import { ConversationConfig } from "./ConversationConfig.js";
import { Message } from "./Message.js";
import { ConversationModel } from "../schemas/conversation.schema.js";
import { ConversationRequestOptions } from "./ConversationRequestOptions.js";
import { ConversationHistory } from "./ConversationHistory.js";
import { ConversationCallableFunctions } from "./ConversationCallableFunctions.js";
import { ConversationRequestOptionsModel } from "schemas/conversationRequestOptions.schema.js";
import { ChatCompletionService } from "./ChatCompletionService.js";
import { ConversationGlobalPlugins, ConversationOptions, PluginsFromConversationOptionsWithGlobalPlugins, PromptOptions } from "../utils/types/index.js";
import { ConversationPlugins } from "./ConversationPlugins.js";
/**
 * A Conversation manages the messages sent to and from the OpenAI API and handles the logic for providing the message history to the API for each prompt.
 */
export declare class Conversation<TOptions extends ConversationOptions = ConversationOptions> {
    /**
     * Plugins that will be used for all conversations.
     *
     * @remarks
     * Only applies to conversations created after this property is set. Previous conversations will not be affected.
     *
     * @example
     * For TypeScript users, you can achieve type-safe global plugins by overriding the `ConversationGlobalPluginsOverride` interface.
     * ```ts
     * const globalPlugins = [somePlugin, someOtherPlugin];
     *
     * declare module "gpt-turbo" {
     *     interface ConversationGlobalPluginsOverride {
     *         globalPlugins: typeof globalPlugins;
     *     }
     * }
     *
     * Conversation.globalPlugins = globalPlugins;
     * ```
     */
    static globalPlugins: ConversationGlobalPlugins;
    /**
     * A UUID generated by the library for this conversation. Not the same as the conversation ID returned by the OpenAI API.
     */
    id: string;
    readonly config: ConversationConfig;
    readonly requestOptions: ConversationRequestOptions;
    readonly history: ConversationHistory;
    readonly callableFunctions: ConversationCallableFunctions;
    readonly plugins: ConversationPlugins<PluginsFromConversationOptionsWithGlobalPlugins<TOptions>>;
    private readonly chatCompletionService;
    private readonly pluginService;
    /**
     * Creates a new Conversation instance.
     *
     * @param options The options for the Conversation instance's configuration, request options, history, and callable functions.
     */
    constructor(options?: TOptions);
    /**
     * Creates a new Conversation instance from a JSON object.
     *
     * @param json The JSON object of the Conversation instance.
     * @param plugins The plugins to use for the Conversation instance.
     * @returns The new Conversation instance.
     */
    static fromJSON(json: ConversationModel, plugins?: ConversationOptions["plugins"]): Conversation<ConversationOptions>;
    /**
     * Serializes the `Conversation` to JSON.
     *
     * @returns A JSON representation of the `Conversation` instance.
     */
    toJSON(): ConversationModel;
    /**
     * This is the **recommended** way to interact with the GPT model. It's a wrapper method around other public methods that handles the logic of adding a user message, sending a request to the OpenAI API, and adding the assistant's response.
     *
     * @param prompt The prompt to send to the assistant.
     * @param options Additional options to pass to the Create Chat Completion API endpoint. This overrides the config passed to the constructor.
     * @param requestOptions Additional options to pass for the HTTP request. This overrides the config passed to the constructor.
     * @returns The assistant's response as a [`Message`](./Message.js) instance.
     */
    prompt(prompt: string, options?: PromptOptions, requestOptions?: ConversationRequestOptionsModel): Promise<Message>;
    /**
     * Removes all messages starting from (but excluding) the `fromMessage` if it's a user message, or its previous user message if `fromMessage` is an assistant message.
     * Then, the `prompt` method is called using either the specified `newPrompt` or the previous user message's content.
     *
     * This is useful if you want to edit a previous user message (by specifying `newPrompt`) or if you want to regenerate the response to a previous user message (by not specifying `newPrompt`).
     *
     * @param fromMessageOrId The message to re-prompt from. This can be either a message ID or a [`Message`](./Message.js) instance.
     * @param newPrompt The new prompt to use for the previous user message. If not provided, the previous user's message content will be reused.
     * @param options Additional options to pass to the Create Chat Completion API endpoint. This overrides the config passed to the constructor.
     * @param requestOptions Additional options to pass for the HTTP request. This overrides the config passed to the constructor.
     * @returns The assistant's response as a [`Message`](./Message.js) instance.
     *
     * @example
     * ```typescript
     * let assistantRes1 = await conversation.prompt("Hello!"); // Hi
     * let assistantRes2 = await conversation.prompt("How are you?"); // I'm good, how are you?
     *
     * // Regenerate the assistantRes2 response
     * assistantRes2 = await conversation.reprompt(assistantRes2); // Good! What about you?
     *
     * // Edit the initial prompt (and remove all messages after it. In this case, assistantRes2's response)
     * assistantRes1 = await conversation.reprompt(assistantRes1, "Goodbye!"); // See you later!
     * ```
     */
    reprompt(fromMessageOrId: string | Message, newPrompt?: string, options?: PromptOptions, requestOptions?: ConversationRequestOptionsModel): Promise<Message>;
    /**
     * Sends the result of a user-evaluated function call to the GPT model and gets the assistant's response.
     * This method should usually be called after receiving a function_call message from the assistant (using `getChatCompletionResponse()` or `prompt()`) and evaluating your own function with the provided arguments from that message.
     *
     * @param name The name of the function used to generate the result. This function must be defined in the `functions` config option.
     * @param result The result of the function call. If the result is anything other than a string, it will be JSON stringified. Since `result` can be anything, the `T` generic is provided for your typing convenience, but is not used internally
     * @param options Additional options to pass to the Create Chat Completion API endpoint. This overrides the config passed to the constructor.
     * @param requestOptions Additional options to pass for the HTTP request. This overrides the config passed to the constructor.
     * @returns The assistant's response as a [`Message`](./Message.js) instance.
     */
    functionPrompt<T = any>(name: string, result: T, options?: PromptOptions, requestOptions?: ConversationRequestOptionsModel): Promise<Message>;
    /**
     * Sends a Create Chat Completion request to the OpenAI API using the current messages stored in the conversation's history.
     *
     * @remarks
     * This method is solely provided for client code that wants to trigger a Create Chat Completion request manually.
     * It is not used internally by the library and does not moderate messages before sending them to the API.
     *
     * @param options Additional options to pass to the Create Chat Completion API endpoint. This overrides the config passed to the constructor.
     * @param requestOptions Additional options to pass for the HTTP request. This overrides the config passed to the constructor.
     * @returns A new [`Message`](./Message.js) instance with the role of "assistant" and the content set to the response from the OpenAI API. If the `stream` config option was set to `true`, the content will be progressively updated as the response is streamed from the API. Listen to the returned message's `onUpdate` event to get the updated content.
     */
    getChatCompletionResponse(...args: Parameters<ChatCompletionService["getChatCompletionResponse"]>): Promise<Message>;
}