582 lines
23 KiB
Python
582 lines
23 KiB
Python
"""Script to run end-to-end evaluation on the benchmark.
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Utils and basic architecture credit to https://github.com/web-arena-x/webarena/blob/main/run.py.
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"""
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import argparse
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import datetime
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import json
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import logging
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import os
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import sys
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import math
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import ast
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import time
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import backoff
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import httpx
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from openai import APIConnectionError, APIError, OpenAI, RateLimitError
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from requests.exceptions import SSLError
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from tqdm import tqdm
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import lib_run_single
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from desktop_env.desktop_env import MAX_RETRIES, DesktopEnv as DesktopEnvBase
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from mm_agents.autoglm import AutoGLMAgent
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from typing import Optional, Dict, Any
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from multiprocessing import Pool
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# Logger Configs {{{ #
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logger = logging.getLogger()
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logger.setLevel(logging.DEBUG)
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datetime_str: str = datetime.datetime.now().strftime("%Y%m%d@%H%M%S")
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file_handler = logging.FileHandler(os.path.join("logs", "normal-{:}.log".format(datetime_str)), encoding="utf-8")
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debug_handler = logging.FileHandler(os.path.join("logs", "debug-{:}.log".format(datetime_str)), encoding="utf-8")
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stdout_handler = logging.StreamHandler(sys.stdout)
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sdebug_handler = logging.FileHandler(os.path.join("logs", "sdebug-{:}.log".format(datetime_str)), encoding="utf-8")
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file_handler.setLevel(logging.INFO)
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debug_handler.setLevel(logging.DEBUG)
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stdout_handler.setLevel(logging.INFO)
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sdebug_handler.setLevel(logging.DEBUG)
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formatter = logging.Formatter(
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fmt="\x1b[1;33m[%(asctime)s \x1b[31m%(levelname)s \x1b[32m%(module)s/%(lineno)d-%(processName)s\x1b[1;33m] \x1b[0m%(message)s"
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)
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file_handler.setFormatter(formatter)
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debug_handler.setFormatter(formatter)
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stdout_handler.setFormatter(formatter)
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sdebug_handler.setFormatter(formatter)
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stdout_handler.addFilter(logging.Filter("desktopenv"))
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sdebug_handler.addFilter(logging.Filter("desktopenv"))
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logger.addHandler(file_handler)
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logger.addHandler(debug_handler)
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logger.addHandler(stdout_handler)
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logger.addHandler(sdebug_handler)
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# }}} Logger Configs #
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logger = logging.getLogger("desktopenv.experiment")
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def config() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Run end-to-end evaluation on the benchmark")
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# environment config
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parser.add_argument("--path_to_vm", type=str)
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parser.add_argument(
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"--provider_name",
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type=str,
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default="docker",
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help="Virtualization provider (vmware, docker, aws, azure, gcp, virtualbox)",
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)
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parser.add_argument("--headless", action="store_true", default=True, help="Run in headless machine")
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parser.add_argument("--action_space", type=str, default="autoglm_computer_use", help="Action type")
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parser.add_argument(
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"--observation_type",
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choices=["screenshot", "a11y_tree", "screenshot_a11y_tree", "som"],
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default="a11y_tree",
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help="Observation type",
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)
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parser.add_argument("--screen_width", type=int, default=1920)
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parser.add_argument("--screen_height", type=int, default=1080)
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parser.add_argument("--sleep_after_execution", type=float, default=1.0)
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parser.add_argument("--max_steps", type=int, default=50)
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# agent config
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parser.add_argument("--max_trajectory_length", type=int, default=3)
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parser.add_argument("--test_config_base_dir", type=str, default="evaluation_examples")
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# lm config
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parser.add_argument("--model", type=str, default="autoglm-os")
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parser.add_argument("--temperature", type=float, default=0.4)
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parser.add_argument("--top_p", type=float, default=0.5)
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parser.add_argument("--max_tokens", type=int, default=4096)
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parser.add_argument("--stop_token", type=str, default=None)
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# example config
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parser.add_argument("--domain", type=str, default="all")
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parser.add_argument("--test_all_meta_path", type=str, default="evaluation_examples/test_nogdrive.json")
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# aws config
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parser.add_argument(
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"--region", type=str, default="us-east-1", help="AWS region for the VM"
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)
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parser.add_argument("--client_password", type=str, default="", help="Client password")
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# logging related
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parser.add_argument("--result_dir", type=str, default="./results")
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# parallel number
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parser.add_argument("--num_workers", type=int, default=20, help="Number of parallel workers")
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args = parser.parse_args()
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return args
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class DesktopEnv(DesktopEnvBase):
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def step(self, action, pause=2):
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self._step_no += 1
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self.action_history.append(action)
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# Mark environment as used when step is called
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self.is_environment_used = True
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reward = 0 # todo: Define reward calculation for each example
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done = False # todo: Define episode termination condition for each example
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info = {}
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logger.info(f"Step {self._step_no} in trajectory {self._traj_no} with action: {action}")
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# handle the special actions
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if action in ['WAIT', 'FAIL', 'DONE']:
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if action == 'WAIT':
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time.sleep(pause)
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exe_result = 'Wait ' + str(pause) + ' seconds'
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elif action == 'FAIL':
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done = True
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info = {"fail": True}
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exe_result = 'Finish: fail'
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elif action == 'DONE':
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done = True
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info = {"done": True}
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exe_result = 'Finish: success'
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elif type(action) == dict:
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if action['action_type'] == 'OPEN_APP':
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self.setup_controller._launch_setup(action['parameters']['launch_app_command'], shell=True)
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exe_result = 'Open ' + action['parameters']['app_name']
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elif action['action_type'] == 'OPEN_CHROME_TAB':
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self.setup_controller._chrome_open_tabs_setup(action['parameters']['urls_to_open'])
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exe_result = 'Open ' + str(action['parameters']['urls_to_open']) + ' in Chrome successfully'
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else:
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# the set of all possible python commands insides `pyautogui`
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result = self.controller.execute_python_command(action)
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try:
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if result['error']:
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exe_result = result['error'].strip()
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else:
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exe_result = result['output'].strip()
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except Exception as e:
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exe_result = 'Error Action: ' + action
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logger.error(f"Error executing action: {e}")
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time.sleep(pause)
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observation = self._get_obs()
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observation['exe_result'] = exe_result
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return observation, reward, done, info
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def reset(self, task_config: Optional[Dict[str, Any]] = None, seed=None, options=None) -> Dict[str, Any]:
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# Reset to certain task in OSWorld
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logger.info("Resetting environment...")
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logger.info("Switching task...")
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logger.info("Setting counters...")
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self._traj_no += 1
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self._step_no = 0
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self.action_history.clear()
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for attempt in range(MAX_RETRIES):
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# Only revert to snapshot if environment has been used (step/setup)
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# This optimization is especially important for cloud providers like AWS
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# where unnecessary snapshot operations are costly and time-consuming
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if task_config is not None:
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# Only consider task proxy requirement if proxy is enabled at system level
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task_use_proxy = task_config.get("proxy", False) and self.enable_proxy
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if not self.enable_proxy and task_config.get("proxy", False):
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logger.info("Task requires proxy but proxy is disabled at system level, ignoring proxy requirement.")
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if task_use_proxy != self.current_use_proxy:
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# keep because get_info_from_website depend on this
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self.current_use_proxy = task_use_proxy
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if self.is_environment_used:
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logger.info("Environment has been used, reverting to snapshot {}...".format(self.snapshot_name))
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self._revert_to_snapshot()
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logger.info("Starting emulator...")
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self._start_emulator()
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logger.info("Emulator started.")
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# Reset the usage flag after reverting
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self.is_environment_used = False
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else:
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logger.info("Environment is clean, skipping snapshot revert (provider: {}).".format(self.provider_name))
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if task_config is not None:
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if task_config.get("proxy", False) and self.enable_proxy:
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# If using proxy and proxy is enabled, set up the proxy configuration
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self.setup_controller._proxy_setup(self.client_password)
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self._set_task_info(task_config)
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self.setup_controller.reset_cache_dir(self.cache_dir)
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logger.info("Setting up environment...")
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success = self.setup_controller.setup(self.config, task_config.get("proxy", False) and self.enable_proxy)
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if success:
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# Mark environment as used when setup is successfully executed
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if self.config: # Only mark as used if there were actual setup operations
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self.is_environment_used = True
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break
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else:
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logger.error(
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"Environment setup failed, retrying (%d/%d)...",
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attempt + 1,
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MAX_RETRIES,
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)
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time.sleep(5)
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else:
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break
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logger.info("Environment setup complete.")
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# Upload tools from autoglm package
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import mm_agents.autoglm
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tool_dir = os.path.join(os.path.dirname(mm_agents.autoglm.__file__), 'tools', 'package')
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for file in os.listdir(tool_dir):
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if os.path.isdir(os.path.join(tool_dir, file)):
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continue
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self.setup_controller._upload_file_setup([{
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"local_path": os.path.join(tool_dir, file),
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"path": os.path.join('~', file)
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}])
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# start soffice service for office tools
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self.setup_controller._launch_setup('soffice --accept="socket,host=localhost,port=2002;urp;" --norestore --nologo --nodefault', shell=True)
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time.sleep(5)
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observation = self._get_obs()
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return observation
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def get_current_apps(self):
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apps_code = r"""import subprocess;
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command = "wmctrl -xl";
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apps = subprocess.run(command, shell=True, capture_output=True, text=True).stdout.strip().split('\n');
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print(apps);"""
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window_code = r"""import subprocess;
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command = "wmctrl -a :ACTIVE: -v 2>&1 | grep 'Using window' | awk '{print $3}'";
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window_id = subprocess.run(command, shell=True, capture_output=True, text=True).stdout.strip();
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print(window_id);"""
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apps = self.controller.execute_python_command(apps_code)['output'].strip()
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apps = ast.literal_eval(apps)
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app_list = {}
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for app in apps:
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parts = app.split(maxsplit=4)
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if len(parts) < 4:
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continue
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if parts[1] != '0':
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continue
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window_id = parts[0]
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app_name = '.'.join(parts[2].split('.')[-(math.ceil(parts[2].count('.') / 2)):])
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title = parts[3]
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app_list[window_id] = {
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'app_name': app_name,
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'title': title
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}
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cur_id = self.controller.execute_python_command(window_code)['output'].strip()
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return app_list, cur_id
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def maximize_window(self):
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window_state = r"""import subprocess;
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command = "xprop -id $(xprop -root _NET_ACTIVE_WINDOW | awk -F' ' '{print $5}') _NET_WM_STATE"
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output = subprocess.run(command, shell=True, capture_output=True, text=True).stdout.strip();
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print(output);"""
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for _ in range(5):
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try:
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self.setup_controller._launch_setup('wmctrl -r :ACTIVE: -b add,maximized_vert,maximized_horz', shell=True)
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time.sleep(2)
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output = self.controller.execute_python_command(window_state)['output'].strip()
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if '_NET_WM_STATE_FOCUSED' not in output or '_NET_WM_STATE_SKIP_TASKBAR' in output or '_NET_WM_STATE_MODAL' in output or '_NET_WM_STATE_MAXIMIZED' in output: # 没有窗口 or popups or 模态窗口 or 窗口已经最大化
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return
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except Exception as e:
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logger.error(f"Failed to maximize window: {e}")
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time.sleep(1)
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def _get_obs(self):
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tool_list = {
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"libreoffice_calc": "CalcTools",
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"libreoffice_impress": "ImpressTools",
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"libreoffice_writer": "WriterTools",
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"code": "CodeTools",
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"vlc": "VLCTools",
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"google_chrome": "BrowserTools"
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}
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self.maximize_window()
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for i in range(3):
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try:
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app_list, cur_id = self.get_current_apps()
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except Exception as e:
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if i == 2:
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raise e
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logger.error(f"Failed to get current apps: {e}")
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time.sleep(1)
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if cur_id in app_list:
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cur_app = app_list[cur_id]['app_name']
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tool_name = cur_app.strip().lower().replace('-', '_')
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if tool_name in tool_list:
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class_name = tool_list[tool_name]
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command = f"from {tool_name} import *; "
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command += f"{class_name}.env_info(); "
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command += f"{class_name}.print_result();"
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app_info = self.controller.execute_python_command(command)['output'].strip()
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else:
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app_info = None
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else:
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cur_app = None
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app_info = None
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tree = self.controller.get_accessibility_tree()
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screenshot = self.controller.get_screenshot()
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if screenshot is None:
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logger.error("Failed to get screenshot.")
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screenshot = b''
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return {
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"screenshot": screenshot,
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"accessibility_tree": tree,
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"instruction": self.instruction,
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"apps": app_list,
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"cur_window_id": cur_id,
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"cur_app": cur_app,
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"app_info": app_info,
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}
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def get_unfinished(action_space, use_model, observation_type, result_dir, total_file_json):
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target_dir = os.path.join(result_dir, action_space, observation_type, use_model)
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if not os.path.exists(target_dir):
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return total_file_json
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finished = {}
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for domain in os.listdir(target_dir):
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finished[domain] = []
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domain_path = os.path.join(target_dir, domain)
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if os.path.isdir(domain_path):
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for example_id in os.listdir(domain_path):
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if example_id == "onboard":
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continue
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example_path = os.path.join(domain_path, example_id)
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if os.path.isdir(example_path):
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if "result.txt" not in os.listdir(example_path):
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# empty all files under example_id
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for file in os.listdir(example_path):
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os.remove(os.path.join(example_path, file))
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else:
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finished[domain].append(example_id)
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if not finished:
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return total_file_json
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for domain, examples in finished.items():
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if domain in total_file_json:
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total_file_json[domain] = [x for x in total_file_json[domain] if x not in examples]
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return total_file_json
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def get_result(action_space, use_model, observation_type, result_dir, total_file_json):
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target_dir = os.path.join(result_dir, action_space, observation_type, use_model)
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if not os.path.exists(target_dir):
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print("New experiment, no result yet.")
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return None
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all_result = []
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for domain in os.listdir(target_dir):
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domain_path = os.path.join(target_dir, domain)
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if os.path.isdir(domain_path):
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for example_id in os.listdir(domain_path):
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example_path = os.path.join(domain_path, example_id)
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if os.path.isdir(example_path):
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if "result.txt" in os.listdir(example_path):
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# empty all files under example_id
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try:
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all_result.append(float(open(os.path.join(example_path, "result.txt"), "r").read()))
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except:
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all_result.append(0.0)
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if not all_result:
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print("New experiment, no result yet.")
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return None
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else:
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print("Current Success Rate:", sum(all_result) / len(all_result) * 100, "%")
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return all_result
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def _worker_run(task):
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import json, os, datetime, logging, httpx, backoff
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from openai import OpenAI, RateLimitError, APIConnectionError
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from types import SimpleNamespace
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domain, example_id, args = task # args 为 argparse.Namespace
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logger = logging.getLogger("desktopenv.experiment")
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try:
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config_file = os.path.join(args.test_config_base_dir, f"examples/{domain}/{example_id}.json")
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with open(config_file, "r", encoding="utf-8") as f:
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example = json.load(f)
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instruction = example["instruction"]
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@backoff.on_exception(backoff.constant, (RateLimitError, APIConnectionError), interval=0.1)
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def call_llm(messages):
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logger.info("Calling LLM...")
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# set api_key and base_url by environment variables
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engine = OpenAI(timeout=60.0)
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response = engine.chat.completions.create(
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model=args.model,
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messages=messages,
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max_tokens=args.max_tokens,
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temperature=args.temperature,
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top_p=args.top_p,
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)
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logger.info("LLM called successfully.")
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return response.choices[0].message.content
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env = DesktopEnv(
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provider_name=args.provider_name,
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region=args.region,
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client_password=args.client_password,
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path_to_vm=args.path_to_vm,
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action_space=args.action_space,
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screen_size=(args.screen_width, args.screen_height),
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headless=args.headless,
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os_type="Ubuntu",
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require_a11y_tree=args.observation_type in ["a11y_tree", "screenshot_a11y_tree", "som"],
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)
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agent = AutoGLMAgent(
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action_space=args.action_space,
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observation_type=args.observation_type,
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max_trajectory_length=args.max_trajectory_length,
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client_password=args.client_password,
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gen_func=call_llm,
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)
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example_result_dir = os.path.join(
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args.result_dir,
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args.action_space,
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args.observation_type,
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args.model,
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domain,
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example_id,
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)
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os.makedirs(example_result_dir, exist_ok=True)
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local_scores = []
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try:
|
|
lib_run_single.run_single_example_autoglm(
|
|
agent,
|
|
env,
|
|
example,
|
|
args.max_steps,
|
|
instruction,
|
|
args,
|
|
example_result_dir,
|
|
local_scores,
|
|
)
|
|
except Exception as e:
|
|
logger.error(f"[并发任务异常] {domain}/{example_id}: {e}")
|
|
if hasattr(env, "controller") and env.controller is not None:
|
|
try:
|
|
env.controller.end_recording(os.path.join(example_result_dir, "recording.mp4"))
|
|
except Exception:
|
|
pass
|
|
with open(os.path.join(example_result_dir, "traj.jsonl"), "a") as f:
|
|
f.write(json.dumps({"Error": f"Exception in {domain}/{example_id}: {str(e)}"}) + "\n")
|
|
finally:
|
|
try:
|
|
env.close()
|
|
except Exception:
|
|
pass
|
|
|
|
score = None
|
|
result_path = os.path.join(example_result_dir, "result.txt")
|
|
if os.path.exists(result_path):
|
|
try:
|
|
with open(result_path, "r") as rf:
|
|
score = float(rf.read().strip())
|
|
except Exception:
|
|
score = 0.0
|
|
else:
|
|
score = 0.0
|
|
logger.info(f"[Finish] {domain}/{example_id} score={score}")
|
|
return (domain, example_id, score)
|
|
except Exception as e:
|
|
logger = logging.getLogger("desktopenv.experiment")
|
|
logger.error(f"[Initializing Fail] {domain}/{example_id}: {e}")
|
|
return (domain, example_id, 0.0)
|
|
|
|
def test_parallel(args: argparse.Namespace, test_all_meta: dict):
|
|
from tqdm import tqdm
|
|
tasks = []
|
|
for domain in test_all_meta:
|
|
for example_id in test_all_meta[domain]:
|
|
tasks.append((domain, example_id, args))
|
|
if not tasks:
|
|
logger.info("No pending tasks")
|
|
return
|
|
logger.info(f"Starting parallel execution: {args.num_workers} processes, {len(tasks)} tasks total")
|
|
|
|
results = []
|
|
with Pool(processes=args.num_workers) as pool:
|
|
for res in tqdm(pool.imap_unordered(_worker_run, tasks), total=len(tasks), desc="Parallel execution"):
|
|
results.append(res)
|
|
|
|
scores = [s for (_, _, s) in results if s is not None]
|
|
if scores:
|
|
avg = sum(scores) / len(scores)
|
|
logger.info(f"Parallel execution completed. Average score: {avg}")
|
|
else:
|
|
logger.info("No scores obtained.")
|
|
|
|
if __name__ == "__main__":
|
|
####### The complete version of the list of examples #######
|
|
os.environ["TOKENIZERS_PARALLELISM"] = "false"
|
|
args = config()
|
|
if args.client_password == "":
|
|
if args.provider_name == "aws":
|
|
args.client_password = "osworld-public-evaluation"
|
|
else:
|
|
args.client_password = "password"
|
|
else:
|
|
args.client_password = args.client_password
|
|
|
|
# save args to json in result_dir/action_space/observation_type/model/args.json
|
|
path_to_args = os.path.join(
|
|
args.result_dir,
|
|
args.action_space,
|
|
args.observation_type,
|
|
args.model,
|
|
"args.json",
|
|
)
|
|
os.makedirs(os.path.dirname(path_to_args), exist_ok=True)
|
|
with open(path_to_args, "w", encoding="utf-8") as f:
|
|
json.dump(vars(args), f, indent=4)
|
|
|
|
with open(args.test_all_meta_path, "r", encoding="utf-8") as f:
|
|
test_all_meta = json.load(f)
|
|
|
|
if args.domain != "all":
|
|
test_all_meta = {args.domain: test_all_meta[args.domain]}
|
|
|
|
test_file_list = get_unfinished(
|
|
args.action_space,
|
|
args.model,
|
|
args.observation_type,
|
|
args.result_dir,
|
|
test_all_meta,
|
|
)
|
|
left_info = ""
|
|
for domain in test_file_list:
|
|
left_info += f"{domain}: {len(test_file_list[domain])}\n"
|
|
logger.info(f"Left tasks:\n{left_info}")
|
|
|
|
get_result(
|
|
args.action_space,
|
|
args.model,
|
|
args.observation_type,
|
|
args.result_dir,
|
|
test_all_meta,
|
|
)
|
|
test_parallel(args, test_file_list)
|