feat: refactor run_multienv_qwen25vl.py and qwen25vl_agent.py for improved logging and task management

- Introduced signal handling for graceful shutdown of environments and processes.
- Enhanced logging configuration to support dynamic log levels and structured output.
- Updated argument parsing to include new parameters for model selection and task execution.
- Refactored task distribution logic to streamline environment task management.
- Improved error handling during task execution and environment cleanup.
- Adjusted Qwen25VLAgent initialization to support new model and thought prefix options.
- Reduced max tries for LLM calls to optimize performance.
This commit is contained in:
yuanmengqi
2025-07-22 19:46:42 +00:00
parent 4a5d48000f
commit 82c3cdd590
2 changed files with 383 additions and 207 deletions

View File

@@ -66,25 +66,24 @@ class Qwen25VLAgent:
def __init__( def __init__(
self, self,
platform="ubuntu", platform="ubuntu",
planner_model="gpt-4o", model="qwen2.5-vl-72b-instruct",
executor_model="qwen2.5vl",
max_tokens=1500, max_tokens=1500,
top_p=0.9, top_p=0.9,
temperature=0.5, temperature=0.5,
action_space="pyautogui", action_space="pyautogui",
observation_type="screenshot", observation_type="screenshot",
history_n=4, # Number of previous interactions to include in full detail history_n=4, # Number of previous interactions to include in full detail
add_thought_prefix=False,
): ):
self.platform = platform self.platform = platform
self.planner_model = planner_model self.model = model
self.executor_model = executor_model
assert self.executor_model is not None, "Executor model cannot be None"
self.max_tokens = max_tokens self.max_tokens = max_tokens
self.top_p = top_p self.top_p = top_p
self.temperature = temperature self.temperature = temperature
self.action_space = action_space self.action_space = action_space
self.observation_type = observation_type self.observation_type = observation_type
self.history_n = history_n # Control how many previous interactions to include self.history_n = history_n # Control how many previous interactions to include
self.add_thought_prefix = add_thought_prefix
assert action_space in ["pyautogui"], "Invalid action space" assert action_space in ["pyautogui"], "Invalid action space"
assert observation_type in ["screenshot"], "Invalid observation type" assert observation_type in ["screenshot"], "Invalid observation type"
self.thoughts = [] self.thoughts = []
@@ -277,19 +276,20 @@ Previous actions:
}) })
# append_text = f"""Step {current_step+1}: Thought:""" # append_text = f"""Step {current_step+1}: Thought:"""
append_text = f"""Thought:""" if self.add_thought_prefix:
messages.append({"role": "assistant", "content": [{"type": "text", "text": append_text}]}) append_text = f"""Thought:"""
messages.append({"role": "assistant", "content": [{"type": "text", "text": append_text}]})
# Call the LLM # Call the LLM
response = self.call_llm( response = self.call_llm(
{ {
"model": self.executor_model, "model": self.model,
"messages": messages, "messages": messages,
"max_tokens": self.max_tokens, "max_tokens": self.max_tokens,
"top_p": self.top_p, "top_p": self.top_p,
"temperature": self.temperature, "temperature": self.temperature,
}, },
self.executor_model, self.model,
) )
logger.info(f"Qwen25VL Output: {response}") logger.info(f"Qwen25VL Output: {response}")
@@ -483,10 +483,10 @@ Previous actions:
continue continue
# Handle lines inside tool call markers # Handle lines inside tool call markers
if line.startswith("<tool_call>"): if line.startswith("<tool_call>") or line.startswith("") or line.startswith("📐"): # Yeah, it's a bug during data processing
inside_tool_call = True inside_tool_call = True
continue continue
elif line.startswith("</tool_call>"): elif line.startswith("</tool_call>") or line.startswith("") or line.startswith("📐"): # Yeah, it's a bug during data processing
if current_tool_call: if current_tool_call:
# Process the collected tool call # Process the collected tool call
process_tool_call("\n".join(current_tool_call)) process_tool_call("\n".join(current_tool_call))
@@ -540,12 +540,13 @@ Previous actions:
# todo: check # todo: check
), ),
interval=30, interval=30,
max_tries=10, max_tries=5,
) )
def call_llm(self, payload, model): def call_llm(self, payload, model):
messages = payload["messages"] messages = payload["messages"]
base_url = "your_base_url"
api_key = "your_api_key" base_url = os.getenv('DASHSCOPE_BASE_URL', "https://dashscope.aliyuncs.com/compatible-mode/v1")
api_key = os.getenv('DASHSCOPE_API_KEY', "sk-123")
client = openai.OpenAI( client = openai.OpenAI(
base_url=base_url, base_url=base_url,

View File

@@ -1,66 +1,34 @@
"""Script to run end-to-end evaluation on the benchmark. from __future__ import annotations
Utils and basic architecture credit to https://github.com/web-arena-x/webarena/blob/main/run.py.
"""
import argparse import argparse
import datetime import datetime
import json import json
import logging import logging
import os import os
import sys import sys
import signal
import time
from typing import List, Dict from typing import List, Dict
import math import math
from tqdm import tqdm from tqdm import tqdm
from multiprocessing import Process, Manager from multiprocessing import Process, Manager
from multiprocessing import current_process
import lib_run_single import lib_run_single
from desktop_env.desktop_env import DesktopEnv from desktop_env.desktop_env import DesktopEnv
from mm_agents.qwen25vl_agent import Qwen25VLAgent from mm_agents.qwen25vl_agent import Qwen25VLAgent
# Global variables for signal handling
active_environments = []
processes = []
is_terminating = False
# import wandb # import wandb
# load the environment variables from .env file
if os.path.exists(".env"):
from dotenv import load_dotenv
load_dotenv()
# Logger Configs {{{ # # 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")
def config() -> argparse.Namespace: def config() -> argparse.Namespace:
parser = argparse.ArgumentParser( parser = argparse.ArgumentParser(
description="Run end-to-end evaluation on the benchmark" description="Run end-to-end evaluation on the benchmark"
@@ -80,23 +48,22 @@ def config() -> argparse.Namespace:
default="screenshot", default="screenshot",
help="Observation type", help="Observation type",
) )
parser.add_argument("--screen_width", type=int, default=1920) parser.add_argument("--sleep_after_execution", type=float, default=0.0)
parser.add_argument("--screen_height", type=int, default=1080) parser.add_argument("--max_steps", type=int, default=15)
parser.add_argument("--sleep_after_execution", type=float, default=2.0)
parser.add_argument("--max_steps", type=int, default=20)
# agent config # agent config
parser.add_argument("--max_trajectory_length", type=int, default=3)
parser.add_argument( parser.add_argument(
"--test_config_base_dir", type=str, default="evaluation_examples" "--test_config_base_dir", type=str, default="evaluation_examples"
) )
# lm config # lm config
parser.add_argument("--planner_model", type=str, default=None) parser.add_argument("--model", type=str, default="gpt-4o")
parser.add_argument("--executor_model", type=str, default="aguvis-s1-s2-agentnet0105-mo5") parser.add_argument("--temperature", type=float, default=1.0)
parser.add_argument("--temperature", type=float, default=0)
parser.add_argument("--top_p", type=float, default=0.9) parser.add_argument("--top_p", type=float, default=0.9)
parser.add_argument("--max_tokens", type=int, default=1500) parser.add_argument("--max_tokens", type=int, default=1500)
parser.add_argument("--stop_token", type=str, default=None) parser.add_argument("--stop_token", type=str, default=None)
parser.add_argument("--add_thought_prefix", action="store_true", help="Add thought prefix to the response")
# example config # example config
parser.add_argument("--domain", type=str, default="all") parser.add_argument("--domain", type=str, default="all")
@@ -107,151 +74,303 @@ def config() -> argparse.Namespace:
# logging related # logging related
parser.add_argument("--result_dir", type=str, default="./results") parser.add_argument("--result_dir", type=str, default="./results")
parser.add_argument("--num_envs", type=int, default=1, help="Number of environments to run in parallel") parser.add_argument("--num_envs", type=int, default=1, help="Number of environments to run in parallel")
parser.add_argument("--log_level", type=str, choices=['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'],
default='INFO', help="Set the logging level")
# aws config
parser.add_argument(
"--region", type=str, default="us-east-1", help="AWS region for the VM"
)
parser.add_argument(
"--provider_name", type=str, default="aws", choices=["aws", "virtualbox", "vmware", "docker", "azure"], help="Provider name"
)
parser.add_argument(
"--client_password", type=str, default="", help="Client password"
)
parser.add_argument(
"--screen_width", type=int, default=1920, help="Screen width"
)
parser.add_argument(
"--screen_height", type=int, default=1080, help="Screen height"
)
args = parser.parse_args() args = parser.parse_args()
return args return args
args = config() # Get command line arguments first
def distribute_tasks(test_all_meta: dict, num_envs: int) -> List[Dict]: logger = logging.getLogger()
"""Distribute tasks evenly across environments.""" log_level = getattr(logging, args.log_level.upper())
# Flatten the tasks into a single list logger.setLevel(log_level)
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)
file_handler.setLevel(logging.INFO)
debug_handler.setLevel(logging.DEBUG)
stdout_handler.setLevel(log_level)
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)
stdout_handler.addFilter(logging.Filter("desktopenv"))
logger.addHandler(file_handler)
logger.addHandler(debug_handler)
logger.addHandler(stdout_handler)
# }}} Logger Configs #
logger = logging.getLogger("desktopenv.experiment")
def distribute_tasks(test_all_meta: dict) -> List[tuple]:
all_tasks = [] all_tasks = []
for domain, examples in test_all_meta.items(): for domain, examples in test_all_meta.items():
for example_id in examples: for example_id in examples:
all_tasks.append((domain, example_id)) all_tasks.append((domain, example_id))
return all_tasks
# Calculate tasks per environment
tasks_per_env = math.ceil(len(all_tasks) / num_envs)
# Distribute tasks
distributed_tasks = []
for i in range(num_envs):
env_tasks = {}
start_idx = i * tasks_per_env
end_idx = min((i + 1) * tasks_per_env, len(all_tasks))
for domain, example_id in all_tasks[start_idx:end_idx]:
if domain not in env_tasks:
env_tasks[domain] = []
env_tasks[domain].append(example_id)
distributed_tasks.append(env_tasks)
return distributed_tasks
def process_signal_handler(signum, frame, env_idx):
"""Signal handler for child processes to gracefully shut down their environments."""
logger.info(f"Process {env_idx + 1} received signal {signum}. Shutting down...")
def run_env_tasks(env_idx: int, env: DesktopEnv, agent, env_tasks: dict, args: argparse.Namespace, shared_scores: list): # Get the active_environments from the caller's frame
"""Run tasks for a single environment.""" local_vars = frame.f_locals
logger.info(f"Executing tasks in environment {env_idx + 1}/{args.num_envs}") active_environments = local_vars.get('active_environments', [])
for domain in tqdm(env_tasks, desc=f"Env{env_idx+1}-Domain"):
for example_id in tqdm(env_tasks[domain], desc="Example", leave=False):
config_file = os.path.join(
args.test_config_base_dir, f"examples/{domain}/{example_id}.json"
)
with open(config_file, "r", encoding="utf-8") as f:
example = json.load(f)
logger.info(f"[Env {env_idx+1}][Domain]: {domain}")
logger.info(f"[Env {env_idx+1}][Example ID]: {example_id}")
logger.info(f"[Env {env_idx+1}][Instruction]: {example['instruction']}")
example_result_dir = os.path.join(
args.result_dir,
args.action_space,
args.observation_type,
"planner-" + str(args.planner_model) + "-executor-" + str(args.executor_model),
domain,
example_id,
)
os.makedirs(example_result_dir, exist_ok=True)
# Close environment in the current process context
for env in active_environments:
if env is not None:
try: try:
lib_run_single.run_single_example( logger.info(f"Process {env_idx + 1} closing environment...")
agent, env.close()
env, logger.info(f"Process {env_idx + 1} environment closed successfully")
example,
args.max_steps,
example["instruction"],
args,
example_result_dir,
shared_scores,
)
except Exception as e: except Exception as e:
logger.error(f"Exception in Env{env_idx+1} {domain}/{example_id}: {e}") logger.error(f"Process {env_idx + 1} error closing environment: {e}")
env.controller.end_recording(
os.path.join(example_result_dir, "recording.mp4")
)
with open(os.path.join(example_result_dir, "traj.jsonl"), "a") as f:
f.write(
json.dumps(
{"Error": f"Time limit exceeded in {domain}/{example_id}"}
)
)
f.write("\n")
env.close() logger.info(f"Process {env_idx + 1} shutdown complete. Exiting.")
sys.exit(0)
def test(args: argparse.Namespace, test_all_meta: dict) -> None: def run_env_tasks(task_queue: Queue, args: argparse.Namespace, shared_scores: list):
logger.info("Args: %s", args) active_environments = []
env = None
distributed_tasks = distribute_tasks(test_all_meta, args.num_envs) try:
from desktop_env.providers.aws.manager import IMAGE_ID_MAP
# First, set up all environments REGION = args.region
logger.info("Setting up all environments...") screen_size = (args.screen_width, args.screen_height)
envs = [] ami_id = IMAGE_ID_MAP[REGION].get(screen_size, IMAGE_ID_MAP[REGION][(1920, 1080)])
agents = [] env = DesktopEnv(
path_to_vm=args.path_to_vm,
for env_idx in range(args.num_envs): action_space=args.action_space,
logger.info(f"Setting up environment {env_idx + 1}/{args.num_envs}") provider_name=args.provider_name,
region=REGION,
snapshot_name=ami_id,
screen_size=screen_size,
headless=args.headless,
os_type="Ubuntu",
require_a11y_tree=args.observation_type in ["a11y_tree", "screenshot_a11y_tree", "som"],
enable_proxy=True,
client_password=args.client_password
)
active_environments.append(env)
agent = Qwen25VLAgent( agent = Qwen25VLAgent(
planner_model=args.planner_model, model=args.model,
executor_model=args.executor_model,
max_tokens=args.max_tokens, max_tokens=args.max_tokens,
top_p=args.top_p, top_p=args.top_p,
temperature=args.temperature, temperature=args.temperature,
action_space=args.action_space, action_space=args.action_space,
add_thought_prefix=args.add_thought_prefix,
) )
agents.append(agent) logger.info(f"Process {current_process().name} started.")
while True:
try:
item = task_queue.get(timeout=5)
except Exception:
break
domain, example_id = item
try:
config_file = os.path.join(
args.test_config_base_dir, f"examples/{domain}/{example_id}.json"
)
with open(config_file, "r", encoding="utf-8") as f:
example = json.load(f)
logger.info(f"[{current_process().name}][Domain]: {domain}")
logger.info(f"[{current_process().name}][Example ID]: {example_id}")
logger.info(f"[{current_process().name}][Instruction]: {example['instruction']}")
example_result_dir = os.path.join(
args.result_dir,
args.action_space,
args.observation_type,
args.model,
domain,
example_id,
)
os.makedirs(example_result_dir, exist_ok=True)
try:
lib_run_single.run_single_example(
agent,
env,
example,
args.max_steps,
example["instruction"],
args,
example_result_dir,
shared_scores,
)
except Exception as e:
import traceback
logger.error(f"Exception in {current_process().name} {domain}/{example_id}: {e}")
logger.error(traceback.format_exc())
try:
env.controller.end_recording(
os.path.join(example_result_dir, "recording.mp4")
)
except Exception as rec_e:
logger.error(f"Failed to end recording: {rec_e}")
with open(os.path.join(example_result_dir, "traj.jsonl"), "a") as f:
f.write(
json.dumps(
{"Error": f"{domain}/{example_id} - {e}"}
)
)
f.write("\n")
except Exception as e:
logger.error(f"Task-level error in {current_process().name}: {e}")
import traceback
logger.error(traceback.format_exc())
except Exception as e:
logger.error(f"Process-level error in {current_process().name}: {e}")
import traceback
logger.error(traceback.format_exc())
finally:
logger.info(f"{current_process().name} cleaning up environment...")
try:
if env:
env.close()
logger.info(f"{current_process().name} environment closed successfully")
except Exception as e:
logger.error(f"{current_process().name} error during environment cleanup: {e}")
env = DesktopEnv(
path_to_vm=args.path_to_vm,
action_space=agent.action_space,
screen_size=(args.screen_width, args.screen_height),
headless=args.headless,
os_type="Ubuntu",
require_a11y_tree=args.observation_type
in ["a11y_tree", "screenshot_a11y_tree", "som"],
provider_name="docker"
)
envs.append(env)
logger.info("All environments are ready. Starting parallel task execution...") def signal_handler(signum, frame):
"""Handle termination signals (SIGINT, SIGTERM) to gracefully shutdown environments."""
global is_terminating, active_environments, processes
# Create a shared list for scores across processes # Avoid duplicate handling
if is_terminating:
return
is_terminating = True
logger.info(f"Received signal {signum}. Gracefully shutting down...")
# Close all registered environments in the main process
for env in active_environments:
try:
logger.info(f"Closing environment...")
env.close()
logger.info(f"Environment closed successfully")
except Exception as e:
logger.error(f"Error closing environment: {e}")
# Send termination signal to all child processes first
for p in processes:
if p.is_alive():
try:
logger.info(f"Sending termination signal to process {p.name}...")
p.terminate()
except Exception as e:
logger.error(f"Error sending termination signal to process: {e}")
# Allow a short time for processes to handle their own cleanup
time.sleep(1)
# Forcefully terminate any processes that didn't exit
for p in processes:
if p.is_alive():
try:
logger.info(f"Forcefully terminating process {p.name}...")
import signal as sig
os.kill(p.pid, sig.SIGKILL)
except Exception as e:
logger.error(f"Error forcefully terminating process: {e}")
logger.info("Shutdown complete. Exiting.")
sys.exit(0)
def test(args: argparse.Namespace, test_all_meta: dict) -> None:
global processes
logger.info("Args: %s", args)
all_tasks = distribute_tasks(test_all_meta)
logger.info(f"Total tasks: {len(all_tasks)}")
with Manager() as manager: with Manager() as manager:
shared_scores = manager.list() shared_scores = manager.list()
task_queue = manager.Queue()
# Create and start processes for each environment for item in all_tasks:
task_queue.put(item)
num_envs = args.num_envs
processes = [] processes = []
for env_idx, (env, agent, env_tasks) in enumerate(zip(envs, agents, distributed_tasks)): for i in range(num_envs):
p = Process( p = Process(
target=run_env_tasks, target=run_env_tasks,
args=(env_idx, env, agent, env_tasks, args, shared_scores) args=(task_queue, args, shared_scores),
name=f"EnvProcess-{i+1}"
) )
processes.append(p) p.daemon = True
p.start() p.start()
processes.append(p)
# Wait for all processes to complete logger.info(f"Started process {p.name} with PID {p.pid}")
for p in processes: try:
p.join() while True:
alive_count = 0
# Convert shared list to regular list for idx, p in enumerate(processes):
if not p.is_alive():
logger.warning(f"Process {p.name} died, restarting...")
new_p = Process(
target=run_env_tasks,
args=(task_queue, args, shared_scores),
name=f"EnvProcess-Restart-{idx+1}"
)
new_p.daemon = True
new_p.start()
processes[idx] = new_p
logger.info(f"Restarted process {new_p.name} with PID {new_p.pid}")
else:
alive_count += 1
if task_queue.empty():
logger.info("All tasks finished.")
break
if alive_count == 0:
logger.error("All processes died, exiting.")
break
time.sleep(5)
for p in processes:
p.join()
except KeyboardInterrupt:
logger.info("Main process received KeyboardInterrupt. Initiating graceful shutdown...")
raise
except Exception as e:
logger.error(f"Unexpected error while waiting for processes: {e}", exc_info=True)
for p in processes:
if p.is_alive():
try:
logger.info(f"Terminating process {p.name} due to error...")
p.terminate()
except Exception as term_e:
logger.error(f"Error terminating process {p.name}: {term_e}")
raise
scores = list(shared_scores) scores = list(shared_scores)
logger.info(f"Average score: {sum(scores) / len(scores) if scores else 0}") logger.info(f"Average score: {sum(scores) / len(scores) if scores else 0}")
@@ -330,33 +449,89 @@ def get_result(action_space, use_model, observation_type, result_dir, total_file
if __name__ == "__main__": if __name__ == "__main__":
####### The complete version of the list of examples ####### ####### The complete version of the list of examples #######
os.environ["TOKENIZERS_PARALLELISM"] = "false" os.environ["TOKENIZERS_PARALLELISM"] = "false"
args = config()
with open(args.test_all_meta_path, "r", encoding="utf-8") as f: # Register signal handlers for graceful termination
test_all_meta = json.load(f) signal.signal(signal.SIGINT, signal_handler) # Handle Ctrl+C
signal.signal(signal.SIGTERM, signal_handler) # Handle termination signal
if args.domain != "all": try:
test_all_meta = {args.domain: test_all_meta[args.domain]} args = config()
exp_name = "planner-" + str(args.planner_model) + "-executor-" + str(args.executor_model) # 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)
test_file_list = get_unfinished( with open(args.test_all_meta_path, "r", encoding="utf-8") as f:
args.action_space, test_all_meta = json.load(f)
exp_name,
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( if args.domain != "all":
args.action_space, test_all_meta = {args.domain: test_all_meta[args.domain]}
exp_name,
args.observation_type, test_file_list = get_unfinished(
args.result_dir, args.action_space,
test_all_meta, args.model,
) args.observation_type,
test(args, test_file_list) 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(args, test_file_list)
except KeyboardInterrupt:
logger.info("Main process received KeyboardInterrupt.")
# Signal handler will take care of cleanup
except Exception as e:
logger.error(f"Unexpected error in main process: {e}", exc_info=True)
# Also trigger cleanup for unhandled exceptions
signal_handler(signal.SIGTERM, None)
finally:
# Final cleanup in case any environments or processes remain
logger.info("Main process final cleanup...")
for env in active_environments:
if env is not None:
try:
logger.info(f"Closing environment in final cleanup...")
env.close()
logger.info(f"Environment closed successfully in final cleanup")
except Exception as e:
logger.error(f"Error during final environment cleanup: {e}")
# First try gentle termination
for p in processes:
if p is not None and p.is_alive():
try:
logger.info(f"Terminating process {p.name}...")
p.terminate()
except Exception as e:
logger.error(f"Error terminating process: {e}")
# Wait a moment for processes to terminate
time.sleep(1)
# Then force kill if needed
for p in processes:
if p is not None and p.is_alive():
try:
logger.info(f"Force killing process {p.name}...")
os.kill(p.pid, signal.SIGKILL)
logger.info(f"Process {p.name} force killed")
except Exception as e:
logger.error(f"Error force killing process: {e}")