update google drive file link in json

desktop_env/evaluators/getters/chrome.py

@@ -1075,8 +1075,8 @@ def get_data_delete_automacally(env, config: Dict[str, str]):
     try:
         content = env.controller.get_file(preference_file_path)
         data = json.loads(content)
-        data_delete_state = data["profile"]["exit_type"]
-        return data_delete_state
+        data_delete_state = data["profile"].get("default_content_setting_values", None)
+        return "true" if data_delete_state is not None else "false"
     except Exception as e:
         logger.error(f"Error: {e}")
         return "Google"

desktop_env/evaluators/metrics/calc.py

@@ -17,8 +17,11 @@ def compare_conference_city_in_order( actual_city_list_path, expected_city):
     print("actual_city_list_path:")
     print(actual_city_list)
     wrong_list = []
-    for i in range(len(actual_city_list)):
-        if expected_city_list[i] not in actual_city_list[i]:
-            wrong_list.append(i)
-            print(f"Expected city {expected_city_list[i]}; Actual city {actual_city_list[i]}")
+    try:
+        for i in range(len(actual_city_list)):
+            if expected_city_list[i] not in actual_city_list[i]:
+                wrong_list.append(i)
+                print(f"Expected city {expected_city_list[i]}; Actual city {actual_city_list[i]}")
+    except:
+        return False
     return True if len(wrong_list) == 0 else False

desktop_env/evaluators/metrics/general.py

@@ -98,13 +98,16 @@ def fuzzy_place_math(result_file_path, rules) -> float:
     for para in doc.paragraphs:
         words_list.extend(para.text.split())
     # Print out the list of extracted words
+    print("Your Answers: ")
     print(words_list)
+    fuzzy_score_list = []
     for word in words_list:
-        if not any(ans in word for ans in expect):
-            print("Wrong place:", word)
-            return 0
-    return 1
-
+        max_score = 0
+        for ans in expect:
+            score = fuzz.ratio(word, ans)
+            max_score = max(max_score, score)
+        fuzzy_score_list.append(max_score)
+    return sum(fuzzy_score_list) / len(fuzzy_score_list)
 
 def check_csv(result: str, rules: Dict[str, List[Dict[str, str]]]) -> float:
     """