/**
 * Cursor Agent Service Client
 *
 * Implements the AgentService API for chat functionality.
 * Uses the BidiSse pattern:
 * - RunSSE (server-streaming) to receive responses
 * - BidiAppend (unary) to send client messages
 *
 * Proto structure:
 * AgentClientMessage:
 *   field 1: run_request (AgentRunRequest)
 *   field 2: exec_client_message (ExecClientMessage)
 *   field 3: kv_client_message (KvClientMessage)
 *   field 4: conversation_action (ConversationAction)
 *   field 5: exec_client_control_message
 *   field 6: interaction_response
 *
 * AgentServerMessage:
 *   field 1: interaction_update (InteractionUpdate)
 *   field 2: exec_server_message (ExecServerMessage)
 *   field 3: conversation_checkpoint_update (completion signal)
 *   field 4: kv_server_message (KvServerMessage)
 *   field 5: exec_server_control_message
 *   field 7: interaction_query
 *
 * InteractionUpdate.message:
 *   field 1: text_delta
 *   field 4: thinking_delta
 *   field 8: token_delta
 *   field 13: heartbeat
 *   field 14: turn_ended
 */
import { AgentMode } from "./proto";
import type { OpenAIToolDefinition, McpExecRequest, ExecRequest, AgentServiceOptions, AgentChatRequest, ToolCallInfo, AgentStreamChunk as AgentStreamChunkType } from "./proto/types";
export { AgentMode };
export type AgentStreamChunk = AgentStreamChunkType;
export type { ExecRequest, McpExecRequest, ToolCallInfo, OpenAIToolDefinition };
export declare const CURSOR_API_URL = "https://api2.cursor.sh";
export declare const AGENT_PRIVACY_URL = "https://agent.api5.cursor.sh";
export declare const AGENT_NON_PRIVACY_URL = "https://agentn.api5.cursor.sh";
export declare class AgentServiceClient {
    private baseUrl;
    private accessToken;
    private workspacePath;
    private blobStore;
    private currentRequestId;
    private currentAppendSeqno;
    private pendingAssistantBlobs;
    constructor(accessToken: string, options?: AgentServiceOptions);
    private getHeaders;
    private blobIdToKey;
    /**
     * Build the AgentClientMessage for a chat request
     */
    private buildChatMessage;
    /**
     * Call BidiAppend to send a client message
     */
    private bidiAppend;
    private handleKvMessage;
    /**
     * Send a tool result back to the server (for MCP tools only)
     * This must be called during an active chat stream when an exec_request chunk is received
     */
    sendToolResult(execRequest: McpExecRequest & {
        type: 'mcp';
    }, result: {
        success?: {
            content: string;
            isError?: boolean;
        };
        error?: string;
    }): Promise<void>;
    /**
     * Send a shell execution result back to the server
     */
    sendShellResult(id: number, execId: string | undefined, command: string, cwd: string, stdout: string, stderr: string, exitCode: number, executionTimeMs?: number): Promise<void>;
    /**
     * Send an LS result back to the server
     */
    sendLsResult(id: number, execId: string | undefined, filesString: string): Promise<void>;
    /**
     * Send a request context result back to the server
     */
    sendRequestContextResult(id: number, execId: string | undefined): Promise<void>;
    /**
     * Send a file read result back to the server
     */
    sendReadResult(id: number, execId: string | undefined, content: string, path: string, totalLines?: number, fileSize?: bigint, truncated?: boolean): Promise<void>;
    /**
     * Send a grep/glob result back to the server
     */
    sendGrepResult(id: number, execId: string | undefined, pattern: string, path: string, files: string[]): Promise<void>;
    /**
     * Send a file write result back to the server
     */
    sendWriteResult(id: number, execId: string | undefined, result: {
        success?: {
            path: string;
            linesCreated: number;
            fileSize: number;
            fileContentAfterWrite?: string;
        };
        error?: {
            path: string;
            error: string;
        };
    }): Promise<void>;
    /**
     * Send a ResumeAction to signal the server to continue after tool results
     * Based on Cursor CLI analysis: after sending tool results, send ConversationAction with resume_action
     * to tell the server to resume streaming instead of storing responses in KV blobs
     */
    sendResumeAction(): Promise<void>;
    /**
     * Send a streaming chat request using BidiSse pattern
     */
    chatStream(request: AgentChatRequest): AsyncGenerator<AgentStreamChunkType>;
    /**
     * Send a non-streaming chat request (collects all chunks)
     */
    chat(request: AgentChatRequest): Promise<string>;
}
/**
 * Create an Agent Service client
 */
export declare function createAgentServiceClient(accessToken: string, options?: AgentServiceOptions): AgentServiceClient;