281 lines
10 KiB
Python
281 lines
10 KiB
Python
from __future__ import annotations
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import logging
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import os
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import subprocess
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import tempfile
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import time
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from typing import Callable, Any, Optional
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# import uuid
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# import platform
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from typing import List, Dict
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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 eval_funcs
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from desktop_env.evaluators import metrics, getters
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# import requests
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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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def _execute_command(command: List[str]) -> None:
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if command[:4] == ["vmrun", "-T", "ws", "start"]:
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p = subprocess.Popen(command)
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p.wait()
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else:
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result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=60, text=True)
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if result.returncode != 0:
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raise Exception("\033[91m" + result.stdout + result.stderr + "\033[0m")
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return result.stdout
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class DesktopEnv(gym.Env):
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"""
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DesktopEnv with OpenAI Gym interface.
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Fixme: refactor the logic when implementing the multi-process version
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"""
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def __init__(
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self,
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path_to_vm: str,
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action_space: str = "computer_13",
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task_config: Dict[str, Any] = None,
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tmp_dir: str = "tmp",
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cache_dir: str = "cache"
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):
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"""
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Args:
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path_to_vm (str): path to .vmx file
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action_space (str): "computer_13" | "pyautogui"
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task_config (Dict[str, Any]): manages task configs integratedly,
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including
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* base snapshot
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* task id (uuid)
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* instruction
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* setup config
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* evaluator config
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tmp_dir (str): temporary directory to store trajectory stuffs like
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the extracted screenshots
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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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"""
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# Initialize environment variables
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self.path_to_vm = os.path.abspath(os.path.expandvars(os.path.expanduser(path_to_vm)))
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self.tmp_dir_base: str = tmp_dir
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self.cache_dir_base: str = cache_dir
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# task-aware stuffs
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# todo: handling the logic of snapshot directory
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self._set_task_info(task_config)
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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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self.vm_ip = self._get_vm_ip()
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self.controller = PythonController(vm_ip=self.vm_ip)
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self.setup_controller = SetupController(vm_ip=self.vm_ip, cache_dir=self.cache_dir)
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# Meta info of the VM, move to the reset() function
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self.vm_platform: str = "" # self.controller.get_vm_platform()
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self.vm_screen_size = None # self.controller.get_vm_screen_size()
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# mode: human or machine
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assert action_space in ["computer_13", "pyautogui"]
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self.action_space = action_space
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# todo: define the action space and the observation space as gym did, or extend theirs
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# episodic stuffs, like tmp dir and counters, will be updated or reset
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# when calling self.reset()
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self.tmp_dir: str = self.tmp_dir_base # just an init value, updated during 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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def _start_emulator(self):
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while True:
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try:
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output = subprocess.check_output("vmrun -T ws list", shell=True, stderr=subprocess.STDOUT)
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output = output.decode()
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output: List[str] = output.splitlines()
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# if self.path_to_vm.lstrip("~/") in output:
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if self.path_to_vm in output:
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logger.info("VM is running.")
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break
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else:
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logger.info("Starting VM...")
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_execute_command(["vmrun", "-T", "ws", "start", self.path_to_vm])
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time.sleep(3)
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except subprocess.CalledProcessError as e:
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logger.error(f"Error executing command: {e.output.decode().strip()}")
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def _get_vm_ip(self):
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max_retries = 10
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logger.info("Getting IP Address...")
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for _ in range(max_retries):
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try:
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output = _execute_command(["vmrun", "-T", "ws", "getGuestIPAddress", self.path_to_vm]).strip()
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logger.info(f"IP address: {output}")
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return output
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except:
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time.sleep(5)
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logger.info("Retrying...")
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raise Exception("Failed to get VM IP address!")
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def _save_state(self):
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_execute_command(["vmrun", "-T", "ws" "snapshot", self.path_to_vm, self.snapshot_path])
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def _get_screenshot(self):
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# random_uuid = str(uuid.uuid4())
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# os.makedirs(os.path.join("tmp", random_uuid), exist_ok=True)
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# image_path = os.path.join("tmp", random_uuid, "screenshot.png")
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image_path: str = os.path.join(self.tmp_dir, "screenshots", "{:d}.png".format(self._step_no))
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# Get the screenshot and save to the image_path
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screenshot = self.controller.get_screenshot()
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with open(image_path, "wb") as f:
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f.write(screenshot)
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return image_path
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def _get_obs(self):
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screenshot_image_path = self._get_screenshot()
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return screenshot_image_path
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def _set_task_info(self, task_config: Dict[str, Any]):
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self.snapshot_path = task_config["snapshot"]
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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"]
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self.evaluator = task_config["evaluator"]
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self.metric: Metric = getattr(metrics, self.evaluator["func"])
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self.result_getter: Getter = getattr(getters, "get_{:}".format(self.evaluator["result"]["type"]))
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self.expected_getter: Getter = getattr(getters, "get_{:}".format(
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self.evaluator["expected"]["type"])) if "expected" in self.evaluator else None
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self.metric_options: Dict[str, Any] = self.evaluator.get("options", {})
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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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logger.info("Resetting environment...")
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logger.info("Switching task...")
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if task_config is not None:
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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 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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logger.info("Setup new temp dir...")
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self.tmp_dir = tempfile.mkdtemp(
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prefix="{:d}.{:}.".format(self._traj_no, self.task_id),
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dir=self.tmp_dir_base
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)
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os.makedirs(os.path.join(self.tmp_dir, "screenshots"))
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logger.info("Reverting to snapshot to {}...".format(self.snapshot_path))
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_execute_command(["vmrun", "-T", "ws", "revertToSnapshot", self.path_to_vm, self.snapshot_path])
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time.sleep(5)
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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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logger.info("Get meta info of the VM...")
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self.vm_platform = self.controller.get_vm_platform()
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self.vm_screen_size = self.controller.get_vm_screen_size()
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logger.info("Setting up environment...")
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self.setup_controller.setup(self.config)
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time.sleep(5)
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logger.info("Environment setup complete.")
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observation = {
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"screenshot": self._get_obs(),
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"accessibility_tree": self.controller.get_accessibility_tree(),
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}
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return observation
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def step(self, action, pause=0.5):
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self._step_no += 1
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self.action_history.append(action)
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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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# 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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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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# fixme: add reminding logic here, decide if the action is valid for the current action_space
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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":
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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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self.controller.execute_python_command(action)
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observation = {
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"screenshot": self._get_obs(),
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"accessibility_tree": self.controller.get_accessibility_tree(),
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"terminal": self.controller.get_terminal_output(),
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"instruction": self.instruction
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}
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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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self.setup_controller.setup(self.evaluator.get("postconfig", []))
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try:
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result_state = self.result_getter(self, self.evaluator["result"])
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except FileNotFoundError:
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logger.error("File not found!")
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return 0
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expected_state = self.expected_getter(self, self.evaluator["expected"]) if "expected" in self.evaluator \
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else None
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metric: float = self.metric(result_state, expected_state, **self.metric_options) if expected_state is not None \
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else self.metric(result_state, **self.metric_options)
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return metric
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def render(self, mode='rgb_array'):
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if mode == 'rgb_array':
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return self._get_obs()
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else:
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raise ValueError('Unsupported render mode: {}'.format(mode))
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def close(self):
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_execute_command(["vmrun", "stop", self.path_to_vm])
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