import datetime import json import logging import os import sys import func_timeout from desktop_env.envs.desktop_env import DesktopEnv from mm_agents.gpt_4v_agent import GPT4v_Agent # Logger Configs {{{ # logger = logging.getLogger() logger.setLevel(logging.DEBUG) datetime_str: str = datetime.datetime.now().strftime("%Y%m%d@%H%M%S") file_handler = logging.FileHandler(os.path.join("logs", "normal-{:}.log".format(datetime_str)), encoding="utf-8") debug_handler = logging.FileHandler(os.path.join("logs", "debug-{:}.log".format(datetime_str)), encoding="utf-8") stdout_handler = logging.StreamHandler(sys.stdout) sdebug_handler = logging.FileHandler(os.path.join("logs", "sdebug-{:}.log".format(datetime_str)), encoding="utf-8") file_handler.setLevel(logging.INFO) debug_handler.setLevel(logging.DEBUG) stdout_handler.setLevel(logging.INFO) sdebug_handler.setLevel(logging.DEBUG) formatter = logging.Formatter( 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") file_handler.setFormatter(formatter) debug_handler.setFormatter(formatter) stdout_handler.setFormatter(formatter) sdebug_handler.setFormatter(formatter) stdout_handler.addFilter(logging.Filter("desktopenv")) sdebug_handler.addFilter(logging.Filter("desktopenv")) logger.addHandler(file_handler) logger.addHandler(debug_handler) logger.addHandler(stdout_handler) logger.addHandler(sdebug_handler) # }}} Logger Configs # logger = logging.getLogger("desktopenv.experiment") PATH_TO_VM = r"C:\Users\tianbaox\Documents\Virtual Machines\Ubuntu\Ubuntu.vmx" # PATH_TO_VM = "../../../../大文件/镜像/Ubuntu-1218/Ubuntu/Ubuntu.vmx" def run_one_example(example, agent, max_steps=10, example_trajectory_dir="exp_trajectory", recording=True): trajectory_recording_path = os.path.join(example_trajectory_dir, "trajectory.json") env = DesktopEnv( path_to_vm=PATH_TO_VM, action_space=agent.action_space, task_config=example ) # reset the environment to certain snapshot observation = env.reset() done = False step_num = 0 if recording: # send a request to the server to start recording env.controller.start_recording() while not done and step_num < max_steps: actions = agent.predict(observation) step_num += 1 for action in actions: # Capture the timestamp before executing the action action_timestamp = datetime.datetime.now().strftime("%Y%m%d@%H%M%S") logger.info("Step %d: %s", step_num, action) observation, reward, done, info = env.step(action) logger.info("Reward: %.2f", reward) logger.info("Done: %s", done) logger.info("Info: %s", info) # Save screenshot and trajectory information with open(os.path.join(example_trajectory_dir, f"step_{step_num}_{action_timestamp}.png"), "wb") as _f: with open(observation['screenshot'], "rb") as __f: screenshot = __f.read() _f.write(screenshot) with open(trajectory_recording_path, "a") as f: f.write(json.dumps({ "step_num": step_num, "action_timestamp": action_timestamp, "action": action, "reward": reward, "done": done, "info": info, "screenshot_file": f"step_{step_num}_{action_timestamp}.png" })) f.write("\n") if done: logger.info("The episode is done.") break def stop_recording(): try: env.controller.end_recording(os.path.join(example_trajectory_dir, "recording.mp4")) except Exception as e: print(f"An error occurred while stopping the recording: {e}") try: func_timeout.func_timeout(30, stop_recording) except func_timeout.exceptions.FunctionTimedOut: logger.info("Recording timed out.") result = env.evaluate() logger.info("Result: %.2f", result) with open(trajectory_recording_path, "a") as f: f.write(json.dumps({ "result": result })) f.write("\n") # env.close() logger.info("Environment closed.") def main(example_class, example_id, gpt4_model="gpt-4-vision-preview"): action_space = "pyautogui" # example_class = "libreoffice_calc" # example_id = "7b6c7e24-c58a-49fc-a5bb-d57b80e5b4c3" # example_id = "01b269ae-2111-4a07-81fd-3fcd711993b0" gemini_model = "gemini-pro-vision" logger.info("Running example %s/%s", example_class, example_id) logger.info("Using model %s", gpt4_model) # logger.info("Using model %s", gemini_model) with open(f"evaluation_examples/examples/{example_class}/{example_id}.json", "r", encoding="utf-8") as f: example = json.load(f) example["snapshot"] = "exp_v5" # example["snapshot"] = "exp_setup4" # example["snapshot"] = "Snapshot 30" api_key = os.environ.get("OPENAI_API_KEY") agent = GPT4v_Agent(api_key=api_key, model=gpt4_model, instruction=example['instruction'], action_space=action_space, exp="both") # api_key = os.environ.get("GENAI_API_KEY") # agent = GeminiPro_Agent(api_key=api_key, model=gemini_model, instruction=example['instruction'], action_space=action_space, exp="both") root_trajectory_dir = "exp_trajectory" example_trajectory_dir = os.path.join(root_trajectory_dir, "both", example_class, gpt4_model, example_id) # example_trajectory_dir = os.path.join(root_trajectory_dir, "both", example_class, gemini_model, example_id) os.makedirs(example_trajectory_dir, exist_ok=True) run_one_example(example, agent, 15, example_trajectory_dir) if __name__ == '__main__': os_list = [ "94d95f96-9699-4208-98ba-3c3119edf9c2", "bedcedc4-4d72-425e-ad62-21960b11fe0d", "43c2d64c-bab5-4dcb-a30c-b888321c319a", "7688b85f-87a4-4e4a-b2f8-f3d6c3f29b82", "ec4e3f68-9ea4-4c18-a5c9-69f89d1178b3", "f9be0997-4b7c-45c5-b05c-4612b44a6118", "28cc3b7e-b194-4bc9-8353-d04c0f4d56d2", "5ea617a3-0e86-4ba6-aab2-dac9aa2e8d57", "e0df059f-28a6-4169-924f-b9623e7184cc", "ddc75b62-7311-4af8-bfb3-859558542b36", "b6781586-6346-41cd-935a-a6b1487918fc", "3ce045a0-877b-42aa-8d2c-b4a863336ab8", "a4d98375-215b-4a4d-aee9-3d4370fccc41", "13584542-872b-42d8-b299-866967b5c3ef", "23393935-50c7-4a86-aeea-2b78fd089c5c" ] # for example_id in os_list: # try: # main("os", example_id) # except Exception as e: # logger.error("An error occurred while running the example: %s", e) # continue calc_list = [ # "eb03d19a-b88d-4de4-8a64-ca0ac66f426b", # "0bf05a7d-b28b-44d2-955a-50b41e24012a", # "7a4e4bc8-922c-4c84-865c-25ba34136be1", # "2bd59342-0664-4ccb-ba87-79379096cc08", # "ecb0df7a-4e8d-4a03-b162-053391d3afaf", # "7efeb4b1-3d19-4762-b163-63328d66303b", # "4e6fcf72-daf3-439f-a232-c434ce416af6", # "6054afcb-5bab-4702-90a0-b259b5d3217c", # "abed40dc-063f-4598-8ba5-9fe749c0615d", # "01b269ae-2111-4a07-81fd-3fcd711993b0", # "8b1ce5f2-59d2-4dcc-b0b0-666a714b9a14", # "0cecd4f3-74de-457b-ba94-29ad6b5dafb6", # "4188d3a4-077d-46b7-9c86-23e1a036f6c1", # "51b11269-2ca8-4b2a-9163-f21758420e78", # "7e429b8d-a3f0-4ed0-9b58-08957d00b127", # "347ef137-7eeb-4c80-a3bb-0951f26a8aff", # "6e99a1ad-07d2-4b66-a1ce-ece6d99c20a5", # "3aaa4e37-dc91-482e-99af-132a612d40f3", # "37608790-6147-45d0-9f20-1137bb35703d", # "f9584479-3d0d-4c79-affa-9ad7afdd8850", "d681960f-7bc3-4286-9913-a8812ba3261a", "21df9241-f8d7-4509-b7f1-37e501a823f7", "1334ca3e-f9e3-4db8-9ca7-b4c653be7d17", "357ef137-7eeb-4c80-a3bb-0951f26a8aff", "aa3a8974-2e85-438b-b29e-a64df44deb4b", "a01fbce3-2793-461f-ab86-43680ccbae25", "4f07fbe9-70de-4927-a4d5-bb28bc12c52c", ] # for example_id in calc_list: # try: # main("libreoffice_calc", example_id) # except Exception as e: # logger.error("An error occurred while running the example: %s", e) # continue impress_list = [ "5d901039-a89c-4bfb-967b-bf66f4df075e", "550ce7e7-747b-495f-b122-acdc4d0b8e54", "455d3c66-7dc6-4537-a39a-36d3e9119df7", "af23762e-2bfd-4a1d-aada-20fa8de9ce07", "c59742c0-4323-4b9d-8a02-723c251deaa0", "ef9d12bd-bcee-4ba0-a40e-918400f43ddf", "9ec204e4-f0a3-42f8-8458-b772a6797cab", "0f84bef9-9790-432e-92b7-eece357603fb", "ce88f674-ab7a-43da-9201-468d38539e4a", "3b27600c-3668-4abd-8f84-7bcdebbccbdb", "a097acff-6266-4291-9fbd-137af7ecd439", "bf4e9888-f10f-47af-8dba-76413038b73c", "21760ecb-8f62-40d2-8d85-0cee5725cb72" ] # for example_id in impress_list: # try: # main("libreoffice_impress", example_id) # except Exception as e: # logger.error("An error occurred while running the example: %s", e) # continue vs_code_list = [ "0ed39f63-6049-43d4-ba4d-5fa2fe04a951", "53ad5833-3455-407b-bbc6-45b4c79ab8fb", "eabc805a-bfcf-4460-b250-ac92135819f6", "982d12a5-beab-424f-8d38-d2a48429e511", "4e60007a-f5be-4bfc-9723-c39affa0a6d3", "e2b5e914-ffe1-44d2-8e92-58f8c5d92bb2", "9439a27b-18ae-42d8-9778-5f68f891805e", "ea98c5d7-3cf9-4f9b-8ad3-366b58e0fcae", "930fdb3b-11a8-46fe-9bac-577332e2640e", "276cc624-87ea-4f08-ab93-f770e3790175", "9d425400-e9b2-4424-9a4b-d4c7abac4140" ] # for example_id in vs_code_list: # try: # main("vs_code", example_id) # except Exception as e: # logger.error("An error occurred while running the example: %s", e) # continue multiple_list = [ "f8cfa149-d1c1-4215-8dac-4a0932bad3c2", "897e3b53-5d4d-444b-85cb-2cdc8a97d903", "4e9f0faf-2ecc-4ae8-a804-28c9a75d1ddc", "b52b40a5-ad70-4c53-b5b0-5650a8387052", "46407397-a7d5-4c6b-92c6-dbe038b1457b", "2b9493d7-49b8-493a-a71b-56cd1f4d6908", "51f5801c-18b3-4f25-b0c3-02f85507a078", "2c9fc0de-3ee7-45e1-a5df-c86206ad78b5", "510f64c8-9bcc-4be1-8d30-638705850618", "937087b6-f668-4ba6-9110-60682ee33441", "ee9a3c83-f437-4879-8918-be5efbb9fac7", "3680a5ee-6870-426a-a997-eba929a0d25c", "e135df7c-7687-4ac0-a5f0-76b74438b53e", "58565672-7bfe-48ab-b828-db349231de6b", "2fe4b718-3bd7-46ec-bdce-b184f5653624" ] for example_id in multiple_list: try: main("multi_apps", example_id) except Exception as e: logger.error("An error occurred while running the example: %s", e) continue