Update utils.py

utils.py

@@ -10,7 +10,7 @@ import numpy as np
 import asyncio
 import nltk
 from sentence_transformers import SentenceTransformer, util
-import signal
+import threading
 
 nltk.download('punkt')
 
@@ -193,33 +193,38 @@ async def parallel_scrap(urls):
 class TimeoutError(Exception):
     pass
 
-
-def signal_handler(signum, frame):
-    raise TimeoutError("Function timed out")
     
 
 def matchingScore(sentence, content):
-    signal.signal(signal.SIGALRM, signal_handler)
-    signal.alarm(10)  # Set alarm for 10 seconds
+    if sentence in content:
+        return 1
+    sentence = removePunc(sentence)
+    content = removePunc(content)
+    if sentence in content:
+        return 1
+    else:
+        n = 5
+        ngrams = getQueries(sentence, n)
+        print("ngrams done.......")
+        if len(ngrams) == 0:
+            return 0
+        matched = [x for x in ngrams if " ".join(x) in content]
+    return len(matched) / len(ngrams)
+
+
+def matchingScoreWithTimeout(sentence, content):
+    def timeout_handler():
+        raise TimeoutError("Function timed out")
+
+    timer = threading.Timer(10, timeout_handler)  # Set a timer for 10 seconds
+    timer.start()
 
     try:
-        if sentence in content:
-            return 1
-        sentence = removePunc(sentence)
-        content = removePunc(content)
-        if sentence in content:
-            return 1
-        else:
-            n = 5
-            ngrams = getQueries(sentence, n)
-            print("ngrams done.......")
-            if len(ngrams) == 0:
-                return 0
-            matched = [x for x in ngrams if " ".join(x) in content]
-            signal.alarm(0)  # Cancel the alarm if calculation completes before timeout
-            return len(matched) / len(ngrams)
+        score = matchingScore(sentence, content)
+        timer.cancel()  # Cancel the timer if calculation completes before timeout
+        return score
     except TimeoutError:
-        return 0
+        return 0    
 
 
 async def matchingScoreAsync(sentences, content, content_idx, ScoreArray):