/core/language_models/base";
import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import { GenerationChunk } from "@langchain/core/outputs";
import { BaseLLMParams, LLM } from "@langchain/core/language_models/llms";
export interface AILanguageModelFactory {
    create(options?: AILanguageModelCreateOptions): Promise<AILanguageModel>;
    capabilities(): Promise<AILanguageModelCapabilities>;
}
export interface AILanguageModel extends EventTarget {
    prompt(input: AILanguageModelPromptInput, options?: AILanguageModelPromptOptions): Promise<string>;
    promptStreaming(input: AILanguageModelPromptInput, options?: AILanguageModelPromptOptions): ReadableStream;
    countPromptTokens(input: AILanguageModelPromptInput, options?: AILanguageModelPromptOptions): Promise<number>;
    get maxTokens(): number;
    get tokensSoFar(): number;
    get tokensLeft(): number;
    get topK(): number;
    get temperature(): number;
    oncontextoverflow: (event: Event) => void;
    clone(options?: AILanguageModelCloneOptions): Promise<AILanguageModel>;
    destroy(): void;
}
interface AILanguageModelCapabilities {
    readonly available: AICapabilityAvailability;
    languageAvailable(languageTag: string): AICapabilityAvailability;
    get defaultTopK(): number | undefined;
    get maxTopK(): number | undefined;
    get defaultTemperature(): number | undefined;
    get maxTemperature(): number | undefined;
}
interface AILanguageModelCreateOptions {
    signal?: AbortSignal;
    monitor?: AICreateMonitorCallback;
    systemPrompt?: string;
    initialPrompts?: AILanguageModelInitialPrompt[];
    topK: number;
    temperature: number;
}
export interface AILanguageModelInitialPrompt {
    role: AILanguageModelInitialPromptRole;
    content: string;
}
export interface AILanguageModelPrompt {
    role: AILanguageModelPromptRole;
    content: string;
}
export interface AILanguageModelPromptOptions {
    signal?: AbortSignal;
}
export interface AILanguageModelCloneOptions {
    signal?: AbortSignal;
}
export type AILanguageModelPromptInput = string | AILanguageModelPrompt | AILanguageModelPrompt[];
declare enum AILanguageModelInitialPromptRole {
    "system" = 0,
    "user" = 1,
    "assistant" = 2
}
declare enum AILanguageModelPromptRole {
    "user" = 0,
    "assistant" = 1
}
export type AICapabilityAvailability = "yes" | "no";
export type AICreateMonitorCallback = () => void;
export interface ChromeAIInputs extends BaseLLMParams {
    topK?: number;
    temperature?: number;
    systemPrompt?: string;
}
export interface ChromeAICallOptions extends BaseLanguageModelCallOptions {
}
/**
 * To use this model you need to have the `Built-in AI Early Preview Program`
 * for Chrome. You can find more information about the program here:
 * @link https://developer.chrome.com/docs/ai/built-in
 *
 * @example
 * ```typescript
 * // Initialize the ChromeAI model.
 * const model = new ChromeAI({
 *   temperature: 0.5, // Optional. Default is 0.5.
 *   topK: 40, // Optional. Default is 40.
 * });
 *
 * // Call the model with a message and await the response.
 * const response = await model.invoke([
 *   new HumanMessage({ content: "My name is John." }),
 * ]);
 * ```
 */
export declare class ChromeAI extends LLM<ChromeAICallOptions> {
    temperature?: number;
    topK?: number;
    systemPrompt?: string;
    static lc_name(): string;
    constructor(inputs?: ChromeAIInputs);
    _llmType(): string;
    /**
     * Initialize the model. This method may be called before invoking the model
     * to set up a chat session in advance.
     */
    protected createSession(): Promise<any>;
    _streamResponseChunks(prompt: string, _options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<GenerationChunk>;
    _call(prompt: string, options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): Promise<string>;
}
export {};