Files
sci-gui-agent-benchmark/experiment_screenshot_a11y_tree.py
2024-01-31 23:50:45 +08:00

292 lines
11 KiB
Python

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