import asyncio import copy import traceback from typing import Type from openhands.controller.agent import Agent from openhands.controller.state.state import State, TrafficControlState from openhands.controller.stuck import StuckDetector from openhands.core.config import AgentConfig, LLMConfig from openhands.core.exceptions import ( LLMMalformedActionError, LLMNoActionError, LLMResponseError, ) from openhands.core.logger import openhands_logger as logger from openhands.core.schema import AgentState from openhands.events import EventSource, EventStream, EventStreamSubscriber from openhands.events.action import ( Action, ActionConfirmationStatus, AddTaskAction, AgentDelegateAction, AgentFinishAction, AgentRejectAction, ChangeAgentStateAction, CmdRunAction, IPythonRunCellAction, MessageAction, ModifyTaskAction, NullAction, ) from openhands.events.event import Event from openhands.events.observation import ( AgentDelegateObservation, AgentStateChangedObservation, CmdOutputObservation, ErrorObservation, Observation, ) from openhands.events.serialization.event import truncate_content from openhands.llm.llm import LLM from openhands.runtime.utils.shutdown_listener import should_continue # note: RESUME is only available on web GUI TRAFFIC_CONTROL_REMINDER = ( "Please click on resume button if you'd like to continue, or start a new task." ) class AgentController: id: str agent: Agent max_iterations: int event_stream: EventStream state: State confirmation_mode: bool agent_to_llm_config: dict[str, LLMConfig] agent_configs: dict[str, AgentConfig] agent_task: asyncio.Future | None = None parent: 'AgentController | None' = None delegate: 'AgentController | None' = None _pending_action: Action | None = None def __init__( self, agent: Agent, event_stream: EventStream, max_iterations: int, max_budget_per_task: float | None = None, agent_to_llm_config: dict[str, LLMConfig] | None = None, agent_configs: dict[str, AgentConfig] | None = None, sid: str = 'default', confirmation_mode: bool = False, initial_state: State | None = None, is_delegate: bool = False, headless_mode: bool = True, ): """Initializes a new instance of the AgentController class. Args: agent: The agent instance to control. event_stream: The event stream to publish events to. max_iterations: The maximum number of iterations the agent can run. max_budget_per_task: The maximum budget (in USD) allowed per task, beyond which the agent will stop. agent_to_llm_config: A dictionary mapping agent names to LLM configurations in the case that we delegate to a different agent. agent_configs: A dictionary mapping agent names to agent configurations in the case that we delegate to a different agent. sid: The session ID of the agent. initial_state: The initial state of the controller. is_delegate: Whether this controller is a delegate. headless_mode: Whether the agent is run in headless mode. """ self._step_lock = asyncio.Lock() self.id = sid self.agent = agent self.headless_mode = headless_mode # subscribe to the event stream self.event_stream = event_stream self.event_stream.subscribe( EventStreamSubscriber.AGENT_CONTROLLER, self.on_event, append=is_delegate ) # state from the previous session, state from a parent agent, or a fresh state self.set_initial_state( state=initial_state, max_iterations=max_iterations, confirmation_mode=confirmation_mode, ) self.max_budget_per_task = max_budget_per_task self.agent_to_llm_config = agent_to_llm_config if agent_to_llm_config else {} self.agent_configs = agent_configs if agent_configs else {} self._initial_max_iterations = max_iterations self._initial_max_budget_per_task = max_budget_per_task # stuck helper self._stuck_detector = StuckDetector(self.state) async def close(self): """Closes the agent controller, canceling any ongoing tasks and unsubscribing from the event stream.""" if self.agent_task is not None: self.agent_task.cancel() await self.set_agent_state_to(AgentState.STOPPED) self.event_stream.unsubscribe(EventStreamSubscriber.AGENT_CONTROLLER) def update_state_before_step(self): self.state.iteration += 1 self.state.local_iteration += 1 async def update_state_after_step(self): # update metrics especially for cost self.state.local_metrics = self.agent.llm.metrics if 'llm_completions' not in self.state.extra_data: self.state.extra_data['llm_completions'] = [] self.state.extra_data['llm_completions'].extend(self.agent.llm.llm_completions) self.agent.llm.llm_completions.clear() async def report_error(self, message: str, exception: Exception | None = None): """Reports an error to the user and sends the exception to the LLM next step, in the hope it can self-correct. This method should be called for a particular type of errors, which have: - a user-friendly message, which will be shown in the chat box. This should not be a raw exception message. - an ErrorObservation that can be sent to the LLM by the agent, with the exception message, so it can self-correct next time. """ self.state.last_error = message if exception: self.state.last_error += f': {exception}' self.event_stream.add_event(ErrorObservation(message), EventSource.AGENT) async def start_step_loop(self): """The main loop for the agent's step-by-step execution.""" logger.info(f'[Agent Controller {self.id}] Starting step loop...') while should_continue(): try: await self._step() except asyncio.CancelledError: logger.info('AgentController task was cancelled') break except Exception as e: traceback.print_exc() logger.error(f'Error while running the agent: {e}') logger.error(traceback.format_exc()) await self.report_error( 'There was an unexpected error while running the agent', exception=e ) await self.set_agent_state_to(AgentState.ERROR) break await asyncio.sleep(0.1) async def on_event(self, event: Event): """Callback from the event stream. Notifies the controller of incoming events. Args: event (Event): The incoming event to process. """ if isinstance(event, Action): await self._handle_action(event) elif isinstance(event, Observation): await self._handle_observation(event) async def _handle_action(self, action: Action): """Handles actions from the event stream. Args: action (Action): The action to handle. """ if isinstance(action, ChangeAgentStateAction): await self.set_agent_state_to(action.agent_state) # type: ignore elif isinstance(action, MessageAction): await self._handle_message_action(action) elif isinstance(action, AgentDelegateAction): await self.start_delegate(action) elif isinstance(action, AddTaskAction): self.state.root_task.add_subtask( action.parent, action.goal, action.subtasks ) elif isinstance(action, ModifyTaskAction): self.state.root_task.set_subtask_state(action.task_id, action.state) elif isinstance(action, AgentFinishAction): self.state.outputs = action.outputs self.state.metrics.merge(self.state.local_metrics) await self.set_agent_state_to(AgentState.FINISHED) elif isinstance(action, AgentRejectAction): self.state.outputs = action.outputs self.state.metrics.merge(self.state.local_metrics) await self.set_agent_state_to(AgentState.REJECTED) async def _handle_observation(self, observation: Observation): """Handles observation from the event stream. Args: observation (observation): The observation to handle. """ if ( self._pending_action and hasattr(self._pending_action, 'is_confirmed') and self._pending_action.is_confirmed == ActionConfirmationStatus.AWAITING_CONFIRMATION ): return # Make sure we print the observation in the same way as the LLM sees it observation_to_print = copy.deepcopy(observation) if len(observation_to_print.content) > self.agent.llm.config.max_message_chars: observation_to_print.content = truncate_content( observation_to_print.content, self.agent.llm.config.max_message_chars ) logger.info(observation_to_print, extra={'msg_type': 'OBSERVATION'}) if self._pending_action and self._pending_action.id == observation.cause: self._pending_action = None if self.state.agent_state == AgentState.USER_CONFIRMED: await self.set_agent_state_to(AgentState.RUNNING) if self.state.agent_state == AgentState.USER_REJECTED: await self.set_agent_state_to(AgentState.AWAITING_USER_INPUT) return if isinstance(observation, CmdOutputObservation): return elif isinstance(observation, AgentDelegateObservation): self.state.history.on_event(observation) elif isinstance(observation, ErrorObservation): if self.state.agent_state == AgentState.ERROR: self.state.metrics.merge(self.state.local_metrics) async def _handle_message_action(self, action: MessageAction): """Handles message actions from the event stream. Args: action (MessageAction): The message action to handle. """ if action.source == EventSource.USER: logger.info( action, extra={'msg_type': 'ACTION', 'event_source': EventSource.USER} ) if self.get_agent_state() != AgentState.RUNNING: await self.set_agent_state_to(AgentState.RUNNING) elif action.source == EventSource.AGENT and action.wait_for_response: await self.set_agent_state_to(AgentState.AWAITING_USER_INPUT) def reset_task(self): """Resets the agent's task.""" self.almost_stuck = 0 self.agent.reset() async def set_agent_state_to(self, new_state: AgentState): """Updates the agent's state and handles side effects. Can emit events to the event stream. Args: new_state (AgentState): The new state to set for the agent. """ logger.debug( f'[Agent Controller {self.id}] Setting agent({self.agent.name}) state from {self.state.agent_state} to {new_state}' ) if new_state == self.state.agent_state: return if new_state == AgentState.STOPPED or new_state == AgentState.ERROR: self.reset_task() elif ( new_state == AgentState.RUNNING and self.state.agent_state == AgentState.PAUSED and self.state.traffic_control_state == TrafficControlState.THROTTLING ): # user intends to interrupt traffic control and let the task resume temporarily self.state.traffic_control_state = TrafficControlState.PAUSED # User has chosen to deliberately continue - lets double the max iterations if ( self.state.iteration is not None and self.state.max_iterations is not None and self._initial_max_iterations is not None ): if self.state.iteration >= self.state.max_iterations: self.state.max_iterations += self._initial_max_iterations if ( self.state.metrics.accumulated_cost is not None and self.max_budget_per_task is not None and self._initial_max_budget_per_task is not None ): if self.state.metrics.accumulated_cost >= self.max_budget_per_task: self.max_budget_per_task += self._initial_max_budget_per_task elif self._pending_action is not None and ( new_state == AgentState.USER_CONFIRMED or new_state == AgentState.USER_REJECTED ): if hasattr(self._pending_action, 'thought'): self._pending_action.thought = '' # type: ignore[union-attr] if new_state == AgentState.USER_CONFIRMED: self._pending_action.is_confirmed = ActionConfirmationStatus.CONFIRMED # type: ignore[attr-defined] else: self._pending_action.is_confirmed = ActionConfirmationStatus.REJECTED # type: ignore[attr-defined] self.event_stream.add_event(self._pending_action, EventSource.AGENT) self.state.agent_state = new_state self.event_stream.add_event( AgentStateChangedObservation('', self.state.agent_state), EventSource.AGENT ) if new_state == AgentState.INIT and self.state.resume_state: await self.set_agent_state_to(self.state.resume_state) self.state.resume_state = None def get_agent_state(self): """Returns the current state of the agent. Returns: AgentState: The current state of the agent. """ return self.state.agent_state async def start_delegate(self, action: AgentDelegateAction): """Start a delegate agent to handle a subtask. OpenHands is a multi-agentic system. A `task` is a conversation between OpenHands (the whole system) and the user, which might involve one or more inputs from the user. It starts with an initial input (typically a task statement) from the user, and ends with either an `AgentFinishAction` initiated by the agent, a stop initiated by the user, or an error. A `subtask` is a conversation between an agent and the user, or another agent. If a `task` is conducted by a single agent, then it's also a `subtask`. Otherwise, a `task` consists of multiple `subtasks`, each executed by one agent. Args: action (AgentDelegateAction): The action containing information about the delegate agent to start. """ agent_cls: Type[Agent] = Agent.get_cls(action.agent) agent_config = self.agent_configs.get(action.agent, self.agent.config) llm_config = self.agent_to_llm_config.get(action.agent, self.agent.llm.config) llm = LLM(config=llm_config) delegate_agent = agent_cls(llm=llm, config=agent_config) state = State( inputs=action.inputs or {}, local_iteration=0, iteration=self.state.iteration, max_iterations=self.state.max_iterations, delegate_level=self.state.delegate_level + 1, # global metrics should be shared between parent and child metrics=self.state.metrics, ) logger.info( f'[Agent Controller {self.id}]: start delegate, creating agent {delegate_agent.name} using LLM {llm}' ) self.delegate = AgentController( sid=self.id + '-delegate', agent=delegate_agent, event_stream=self.event_stream, max_iterations=self.state.max_iterations, max_budget_per_task=self.max_budget_per_task, agent_to_llm_config=self.agent_to_llm_config, agent_configs=self.agent_configs, initial_state=state, is_delegate=True, headless_mode=self.headless_mode, ) await self.delegate.set_agent_state_to(AgentState.RUNNING) async def _step(self) -> None: """Executes a single step of the parent or delegate agent. Detects stuck agents and limits on the number of iterations and the task budget.""" if self.get_agent_state() != AgentState.RUNNING: await asyncio.sleep(1) return if self._pending_action: await asyncio.sleep(1) return if self.delegate is not None: assert self.delegate != self if self.delegate.get_agent_state() == AgentState.PAUSED: await asyncio.sleep(1) else: await self._delegate_step() return logger.info( f'{self.agent.name} LEVEL {self.state.delegate_level} LOCAL STEP {self.state.local_iteration} GLOBAL STEP {self.state.iteration}', extra={'msg_type': 'STEP'}, ) # check if agent hit the resources limit stop_step = False if self.state.iteration >= self.state.max_iterations: stop_step = await self._handle_traffic_control( 'iteration', self.state.iteration, self.state.max_iterations ) if self.max_budget_per_task is not None: current_cost = self.state.metrics.accumulated_cost if current_cost > self.max_budget_per_task: stop_step = await self._handle_traffic_control( 'budget', current_cost, self.max_budget_per_task ) if stop_step: return self.update_state_before_step() action: Action = NullAction() try: action = self.agent.step(self.state) if action is None: raise LLMNoActionError('No action was returned') except (LLMMalformedActionError, LLMNoActionError, LLMResponseError) as e: # report to the user # and send the underlying exception to the LLM for self-correction await self.report_error(str(e)) return if action.runnable: if self.state.confirmation_mode and ( type(action) is CmdRunAction or type(action) is IPythonRunCellAction ): action.is_confirmed = ActionConfirmationStatus.AWAITING_CONFIRMATION self._pending_action = action if not isinstance(action, NullAction): if ( hasattr(action, 'is_confirmed') and action.is_confirmed == ActionConfirmationStatus.AWAITING_CONFIRMATION ): await self.set_agent_state_to(AgentState.AWAITING_USER_CONFIRMATION) self.event_stream.add_event(action, EventSource.AGENT) await self.update_state_after_step() logger.info(action, extra={'msg_type': 'ACTION'}) if self._is_stuck(): await self.report_error('Agent got stuck in a loop') await self.set_agent_state_to(AgentState.ERROR) async def _delegate_step(self): """Executes a single step of the delegate agent.""" logger.debug(f'[Agent Controller {self.id}] Delegate not none, awaiting...') await self.delegate._step() # type: ignore[union-attr] logger.debug(f'[Agent Controller {self.id}] Delegate step done') assert self.delegate is not None delegate_state = self.delegate.get_agent_state() logger.debug(f'[Agent Controller {self.id}] Delegate state: {delegate_state}') if delegate_state == AgentState.ERROR: # update iteration that shall be shared across agents self.state.iteration = self.delegate.state.iteration # close the delegate upon error await self.delegate.close() self.delegate = None self.delegateAction = None await self.report_error('Delegator agent encountered an error') elif delegate_state in (AgentState.FINISHED, AgentState.REJECTED): logger.info( f'[Agent Controller {self.id}] Delegate agent has finished execution' ) # retrieve delegate result outputs = self.delegate.state.outputs if self.delegate.state else {} # update iteration that shall be shared across agents self.state.iteration = self.delegate.state.iteration # close delegate controller: we must close the delegate controller before adding new events await self.delegate.close() # update delegate result observation # TODO: replace this with AI-generated summary (#2395) formatted_output = ', '.join( f'{key}: {value}' for key, value in outputs.items() ) content = ( f'{self.delegate.agent.name} finishes task with {formatted_output}' ) obs: Observation = AgentDelegateObservation( outputs=outputs, content=content ) # clean up delegate status self.delegate = None self.delegateAction = None self.event_stream.add_event(obs, EventSource.AGENT) return async def _handle_traffic_control( self, limit_type: str, current_value: float, max_value: float ): """Handles agent state after hitting the traffic control limit. Args: limit_type (str): The type of limit that was hit. current_value (float): The current value of the limit. max_value (float): The maximum value of the limit. """ stop_step = False if self.state.traffic_control_state == TrafficControlState.PAUSED: logger.info('Hitting traffic control, temporarily resume upon user request') self.state.traffic_control_state = TrafficControlState.NORMAL else: self.state.traffic_control_state = TrafficControlState.THROTTLING if self.headless_mode: # set to ERROR state if running in headless mode # since user cannot resume on the web interface await self.report_error( f'Agent reached maximum {limit_type} in headless mode, task stopped. ' f'Current {limit_type}: {current_value:.2f}, max {limit_type}: {max_value:.2f}' ) await self.set_agent_state_to(AgentState.ERROR) else: await self.report_error( f'Agent reached maximum {limit_type}, task paused. ' f'Current {limit_type}: {current_value:.2f}, max {limit_type}: {max_value:.2f}. ' f'{TRAFFIC_CONTROL_REMINDER}' ) await self.set_agent_state_to(AgentState.PAUSED) stop_step = True return stop_step def get_state(self): """Returns the current running state object. Returns: State: The current state object. """ return self.state def set_initial_state( self, state: State | None, max_iterations: int, confirmation_mode: bool = False, ): """Sets the initial state for the agent, either from the previous session, or from a parent agent, or by creating a new one. Args: state: The state to initialize with, or None to create a new state. max_iterations: The maximum number of iterations allowed for the task. confirmation_mode: Whether to enable confirmation mode. """ # state from the previous session, state from a parent agent, or a new state # note that this is called twice when restoring a previous session, first with state=None if state is None: self.state = State( inputs={}, max_iterations=max_iterations, confirmation_mode=confirmation_mode, ) else: self.state = state # when restored from a previous session, the State object will have history, start_id, and end_id # connect it to the event stream self.state.history.set_event_stream(self.event_stream) # if start_id was not set in State, we're starting fresh, at the top of the stream start_id = self.state.start_id if start_id == -1: start_id = self.event_stream.get_latest_event_id() + 1 else: logger.debug(f'AgentController {self.id} restoring from event {start_id}') # make sure history is in sync self.state.start_id = start_id self.state.history.start_id = start_id # if there was an end_id saved in State, set it in history # currently not used, later useful for delegates if self.state.end_id > -1: self.state.history.end_id = self.state.end_id def _is_stuck(self): """Checks if the agent or its delegate is stuck in a loop. Returns: bool: True if the agent is stuck, False otherwise. """ # check if delegate stuck if self.delegate and self.delegate._is_stuck(): return True return self._stuck_detector.is_stuck() def __repr__(self): return ( f'AgentController(id={self.id}, agent={self.agent!r}, ' f'event_stream={self.event_stream!r}, ' f'state={self.state!r}, agent_task={self.agent_task!r}, ' f'delegate={self.delegate!r}, _pending_action={self._pending_action!r})' )