import { VercelAiClientConfigureProps } from '../llm/vercelai-client';
export interface AssistantClass {
    configure(config: VercelAiClientConfigureProps & {
        chatEndpoint?: string;
        voiceEndpoint?: string;
    }): void;
    getInstance(): Promise<any>;
    registerTool(props: {
        name: string;
        tool: unknown;
        component?: unknown;
    }): void;
    addToolResult?(toolCallId: string, additionalData: unknown): void;
    testConnection?(apiKey: string, model: string): Promise<boolean>;
    getBaseURL?(): string | void;
}
/**
 * Returns the appropriate Assistant model based on the provider. (Internal use)
 *
 * @example
 *  ```tsx
 * import { GetAssistantModelByProvider } from '@openassistant/core';
 *
 * const AssistantModel = await GetAssistantModelByProvider({
 *   provider: 'openai',
 * });
 *
 * // configure the assistant model
 * AssistantModel.configure({
 *   apiKey: 'your-api-key',
 *   model: 'gpt-4o',
 * });
 *
 * // initialize the assistant model
 * const assistant = await AssistantModel.getInstance();
 *
 * // send a message to the assistant
 * const result = await assistant.processTextMessage({
 *   text: 'Hello, world!',
 * });
 * ```
 *
 * @param {Object} options - The options object
 * @param {string} [options.provider] - The name of the AI provider. The supported providers are: 'openai', 'anthropic', 'google', 'deepseek', 'xai', 'ollama', 'bedrock'
 * @param {string} [options.chatEndpoint] - The chat endpoint that handles the chat requests, e.g. '/api/chat'. This is required for server-side support.
 * @returns {Promise<AssistantClass>} Promise that resolves to the assistant model class.
 */
export declare function GetAssistantModelByProvider({ provider, chatEndpoint, }: {
    provider?: string;
    chatEndpoint?: string;
}): Promise<AssistantClass>;