add support for mobile agent v3 (#328)

* add support for mobile agent v3

* add mobile_agent

* add support for mobile agent v3

lib_run_single_mobileagent_v3.py

@@ -0,0 +1,73 @@
+import datetime
+import json
+import logging
+import os
+import time
+from wrapt_timeout_decorator import *
+
+logger = logging.getLogger("desktopenv.experiment")
+
+
+def run_single_example(agent, env, example, max_steps, instruction, args, example_result_dir, scores):
+    runtime_logger = setup_logger(example, example_result_dir)
+    try:
+        agent.reset(runtime_logger)
+    except:
+        agent.reset()
+    env.reset(task_config=example)
+    time.sleep(60) # Wait for the environment to be ready
+    obs = env._get_obs() # Get the initial observation
+
+    done = False
+    step_idx = 0
+    
+    # save the first step
+    action_timestamp = datetime.datetime.now().strftime("%Y%m%d@%H%M%S")
+    with open(os.path.join(example_result_dir, f"step_{step_idx}_{action_timestamp}.png"), "wb") as _f:
+        _f.write(obs['screenshot'])
+    
+    eval_flag = True
+    env.controller.start_recording()
+    while not done and step_idx < max_steps:
+        global_state, action_code, step_status, reward, done = agent.step(instruction, env, args)
+        action_timestamp = datetime.datetime.now().strftime("%Y%m%d@%H%M%S")
+
+        if step_status is False:
+            eval_flag = False
+            done = True
+            reward = None
+        else:
+            obs = env._get_obs()
+            with open(os.path.join(example_result_dir, f"step_{step_idx + 1}_{action_timestamp}.png"),
+                        "wb") as _f:
+                _f.write(obs['screenshot'])
+        with open(os.path.join(example_result_dir, "traj.jsonl"), "a") as f:
+            f.write(json.dumps({
+                "step_num": step_idx + 1,
+                "step_status": step_status,
+                "action_timestamp": action_timestamp,
+                "action": action_code,
+                "reward": reward,
+                "done": done,
+                "screenshot_file": f"step_{step_idx + 1}_{action_timestamp}.png",
+            }))
+            f.write("\n")
+        if done:    
+            logger.info("The episode is done.")
+            break
+        step_idx += 1
+
+    if eval_flag:
+        result = env.evaluate()
+        logger.info("Result: %.2f", result)
+        scores.append(result)
+        with open(os.path.join(example_result_dir, "result.txt"), "w", encoding="utf-8") as f:
+            f.write(f"{result}\n")
+    env.controller.end_recording(os.path.join(example_result_dir, "recording.mp4"))
+
+
+def setup_logger(example, example_result_dir):
+    runtime_logger = logging.getLogger(f"desktopenv.example.{example['id']}")
+    runtime_logger.setLevel(logging.DEBUG)
+    runtime_logger.addHandler(logging.FileHandler(os.path.join(example_result_dir, "runtime.log")))
+    return runtime_logger