import asyncio import copy import traceback from typing import Callable, ClassVar, Type import litellm 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, ErrorObservation, NullObservation, 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 filter_out: ClassVar[tuple[type[Event], ...]] = ( NullAction, NullObservation, ChangeAgentStateAction, AgentStateChangedObservation, ) 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, status_callback: Callable | None = None, ): """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, self.id ) # 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) self.status_callback = status_callback async def close(self): """Closes the agent controller, canceling any ongoing tasks and unsubscribing from the event stream. Note that it's fairly important that this closes properly, otherwise the state is incomplete.""" await self.set_agent_state_to(AgentState.STOPPED) # we made history, now is the time to rewrite it! # the final state.history will be used by external scripts like evals, tests, etc. # history will need to be complete WITH delegates events # like the regular agent history, it does not include: # - 'hidden' events, events with hidden=True # - backend events (the default 'filtered out' types, types in self.filter_out) start_id = self.state.start_id if self.state.start_id >= 0 else 0 end_id = ( self.state.end_id if self.state.end_id >= 0 else self.event_stream.get_latest_event_id() ) self.state.history = list( self.event_stream.get_events( start_id=start_id, end_id=end_id, reverse=False, filter_out_type=self.filter_out, filter_hidden=True, ) ) # unsubscribe from the event stream self.event_stream.unsubscribe(EventStreamSubscriber.AGENT_CONTROLLER, self.id) def log(self, level: str, message: str, extra: dict | None = None): """Logs a message to the agent controller's logger. Args: message (str): The message to log. """ message = f'[Agent Controller {self.id}] {message}' getattr(logger, level)(message, extra=extra, stacklevel=2) 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. Use deepcopy to avoid it being modified by agent.reset() self.state.local_metrics = copy.deepcopy(self.agent.llm.metrics) async def _react_to_exception( self, e: Exception, ): await self.set_agent_state_to(AgentState.ERROR) if self.status_callback is not None: err_id = '' if isinstance(e, litellm.AuthenticationError): err_id = 'STATUS$ERROR_LLM_AUTHENTICATION' self.status_callback('error', err_id, str(e)) async def start_step_loop(self): """The main loop for the agent's step-by-step execution.""" self.log('info', 'Starting step loop...') while should_continue(): try: await self._step() except asyncio.CancelledError: self.log('debug', 'AgentController task was cancelled') break except Exception as e: traceback.print_exc() self.log('error', f'Error while running the agent: {e}') await self._react_to_exception(e) 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 hasattr(event, 'hidden') and event.hidden: return # if the event is not filtered out, add it to the history if not any(isinstance(event, filter_type) for filter_type in self.filter_out): self.state.history.append(event) 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. """ 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 ) self.log('debug', str(observation_to_print), extra={'msg_type': 'OBSERVATION'}) if observation.llm_metrics is not None: self.agent.llm.metrics.merge(observation.llm_metrics) 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 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: self.log( 'debug', str(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. """ self.log( 'info', f'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 in (AgentState.STOPPED, 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 in (AgentState.USER_CONFIRMED, AgentState.USER_REJECTED) ): if hasattr(self._pending_action, 'thought'): self._pending_action.thought = '' # type: ignore[union-attr] if new_state == AgentState.USER_CONFIRMED: confirmation_state = ActionConfirmationStatus.CONFIRMED else: confirmation_state = ActionConfirmationStatus.REJECTED self._pending_action.confirmation_state = confirmation_state # 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.ENVIRONMENT, ) 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, # start on top of the stream start_id=self.event_stream.get_latest_event_id() + 1, ) self.log( 'debug', f'start delegate, creating agent {delegate_agent.name} using LLM {llm}', ) self.event_stream.unsubscribe(EventStreamSubscriber.AGENT_CONTROLLER, self.id) 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._is_stuck(): await self._react_to_exception(RuntimeError('Agent got stuck in a loop')) 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 self.log( 'info', f'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: self.event_stream.add_event( ErrorObservation( content=str(e), ), EventSource.AGENT, ) return if action.runnable: if self.state.confirmation_mode and ( type(action) is CmdRunAction or type(action) is IPythonRunCellAction ): action.confirmation_state = ( ActionConfirmationStatus.AWAITING_CONFIRMATION ) self._pending_action = action if not isinstance(action, NullAction): if ( hasattr(action, 'confirmation_state') and action.confirmation_state == 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() self.log('debug', str(action), extra={'msg_type': 'ACTION'}) async def _delegate_step(self): """Executes a single step of the delegate agent.""" await self.delegate._step() # type: ignore[union-attr] assert self.delegate is not None delegate_state = self.delegate.get_agent_state() self.log('debug', f'Delegate state: {delegate_state}') if delegate_state == AgentState.ERROR: # update iteration that shall be shared across agents self.state.iteration = self.delegate.state.iteration # emit AgentDelegateObservation to mark delegate termination due to error delegate_outputs = ( self.delegate.state.outputs if self.delegate.state else {} ) content = ( f'{self.delegate.agent.name} encountered an error during execution.' ) obs = AgentDelegateObservation(outputs=delegate_outputs, content=content) self.event_stream.add_event(obs, EventSource.AGENT) # close the delegate upon error await self.delegate.close() # resubscribe parent when delegate is finished self.event_stream.subscribe( EventStreamSubscriber.AGENT_CONTROLLER, self.on_event, self.id ) self.delegate = None self.delegateAction = None elif delegate_state in (AgentState.FINISHED, AgentState.REJECTED): self.log('debug', '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() # resubscribe parent when delegate is finished self.event_stream.subscribe( EventStreamSubscriber.AGENT_CONTROLLER, self.on_event, self.id ) # 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 = 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: self.log( 'debug', '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: e = RuntimeError( f'Agent reached maximum {limit_type} in headless mode. ' f'Current {limit_type}: {current_value:.2f}, max {limit_type}: {max_value:.2f}' ) await self._react_to_exception(e) else: e = RuntimeError( f'Agent reached maximum {limit_type}. ' f'Current {limit_type}: {current_value:.2f}, max {limit_type}: {max_value:.2f}. ' ) # FIXME: this isn't really an exception--we should have a different path await self._react_to_exception(e) 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 can come from: # - the previous session, in which case it has history # - from a parent agent, in which case it has no history # - None / a new state if state is None: self.state = State( inputs={}, max_iterations=max_iterations, confirmation_mode=confirmation_mode, ) else: self.state = state if self.state.start_id <= -1: self.state.start_id = 0 self.log( 'debug', f'AgentController {self.id} initializing history from event {self.state.start_id}', ) self._init_history() def _init_history(self): """Initializes the agent's history from the event stream. The history is a list of events that: - Excludes events of types listed in self.filter_out - Excludes events with hidden=True attribute - For delegate events (between AgentDelegateAction and AgentDelegateObservation): - Excludes all events between the action and observation - Includes the delegate action and observation themselves """ # define range of events to fetch # delegates start with a start_id and initially won't find any events # otherwise we're restoring a previous session start_id = self.state.start_id if self.state.start_id >= 0 else 0 end_id = ( self.state.end_id if self.state.end_id >= 0 else self.event_stream.get_latest_event_id() ) # sanity check if start_id > end_id + 1: self.log( 'debug', f'start_id {start_id} is greater than end_id + 1 ({end_id + 1}). History will be empty.', ) self.state.history = [] return # Get all events, filtering out backend events and hidden events events = list( self.event_stream.get_events( start_id=start_id, end_id=end_id, reverse=False, filter_out_type=self.filter_out, filter_hidden=True, ) ) # Find all delegate action/observation pairs delegate_ranges: list[tuple[int, int]] = [] delegate_action_ids: list[int] = [] # stack of unmatched delegate action IDs for event in events: if isinstance(event, AgentDelegateAction): delegate_action_ids.append(event.id) # Note: we can get agent=event.agent and task=event.inputs.get('task','') # if we need to track these in the future elif isinstance(event, AgentDelegateObservation): # Match with most recent unmatched delegate action if not delegate_action_ids: self.log( 'error', f'Found AgentDelegateObservation without matching action at id={event.id}', ) continue action_id = delegate_action_ids.pop() delegate_ranges.append((action_id, event.id)) # Filter out events between delegate action/observation pairs if delegate_ranges: filtered_events: list[Event] = [] current_idx = 0 for start_id, end_id in sorted(delegate_ranges): # Add events before delegate range filtered_events.extend( event for event in events[current_idx:] if event.id < start_id ) # Add delegate action and observation filtered_events.extend( event for event in events if event.id in (start_id, end_id) ) # Update index to after delegate range current_idx = next( (i for i, e in enumerate(events) if e.id > end_id), len(events) ) # Add any remaining events after last delegate range filtered_events.extend(events[current_idx:]) self.state.history = filtered_events else: self.state.history = events # make sure history is in sync self.state.start_id = start_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})' )