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import asyncio
import json
import os
from pathlib import Path
from typing import Callable, Protocol
import openhands.agenthub # noqa F401 (we import this to get the agents registered)
from openhands.controller.agent import Agent
from openhands.controller.replay import ReplayManager
from openhands.controller.state.state import State
from openhands.core.config import (
OpenHandsConfig,
parse_arguments,
setup_config_from_args,
)
from openhands.core.config.mcp_config import OpenHandsMCPConfigImpl
from openhands.core.logger import openhands_logger as logger
from openhands.core.loop import run_agent_until_done
from openhands.core.schema import AgentState
from openhands.core.setup import (
create_agent,
create_controller,
create_memory,
create_runtime,
generate_sid,
initialize_repository_for_runtime,
)
from openhands.events import EventSource, EventStreamSubscriber
from openhands.events.action import MessageAction, NullAction
from openhands.events.action.action import Action
from openhands.events.event import Event
from openhands.events.observation import AgentStateChangedObservation
from openhands.io import read_input, read_task
from openhands.mcp import add_mcp_tools_to_agent
from openhands.memory.memory import Memory
from openhands.runtime.base import Runtime
from openhands.utils.async_utils import call_async_from_sync
class FakeUserResponseFunc(Protocol):
def __call__(
self,
state: State,
encapsulate_solution: bool = False,
try_parse: Callable[[Action | None], str] | None = None,
) -> str: ...
async def run_controller(
config: OpenHandsConfig,
initial_user_action: Action,
sid: str | None = None,
runtime: Runtime | None = None,
agent: Agent | None = None,
exit_on_message: bool = False,
fake_user_response_fn: FakeUserResponseFunc | None = None,
headless_mode: bool = True,
memory: Memory | None = None,
conversation_instructions: str | None = None,
) -> State | None:
"""Main coroutine to run the agent controller with task input flexibility.
It's only used when you launch openhands backend directly via cmdline.
Args:
config: The app config.
initial_user_action: An Action object containing initial user input
sid: (optional) The session id. IMPORTANT: please don't set this unless you know what you're doing.
Set it to incompatible value will cause unexpected behavior on RemoteRuntime.
runtime: (optional) A runtime for the agent to run on.
agent: (optional) A agent to run.
exit_on_message: quit if agent asks for a message from user (optional)
fake_user_response_fn: An optional function that receives the current state
(could be None) and returns a fake user response.
headless_mode: Whether the agent is run in headless mode.
Returns:
The final state of the agent, or None if an error occurred.
Raises:
AssertionError: If initial_user_action is not an Action instance.
Exception: Various exceptions may be raised during execution and will be logged.
Notes:
- State persistence: If config.file_store is set, the agent's state will be
saved between sessions.
- Trajectories: If config.trajectories_path is set, execution history will be
saved as JSON for analysis.
- Budget control: Execution is limited by config.max_iterations and
config.max_budget_per_task.
Example:
>>> config = load_openhands_config()
>>> action = MessageAction(content="Write a hello world program")
>>> state = await run_controller(config=config, initial_user_action=action)
"""
sid = sid or generate_sid(config)
if agent is None:
agent = create_agent(config)
# when the runtime is created, it will be connected and clone the selected repository
repo_directory = None
if runtime is None:
runtime = create_runtime(
config,
sid=sid,
headless_mode=headless_mode,
agent=agent,
)
# Connect to the runtime
call_async_from_sync(runtime.connect)
# Initialize repository if needed
if config.sandbox.selected_repo:
repo_directory = initialize_repository_for_runtime(
runtime,
selected_repository=config.sandbox.selected_repo,
)
event_stream = runtime.event_stream
# when memory is created, it will load the microagents from the selected repository
if memory is None:
memory = create_memory(
runtime=runtime,
event_stream=event_stream,
sid=sid,
selected_repository=config.sandbox.selected_repo,
repo_directory=repo_directory,
conversation_instructions=conversation_instructions,
)
# Add MCP tools to the agent
if agent.config.enable_mcp:
# Add OpenHands' MCP server by default
_, openhands_mcp_stdio_servers = (
OpenHandsMCPConfigImpl.create_default_mcp_server_config(
config.mcp_host, config, None
)
)
config.mcp.stdio_servers.extend(openhands_mcp_stdio_servers)
await add_mcp_tools_to_agent(agent, runtime, memory, config)
replay_events: list[Event] | None = None
if config.replay_trajectory_path:
logger.info('Trajectory replay is enabled')
assert isinstance(initial_user_action, NullAction)
replay_events, initial_user_action = load_replay_log(
config.replay_trajectory_path
)
controller, initial_state = create_controller(
agent, runtime, config, replay_events=replay_events
)
assert isinstance(initial_user_action, Action), (
f'initial user actions must be an Action, got {type(initial_user_action)}'
)
logger.debug(
f'Agent Controller Initialized: Running agent {agent.name}, model '
f'{agent.llm.config.model}, with actions: {initial_user_action}'
)
# start event is a MessageAction with the task, either resumed or new
if initial_state is not None and initial_state.last_error:
# we're resuming the previous session
event_stream.add_event(
MessageAction(
content=(
"Let's get back on track. If you experienced errors before, do "
'NOT resume your task. Ask me about it.'
),
),
EventSource.USER,
)
else:
# init with the provided actions
event_stream.add_event(initial_user_action, EventSource.USER)
def on_event(event: Event) -> None:
if isinstance(event, AgentStateChangedObservation):
if event.agent_state == AgentState.AWAITING_USER_INPUT:
if exit_on_message:
message = '/exit'
elif fake_user_response_fn is None:
message = read_input(config.cli_multiline_input)
else:
message = fake_user_response_fn(controller.get_state())
action = MessageAction(content=message)
event_stream.add_event(action, EventSource.USER)
event_stream.subscribe(EventStreamSubscriber.MAIN, on_event, sid)
end_states = [
AgentState.FINISHED,
AgentState.REJECTED,
AgentState.ERROR,
AgentState.PAUSED,
AgentState.STOPPED,
]
try:
await run_agent_until_done(controller, runtime, memory, end_states)
except Exception as e:
logger.error(f'Exception in main loop: {e}')
# save session when we're about to close
if config.file_store is not None and config.file_store != 'memory':
end_state = controller.get_state()
# NOTE: the saved state does not include delegates events
end_state.save_to_session(
event_stream.sid, event_stream.file_store, event_stream.user_id
)
await controller.close(set_stop_state=False)
state = controller.get_state()
# save trajectories if applicable
if config.save_trajectory_path is not None:
# if save_trajectory_path is a folder, use session id as file name
if os.path.isdir(config.save_trajectory_path):
file_path = os.path.join(config.save_trajectory_path, sid + '.json')
else:
file_path = config.save_trajectory_path
os.makedirs(os.path.dirname(file_path), exist_ok=True)
histories = controller.get_trajectory(config.save_screenshots_in_trajectory)
with open(file_path, 'w') as f: # noqa: ASYNC101
json.dump(histories, f, indent=4)
return state
def auto_continue_response(
state: State,
encapsulate_solution: bool = False,
try_parse: Callable[[Action | None], str] | None = None,
) -> str:
"""Default function to generate user responses.
Tell the agent to proceed without asking for more input, or finish the interaction.
"""
message = (
'Please continue on whatever approach you think is suitable.\n'
'If you think you have solved the task, please finish the interaction.\n'
'IMPORTANT: YOU SHOULD NEVER ASK FOR HUMAN RESPONSE.\n'
)
return message
def load_replay_log(trajectory_path: str) -> tuple[list[Event] | None, Action]:
"""
Load trajectory from given path, serialize it to a list of events, and return
two things:
1) A list of events except the first action
2) First action (user message, a.k.a. initial task)
"""
try:
path = Path(trajectory_path).resolve()
if not path.exists():
raise ValueError(f'Trajectory file not found: {path}')
if not path.is_file():
raise ValueError(f'Trajectory path is a directory, not a file: {path}')
with open(path, 'r', encoding='utf-8') as file:
events = ReplayManager.get_replay_events(json.load(file))
assert isinstance(events[0], MessageAction)
return events[1:], events[0]
except json.JSONDecodeError as e:
raise ValueError(f'Invalid JSON format in {trajectory_path}: {e}')
if __name__ == '__main__':
args = parse_arguments()
config: OpenHandsConfig = setup_config_from_args(args)
# Read task from file, CLI args, or stdin
task_str = read_task(args, config.cli_multiline_input)
initial_user_action: Action = NullAction()
if config.replay_trajectory_path:
if task_str:
raise ValueError(
'User-specified task is not supported under trajectory replay mode'
)
else:
if not task_str:
raise ValueError('No task provided. Please specify a task through -t, -f.')
# Create actual initial user action
initial_user_action = MessageAction(content=task_str)
# Set session name
session_name = args.name
sid = generate_sid(config, session_name)
asyncio.run(
run_controller(
config=config,
initial_user_action=initial_user_action,
sid=sid,
fake_user_response_fn=None
if args.no_auto_continue
else auto_continue_response,
)
)