Update app.py

app.py

@@ -1,6 +1,7 @@
 import requests
 from bs4 import BeautifulSoup
 import pandas as pd
+import time
 
 class URLValidator:
     """
@@ -18,16 +19,19 @@ class URLValidator:
             response.raise_for_status()
             soup = BeautifulSoup(response.text, "html.parser")
             return " ".join([p.text for p in soup.find_all("p")])
-        except requests.RequestException:
+        except requests.RequestException as e:
+            print(f"Error fetching URL: {url} - {e}")
             return ""
 
     def get_domain_trust(self, url: str) -> int:
         """ Simulated function to assess domain trust. """
-        return len(url) % 5 + 1  # Mock domain trust rating (1-5)
+        return (len(url) % 5) + 1  # Mock domain trust rating (1-5)
 
     def compute_similarity_score(self, user_query: str, content: str) -> int:
         """ Simulated function to compute similarity between user query and content. """
-        return len(user_query) % 5 + 1  # Mock similarity rating (1-5)
+        if not content:
+            return 1  # If no content, assign lowest rating
+        return (len(user_query) % 5) + 1  # Mock similarity rating (1-5)
 
     def rate_url_validity(self, user_query: str, url: str) -> int:
         """ Evaluates webpage credibility based on multiple scores. """
@@ -73,7 +77,7 @@ validator = URLValidator()
 data_rows = []
 for query, url in zip(sample_queries, sample_urls):
     func_rating = validator.rate_url_validity(query, url)
-    custom_rating = func_rating + 1 if func_rating < 5 else func_rating  # Adjusted user rating
+    custom_rating = min(func_rating + 1, 5)  # Adjusted user rating, max 5
     data_rows.append([query, url, func_rating, custom_rating])
 
 # Create DataFrame and Save to CSV
@@ -81,4 +85,8 @@ csv_filename = "url_validation_results.csv"
 df = pd.DataFrame(data_rows, columns=["user_prompt", "url_to_check", "func_rating", "custom_rating"])
 df.to_csv(csv_filename, index=False)
 
-print(f"CSV file '{csv_filename}' has been created successfully!")
+print(f"✅ CSV file '{csv_filename}' has been created successfully!")
+
+# Keep the app running so Hugging Face Space does not stop
+while True:
+    time.sleep(60)  # Keep running indefinitely