def execute(
    self, request: str, instantiated_plan: List[Dict[str, Any]]
) -> Tuple[List[Dict[str, Any]], Dict[str, str]]:
    """
    Execute the execute flow: Execute the task and save the result.
    :param request: Original request to be executed.
    :param instantiated_plan: Instantiated plan containing steps to execute.
    :return: Tuple containing task quality flag, comment, and task type.
    """

    start_time = time.time()
    try:
        executed_plan = self.execute_plan(instantiated_plan)
    except Exception as error:
        raise RuntimeError(f"Execution failed. {error}")
    finally:
        self.execution_time = round(time.time() - start_time, 3)

    start_time = time.time()
    try:
        result, _ = self.eval_agent.evaluate(
            request=request, log_path=self.log_path
        )
        utils.print_with_color(f"Result: {result}", "green")
    except Exception as error:
        raise RuntimeError(f"Evaluation failed. {error}")
    finally:
        self.eval_time = round(time.time() - start_time, 3)

    return executed_plan, result

def execute_action(self) -> None:
    """
    Execute the action.
    """

    control_selected = None
    # Find the matching window and control.
    self.application_window = self._app_env.find_matching_window(
        self._task_file_name
    )
    if self.control_text == "":
        control_selected = self.application_window
    else:
        self._control_label, control_selected = self._app_env.find_matching_controller(
            self.filtered_annotation_dict, self.control_text
            )
        if control_selected:
            self._matched_control = control_selected.window_text()

    if not control_selected:
        # If the control is not found, raise an error.
        raise RuntimeError(f"Control with text '{self.control_text}' not found.")

    try:
        # Get the selected control item from the annotation dictionary and LLM response.
        # The LLM response is a number index corresponding to the key in the annotation dictionary.
        if control_selected:

            if _ufo_configs.get("SHOW_VISUAL_OUTLINE_ON_SCREEN", True):
                control_selected.draw_outline(colour="red", thickness=3)
                time.sleep(_ufo_configs.get("RECTANGLE_TIME", 0))

            control_coordinates = PhotographerDecorator.coordinate_adjusted(
                self.application_window.rectangle(), control_selected.rectangle()
            )

            self._control_log = {
                "control_class": control_selected.element_info.class_name,
                "control_type": control_selected.element_info.control_type,
                "control_automation_id": control_selected.element_info.automation_id,
                "control_friendly_class_name": control_selected.friendly_class_name(),
                "control_coordinates": {
                    "left": control_coordinates[0],
                    "top": control_coordinates[1],
                    "right": control_coordinates[2],
                    "bottom": control_coordinates[3],
                },
            }

            self.app_agent.Puppeteer.receiver_manager.create_ui_control_receiver(
                control_selected, self.application_window
            )

            # Save the screenshot of the tagged selected control.
            self.capture_control_screenshot(control_selected)

            self._results = self.app_agent.Puppeteer.execute_command(
                self._operation, self._args
            )
            self.control_reannotate = None
            if not utils.is_json_serializable(self._results):
                self._results = ""

                return

    except Exception:
        self.general_error_handler()

def execute_plan(
    self, instantiated_plan: List[Dict[str, Any]]
) -> List[Dict[str, Any]]:
    """
    Get the executed result from the execute agent.
    :param instantiated_plan: Plan containing steps to execute.
    :return: List of executed steps.
    """

    # Initialize the step counter and capture the initial screenshot.
    self.session_step = 0
    try:
        time.sleep(1)
        # Initialize the API receiver
        self.app_agent.Puppeteer.receiver_manager.create_api_receiver(
            self.app_agent._app_root_name, self.app_agent._process_name
        )
        # Initialize the control receiver
        current_receiver = self.app_agent.Puppeteer.receiver_manager.receiver_list[
            -1
        ]

        if current_receiver is not None:
            self.application_window = self._app_env.find_matching_window(
                self._task_file_name
            )
            current_receiver.com_object = (
                current_receiver.get_object_from_process_name()
            )

        self.init_and_final_capture_screenshot()
    except Exception as error:
        raise RuntimeError(f"Execution initialization failed. {error}")

    # Initialize the success flag for each step.
    for index, step_plan in enumerate(instantiated_plan):
        instantiated_plan[index]["Success"] = None
        instantiated_plan[index]["MatchedControlText"] = None

    for index, step_plan in enumerate(instantiated_plan):
        try:
            self.session_step += 1

            # Check if the maximum steps have been exceeded.
            if self.session_step > _configs["MAX_STEPS"]:
                raise RuntimeError("Maximum steps exceeded.")

            self._parse_step_plan(step_plan)

            try:
                self.process()
                instantiated_plan[index]["Success"] = True
                instantiated_plan[index]["ControlLabel"] = self._control_label
                instantiated_plan[index][
                    "MatchedControlText"
                ] = self._matched_control
            except Exception as ControllerNotFoundError:
                instantiated_plan[index]["Success"] = False
                raise ControllerNotFoundError

        except Exception as error:
            err_info = RuntimeError(
                f"Step {self.session_step} execution failed. {error}"
            )
            raise err_info
    # capture the final screenshot
    self.session_step += 1
    time.sleep(1)
    self.init_and_final_capture_screenshot()
    # save the final state of the app

    win_com_receiver = None
    for receiver in reversed(
        self.app_agent.Puppeteer.receiver_manager.receiver_list
    ):
        if isinstance(receiver, WinCOMReceiverBasic):
            if receiver.client is not None:
                win_com_receiver = receiver
                break

    if win_com_receiver is not None:
        win_com_receiver.save()
        time.sleep(1)
        win_com_receiver.client.Quit()

    print("Execution complete.")

    return instantiated_plan

def general_error_handler(self) -> None:
    """
    Handle general errors.
    """

    pass

def init_and_final_capture_screenshot(self) -> None:
    """
    Capture the screenshot.
    """

    # Define the paths for the screenshots saved.
    screenshot_save_path = self.log_path + f"action_step{self.session_step}.png"

    self._memory_data.add_values_from_dict(
        {
            "CleanScreenshot": screenshot_save_path,
        }
    )

    self.photographer.capture_app_window_screenshot(
        self.application_window, save_path=screenshot_save_path
    )
    # Capture the control screenshot.
    control_selected = self._app_env.app_window
    self.capture_control_screenshot(control_selected)

def log_save(self) -> None:
    """
    Log the constructed prompt message for the PrefillAgent.
    """

    step_memory = {
        "Step": self.session_step,
        "Subtask": self.subtask,
        "ControlLabel": self._control_label,
        "ControlText": self.control_text,
        "Action": self.action,
        "ActionType": self.app_agent.Puppeteer.get_command_types(self._operation),
        "Results": self._results,
        "Application": self.app_agent._app_root_name,
        "TimeCost": self.time_cost,
    }
    self._memory_data.add_values_from_dict(step_memory)
    self.log(self._memory_data.to_dict())

def print_step_info(self) -> None:
    """
    Print the step information.
    """

    utils.print_with_color(
        "Step {step}: {subtask}".format(
            step=self.session_step,
            subtask=self.subtask,
        ),
        "magenta",
    )

def process(self) -> None:
    """
    Process the current step.
    """

    step_start_time = time.time()
    self.print_step_info()
    self.capture_screenshot()
    self.execute_action()
    self.time_cost = round(time.time() - step_start_time, 3)
    self.log_save()

def get_prompter(
    self,
    is_visual: bool,
    prompt_template: str,
    example_prompt_template: str,
    api_prompt_template: str,
    root_name: Optional[str] = None,
) -> ExecuteEvalAgentPrompter:
    """
    Get the prompter for the agent.
    :param is_visual: The flag indicating whether the agent is visual or not.
    :param prompt_template: The prompt template.
    :param example_prompt_template: The example prompt template.
    :param api_prompt_template: The API prompt template.
    :param root_name: The name of the root.
    :return: The prompter.
    """

    return ExecuteEvalAgentPrompter(
        is_visual=is_visual,
        prompt_template=prompt_template,
        example_prompt_template=example_prompt_template,
        api_prompt_template=api_prompt_template,
        root_name=root_name,
    )