async def do_async(task: Task, model: ModelNames | None = None, client: Any = None, debug: bool = False, retry: int = 3):
        """
        Execute a direct LLM call with the given task and model asynchronously.
        
        Args:
            task: The task to execute
            model: The LLM model to use (default: "openai/gpt-4")
            client: Optional custom client to use instead of creating a new one
            debug: Whether to enable debug mode
            retry: Number of retries for failed calls (default: 3)
            
        Returns:
            The response from the LLM
        """
        global latest_upsonic_client
        from ..latest_upsonic_client import latest_upsonic_client

        # Use provided client or get/create one
        if client is not None:
            the_client = client
        else:
            the_client = get_or_create_client(debug=debug)
        
        # Register tools if needed
        the_client = register_tools(the_client, task.tools)

        # Execute the direct call asynchronously with retry parameter
        await the_client.call_async(task, model, retry=retry)
        
        # Print the price ID summary if the task has a price ID
        if not task.not_main_task:
            print_price_id_summary(task.price_id, task)
            
        return task.response

        Execute a direct LLM call with the given task and model asynchronously.
        
        Args:
            task: The task to execute
            model: The LLM model to use (default: "openai/gpt-4")
            client: Optional custom client to use instead of creating a new one
            debug: Whether to enable debug mode
            retry: Number of retries for failed calls (default: 3)
            
        Returns:
            The response from the LLM
        
src/upsonic/client/direct_llm_call/direct_llm_cal.py