00804f8118
- Changed the default provider name from "aws" to "vmware" to reflect new environment requirements. - Updated the action space from "computer_13" to "pyautogui" for improved interaction capabilities. - Maintained existing class structure and logic while implementing these updates for better functionality.
497 lines
22 KiB
Python
497 lines
22 KiB
Python
from __future__ import annotations
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import logging
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import os
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import time
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import re
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from typing import Callable, Any, Optional, Tuple
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from typing import List, Dict, Union
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import gymnasium as gym
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from desktop_env.controllers.python import PythonController
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from desktop_env.controllers.setup import SetupController
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from desktop_env.evaluators import metrics, getters
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from desktop_env.providers import create_vm_manager_and_provider
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logger = logging.getLogger("desktopenv.env")
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Metric = Callable[[Any, Any], float]
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Getter = Callable[[gym.Env, Dict[str, Any]], Any]
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MAX_RETRIES = 5 # Maximum retries for environment setup
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def _fix_pyautogui_less_than_bug(command: str) -> str:
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"""
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Fix PyAutoGUI '<' character bug by converting it to hotkey("shift", ',') calls.
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This fixes the known PyAutoGUI issue where typing '<' produces '>' instead.
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References:
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- https://github.com/asweigart/pyautogui/issues/198
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- https://github.com/xlang-ai/OSWorld/issues/257
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Args:
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command (str): The original pyautogui command
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Returns:
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str: The fixed command with '<' characters handled properly
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"""
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# Pattern to match press('<') or press('\u003c') calls
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press_pattern = r'pyautogui\.press\(["\'](?:<|\\u003c)["\']\)'
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# Handle press('<') calls
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def replace_press_less_than(match):
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return 'pyautogui.hotkey("shift", ",")'
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# First handle press('<') calls
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command = re.sub(press_pattern, replace_press_less_than, command)
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# Pattern to match typewrite calls with quoted strings
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typewrite_pattern = r'pyautogui\.typewrite\((["\'])(.*?)\1\)'
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# Then handle typewrite calls
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def process_typewrite_match(match):
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quote_char = match.group(1)
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content = match.group(2)
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# Preprocess: Try to decode Unicode escapes like \u003c to actual '<'
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# This handles cases where '<' is represented as escaped Unicode
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try:
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# Attempt to decode unicode escapes
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decoded_content = content.encode('utf-8').decode('unicode_escape')
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content = decoded_content
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except UnicodeDecodeError:
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# If decoding fails, proceed with original content to avoid breaking existing logic
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pass # English comment: Graceful degradation - fall back to original content if decoding fails
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# Check if content contains '<'
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if '<' not in content:
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return match.group(0)
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# Split by '<' and rebuild
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parts = content.split('<')
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result_parts = []
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for i, part in enumerate(parts):
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if i == 0:
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# First part
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if part:
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result_parts.append(f"pyautogui.typewrite({quote_char}{part}{quote_char})")
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else:
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# Add hotkey for '<' and then typewrite for the rest
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result_parts.append('pyautogui.hotkey("shift", ",")')
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if part:
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result_parts.append(f"pyautogui.typewrite({quote_char}{part}{quote_char})")
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return '; '.join(result_parts)
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command = re.sub(typewrite_pattern, process_typewrite_match, command)
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return command
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class DesktopEnv(gym.Env):
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"""
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DesktopEnv with OpenAI Gym interface. It provides a desktop environment for setting and evaluating desktop automation tasks.
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"""
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def __init__(
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self,
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provider_name: str = "vmware",
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region: str = None,
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path_to_vm: str = None,
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snapshot_name: str = "init_state",
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action_space: str = "pyautogui",
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cache_dir: str = "cache",
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screen_size: Tuple[int] = (int(os.environ.get("SCREEN_WIDTH", 1920)), int(os.environ.get("SCREEN_HEIGHT", 1080))),
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headless: bool = False,
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require_a11y_tree: bool = True,
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require_terminal: bool = False,
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os_type: str = "Ubuntu",
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enable_proxy: bool = False,
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client_password: str = "",
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):
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"""
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Args:
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provider_name (str): virtualization provider name, default to "vmware"
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region (str): the region for allocate machines, work for cloud services, default to "us-east-1"
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path_to_vm (str): path to .vmx file
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snapshot_name (str): snapshot name to revert to, default to "init_state"
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action_space (str): "computer_13" | "pyautogui"
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cache_dir (str): cache directory to cache task-related stuffs like
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reference file for evaluation
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screen_size (Tuple[int]): screen size of the VM
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headless (bool): whether to run the VM in headless mode
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require_a11y_tree (bool): whether to require accessibility tree
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require_terminal (bool): whether to require terminal output
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os_type (str): operating system type, default to "Ubuntu"
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enable_proxy (bool): whether to enable proxy support, default to False
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"""
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# Initialize VM manager and vitualization provider
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self.region = region
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self.provider_name = provider_name
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self.enable_proxy = enable_proxy # Store proxy enablement setting
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if client_password == "":
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if self.provider_name == "aws":
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self.client_password = "osworld-public-evaluation"
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else:
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self.client_password = "password"
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else:
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self.client_password = client_password
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self.screen_width = screen_size[0]
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self.screen_height = screen_size[1]
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# Default
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self.server_port = 5000
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self.chromium_port = 9222
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self.vnc_port = 8006
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self.vlc_port = 8080
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# Initialize with default (no proxy) provider
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self.current_use_proxy = False
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self.manager, self.provider = create_vm_manager_and_provider(provider_name, region, use_proxy=False)
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self.os_type = os_type
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# Track whether environment has been used (step/setup) to optimize snapshot revert
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# docker, aws, gcp, azure are always unused as the emulator starts from a clean state
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# vmware, virtualbox are always used as the emulator starts from a dirty state
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if self.provider_name in {"docker", "aws", "gcp", "azure"}:
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self.is_environment_used = False
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elif self.provider_name in {"vmware", "virtualbox"}:
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self.is_environment_used = True
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else:
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raise ValueError(f"Invalid provider name: {self.provider_name}")
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# Initialize environment variables
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if path_to_vm:
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self.path_to_vm = os.path.abspath(os.path.expandvars(os.path.expanduser(path_to_vm))) \
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if provider_name in {"vmware", "virtualbox"} else path_to_vm
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else:
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self.path_to_vm = self.manager.get_vm_path(os_type=self.os_type, region=region, screen_size=(self.screen_width, self.screen_height))
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try:
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self.snapshot_name = snapshot_name
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self.cache_dir_base: str = cache_dir
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# todo: add the logic to get the screen size from the VM
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self.headless = headless
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self.require_a11y_tree = require_a11y_tree
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self.require_terminal = require_terminal
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# Initialize emulator and controller
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logger.info("Initializing...")
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self._start_emulator()
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# mode: human or machine
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self.instruction = None
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assert action_space in ["computer_13", "pyautogui", "claude_computer_use"]
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self.action_space = action_space # todo: refactor it to the ActType
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# episodic stuffs, like counters, will be updated or reset
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# when calling self.reset()
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self._traj_no: int = -1
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self._step_no: int = 0
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self.action_history: List[Dict[str, any]] = []
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except Exception as e:
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logger.error(f"Failed to initialize DesktopEnv: {e}")
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# If initialization fails, we should clean up the VM
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try:
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self.close()
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self.manager.delete_vm(self.path_to_vm, self.region)
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logger.info(f"Cleaned up VM {self.path_to_vm}.")
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except Exception as cleanup_error:
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logger.error(f"Failed to clean up VM {self.path_to_vm}: {cleanup_error}")
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raise
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def _start_emulator(self):
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# Power on the virtual machine
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self.provider.start_emulator(self.path_to_vm, self.headless, self.os_type)
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# Get the ip from the virtual machine, and setup the controller
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vm_ip_ports = self.provider.get_ip_address(self.path_to_vm).split(':')
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self.vm_ip = vm_ip_ports[0]
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# Get the ports from the virtual machine (for Docker provider only)
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if len(vm_ip_ports) > 1:
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self.server_port = int(vm_ip_ports[1])
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self.chromium_port = int(vm_ip_ports[2])
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self.vnc_port = int(vm_ip_ports[3])
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self.vlc_port = int(vm_ip_ports[4])
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self.controller = PythonController(vm_ip=self.vm_ip, server_port=self.server_port)
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self.setup_controller = SetupController(vm_ip=self.vm_ip, server_port=self.server_port, chromium_port=self.chromium_port, vlc_port=self.vlc_port, cache_dir=self.cache_dir_base, client_password=self.client_password, screen_width=self.screen_width, screen_height=self.screen_height)
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def _revert_to_snapshot(self):
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# Revert to certain snapshot of the virtual machine, and refresh the path to vm and ip of vm
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# due to the fact it could be changed when implemented by cloud services
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path_to_vm = self.provider.revert_to_snapshot(self.path_to_vm, self.snapshot_name)
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if path_to_vm and not path_to_vm == self.path_to_vm:
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# path_to_vm has to be a new path
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self.manager.delete_vm(self.path_to_vm, self.region)
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self.manager.add_vm(path_to_vm, self.region)
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self.manager.occupy_vm(path_to_vm, os.getpid(), self.region)
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self.path_to_vm = path_to_vm
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def _save_state(self, snapshot_name=None):
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# Save the current virtual machine state to a certain snapshot name
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self.provider.save_state(self.path_to_vm, snapshot_name)
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def close(self):
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# Close (release) the virtual machine
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self.provider.stop_emulator(self.path_to_vm)
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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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observation = self._get_obs()
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return observation
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def _get_obs(self):
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# We provide screenshot, accessibility_tree (optional), terminal (optional), and instruction.
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# can be customized and scaled
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return {
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"screenshot": self.controller.get_screenshot(),
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"accessibility_tree": self.controller.get_accessibility_tree() if self.require_a11y_tree else None,
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"terminal": self.controller.get_terminal_output() if self.require_terminal else None,
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"instruction": self.instruction
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}
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@property
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def vm_platform(self):
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return self.controller.get_vm_platform()
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@property
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def vm_screen_size(self):
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return self.controller.get_vm_screen_size()
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def _set_task_info(self, task_config: Dict[str, Any]):
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"""Set task info (proxy logic is handled in reset method)"""
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self.task_id: str = task_config["id"]
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self.cache_dir: str = os.path.join(self.cache_dir_base, self.task_id)
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os.makedirs(self.cache_dir, exist_ok=True)
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self.instruction = task_config["instruction"]
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self.config = task_config["config"] if "config" in task_config else []
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self._set_evaluator_info(task_config)
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def _set_evaluator_info(self, task_config: Dict[str, Any]):
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"""Set evaluator information from task config"""
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# evaluator dict
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# func -> metric function string, or list of metric function strings
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# conj -> conjunction of multiple metrics if func is a list with length > 1, "and"/"or"
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# result -> result getter config, or list of result getter configs
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# expected (optional) -> expected getter config, or list of expected getter configs
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# options (optional) -> metric options, or list of metric options
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# if func is a str list, then result, expected (if exists), options (if exists) should also be lists of the same length
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# even if one of the metrics does not need expected or options field, it should be included in the list with None
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self.evaluator = task_config["evaluator"]
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self.metric: Metric = [getattr(metrics, func) for func in self.evaluator["func"]] \
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if isinstance(self.evaluator["func"], list) \
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else getattr(metrics, self.evaluator["func"])
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self.metric_conj: str = self.evaluator.get("conj", "and") # take conjunction of multiple metrics
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if "result" in self.evaluator and len(self.evaluator["result"]) > 0:
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self.result_getter: Getter = [getattr(getters, "get_{:}".format(res["type"])) for res in
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self.evaluator["result"]] \
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if isinstance(self.evaluator["result"], list) \
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else getattr(getters, "get_{:}".format(self.evaluator["result"]["type"]))
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else:
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self.result_getter = [None] * len(self.metric) \
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if isinstance(self.metric, list) \
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else None
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if "expected" in self.evaluator and len(self.evaluator["expected"]) > 0:
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self.expected_getter: Getter = [getattr(getters, "get_{:}".format(exp["type"])) if exp else None for exp in
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self.evaluator["expected"]] \
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if isinstance(self.evaluator["expected"], list) \
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else getattr(getters, "get_{:}".format(self.evaluator["expected"]["type"]))
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else:
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self.expected_getter = [None] * len(self.metric) \
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if isinstance(self.metric, list) \
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else None
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self.metric_options: Union[List[Dict[str, Any]], Dict[str, Any]] = [opt if opt else {} for opt in
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self.evaluator["options"]] \
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if isinstance(self.evaluator.get("options", {}), list) \
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else self.evaluator["options"] \
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if "options" in self.evaluator \
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else [{}] * len(self.metric) \
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if isinstance(self.metric, list) \
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else {}
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assert (not isinstance(self.evaluator["func"], list)
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or (len(self.metric) == len(self.result_getter) == len(self.expected_getter) == len(
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self.metric_options)))
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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'] or (type(action) == dict and action['action_type'] in ['WAIT', 'FAIL', 'DONE']):
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if action == 'WAIT':
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time.sleep(pause)
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elif action == 'FAIL':
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done = True
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info = {"fail": True}
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elif action == 'DONE':
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done = True
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info = {"done": True}
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if self.action_space == "computer_13":
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# the set of all possible actions defined in the action representation
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self.controller.execute_action(action)
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elif self.action_space == "pyautogui" or self.action_space == "claude_computer_use":
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if action in ['WAIT', 'FAIL', 'DONE']:
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self.controller.execute_action(action)
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else:
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# the set of all possible python commands insides `pyautogui`
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if type(action) == str:
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# Fix PyAutoGUI '<' character bug before execution
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fixed_command = _fix_pyautogui_less_than_bug(action)
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self.controller.execute_python_command(fixed_command)
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elif type(action) == dict:
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# Fix PyAutoGUI '<' character bug before execution
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fixed_command = _fix_pyautogui_less_than_bug(action['command'])
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self.controller.execute_python_command(fixed_command)
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time.sleep(pause)
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observation = self._get_obs()
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return observation, reward, done, info
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def evaluate(self):
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"""
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Evaluate whether the task is successfully completed.
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"""
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postconfig = self.evaluator.get("postconfig", [])
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self.setup_controller.setup(postconfig)
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# Mark environment as used if there were postconfig setup operations
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if postconfig:
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self.is_environment_used = True
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if self.evaluator['func'] == "infeasible":
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if len(self.action_history) > 0 and self.action_history[-1] == "FAIL":
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return 1
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else:
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return 0
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else:
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if len(self.action_history) > 0 and self.action_history[-1] == "FAIL":
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return 0
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if type(self.metric) == list:
|
|
# Multiple metrics to evaluate whether the task is successfully completed
|
|
results = []
|
|
assert len(self.metric) == len(self.result_getter), "The number of metrics and result getters must be the same"
|
|
if "expected" in self.evaluator:
|
|
assert len(self.metric) == len(self.expected_getter), "The number of metrics and expected getters must be the same"
|
|
for idx, metric in enumerate(self.metric):
|
|
try:
|
|
config = self.evaluator["result"][idx]
|
|
result_state = self.result_getter[idx](self, config)
|
|
except FileNotFoundError:
|
|
logger.error("File not found!")
|
|
if self.metric_conj == 'and':
|
|
return 0
|
|
|
|
if "expected" in self.evaluator and self.expected_getter and self.evaluator["expected"]:
|
|
expected_state = self.expected_getter[idx](self, self.evaluator["expected"][idx])
|
|
metric: int = metric(result_state, expected_state, **self.metric_options[idx])
|
|
else:
|
|
metric: int = metric(result_state, **self.metric_options[idx])
|
|
|
|
if self.metric_conj == 'and' and float(metric) == 0.0:
|
|
return 0
|
|
elif self.metric_conj == 'or' and float(metric) == 1.0:
|
|
return 1
|
|
else:
|
|
results.append(metric)
|
|
|
|
return sum(results) / len(results) if self.metric_conj == 'and' else max(results)
|
|
else:
|
|
# Single metric to evaluate whether the task is successfully completed
|
|
try:
|
|
result_state = self.result_getter(self, self.evaluator["result"])
|
|
except FileNotFoundError:
|
|
logger.error("File not found!")
|
|
return 0
|
|
|
|
if "expected" in self.evaluator and self.expected_getter and self.evaluator["expected"]:
|
|
expected_state = self.expected_getter(self, self.evaluator["expected"])
|
|
metric: float = self.metric(result_state, expected_state, **self.metric_options)
|
|
else:
|
|
metric: float = self.metric(result_state, **self.metric_options)
|
|
|
|
return metric
|
|
|
|
def render(self, mode='rgb_array'):
|
|
if mode == 'rgb_array':
|
|
return self.controller.get_screenshot()
|
|
else:
|
|
raise ValueError('Unsupported render mode: {}'.format(mode))
|