mirror of
https://github.com/OpenHands/OpenHands.git
synced 2025-12-26 05:48:36 +08:00
* Remove global config from memory * Remove runtime global config * Remove from storage * Remove global config * Fix event stream tests * Fix sandbox issue * Change config * Removed transferred tests * Add swe env box * Fixes on testing * Fixed some tests * Fix typing * Fix ipython test * Revive function * Make temp_dir fixture * Remove test to avoid circular import
188 lines
6.7 KiB
Python
188 lines
6.7 KiB
Python
import asyncio
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import os
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import sys
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from typing import Callable, Type
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import agenthub # noqa F401 (we import this to get the agents registered)
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from opendevin.controller import AgentController
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from opendevin.controller.agent import Agent
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from opendevin.controller.state.state import State
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from opendevin.core.config import get_llm_config_arg, load_app_config, parse_arguments
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from opendevin.core.logger import opendevin_logger as logger
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from opendevin.core.schema import AgentState
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from opendevin.events import EventSource, EventStream, EventStreamSubscriber
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from opendevin.events.action import MessageAction
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from opendevin.events.event import Event
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from opendevin.events.observation import AgentStateChangedObservation
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from opendevin.llm.llm import LLM
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from opendevin.runtime import get_runtime_cls
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from opendevin.runtime.sandbox import Sandbox
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from opendevin.storage import get_file_store
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config = load_app_config()
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def read_task_from_file(file_path: str) -> str:
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"""Read task from the specified file."""
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with open(file_path, 'r', encoding='utf-8') as file:
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return file.read()
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def read_task_from_stdin() -> str:
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"""Read task from stdin."""
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return sys.stdin.read()
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async def run_agent_controller(
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agent: Agent,
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task_str: str,
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max_iterations: int,
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max_budget_per_task: float | None = None,
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exit_on_message: bool = False,
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fake_user_response_fn: Callable[[State | None], str] | None = None,
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sandbox: Sandbox | None = None,
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runtime_tools_config: dict | None = None,
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sid: str | None = None,
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headless_mode: bool = True,
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) -> State | None:
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"""Main coroutine to run the agent controller with task input flexibility.
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It's only used when you launch opendevin backend directly via cmdline.
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Args:
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task_str: The task to run.
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exit_on_message: quit if agent asks for a message from user (optional)
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fake_user_response_fn: An optional function that receives the current state (could be None) and returns a fake user response.
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sandbox: An optional sandbox to run the agent in.
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headless_mode: Whether the agent is run in headless mode.
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"""
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# Logging
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logger.info(
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f'Running agent {agent.name}, model {agent.llm.config.model}, with task: "{task_str}"'
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)
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# set up the event stream
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file_store = get_file_store(config.file_store, config.file_store_path)
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cli_session = 'main' + ('_' + sid if sid else '')
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event_stream = EventStream(cli_session, file_store)
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# restore cli session if enabled
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initial_state = None
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if config.enable_cli_session:
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try:
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logger.info('Restoring agent state from cli session')
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initial_state = State.restore_from_session(cli_session, file_store)
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except Exception as e:
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print('Error restoring state', e)
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# init controller with this initial state
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controller = AgentController(
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agent=agent,
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max_iterations=max_iterations,
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max_budget_per_task=max_budget_per_task,
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agent_to_llm_config=config.get_agent_to_llm_config_map(),
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event_stream=event_stream,
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initial_state=initial_state,
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headless_mode=headless_mode,
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)
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# runtime and tools
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runtime_cls = get_runtime_cls(config.runtime)
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runtime = runtime_cls(config=config, event_stream=event_stream, sandbox=sandbox)
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await runtime.ainit()
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runtime.init_sandbox_plugins(controller.agent.sandbox_plugins)
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runtime.init_runtime_tools(
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controller.agent.runtime_tools,
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is_async=False,
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runtime_tools_config=runtime_tools_config,
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)
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# browser eval specific
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# TODO: move to a better place
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if runtime.browser and runtime.browser.eval_dir:
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logger.info(f'Evaluation directory: {runtime.browser.eval_dir}')
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with open(
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os.path.join(runtime.browser.eval_dir, 'goal.txt'), 'r', encoding='utf-8'
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) as f:
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task_str = f.read()
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logger.info(f'Dynamic Eval task: {task_str}')
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# start event is a MessageAction with the task, either resumed or new
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if config.enable_cli_session and initial_state is not None:
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# we're resuming the previous session
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event_stream.add_event(
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MessageAction(
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content="Let's get back on track. If you experienced errors before, do NOT resume your task. Ask me about it."
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),
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EventSource.USER,
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)
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elif initial_state is None:
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# init with the provided task
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event_stream.add_event(MessageAction(content=task_str), EventSource.USER)
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async def on_event(event: Event):
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if isinstance(event, AgentStateChangedObservation):
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if event.agent_state == AgentState.AWAITING_USER_INPUT:
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if exit_on_message:
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message = '/exit'
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elif fake_user_response_fn is None:
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message = input('Request user input >> ')
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else:
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message = fake_user_response_fn(controller.get_state())
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action = MessageAction(content=message)
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event_stream.add_event(action, EventSource.USER)
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event_stream.subscribe(EventStreamSubscriber.MAIN, on_event)
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while controller.state.agent_state not in [
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AgentState.FINISHED,
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AgentState.REJECTED,
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AgentState.ERROR,
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AgentState.PAUSED,
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AgentState.STOPPED,
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]:
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await asyncio.sleep(1) # Give back control for a tick, so the agent can run
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# save session when we're about to close
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if config.enable_cli_session:
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end_state = controller.get_state()
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end_state.save_to_session(cli_session, file_store)
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# close when done
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await controller.close()
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await runtime.close()
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return controller.get_state()
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if __name__ == '__main__':
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args = parse_arguments()
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# Determine the task
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if args.file:
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task_str = read_task_from_file(args.file)
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elif args.task:
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task_str = args.task
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elif not sys.stdin.isatty():
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task_str = read_task_from_stdin()
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else:
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raise ValueError('No task provided. Please specify a task through -t, -f.')
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# Override default LLM configs ([llm] section in config.toml)
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if args.llm_config:
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llm_config = get_llm_config_arg(args.llm_config)
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if llm_config is None:
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raise ValueError(f'Invalid toml file, cannot read {args.llm_config}')
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config.set_llm_config(llm_config)
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llm = LLM(config=config.get_llm_config_from_agent(args.agent_cls))
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# Create the agent
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AgentCls: Type[Agent] = Agent.get_cls(args.agent_cls)
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agent = AgentCls(llm=llm)
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asyncio.run(
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run_agent_controller(
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agent=agent,
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task_str=task_str,
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max_iterations=args.max_iterations,
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max_budget_per_task=args.max_budget_per_task,
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)
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)
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