Update deliverable2.py

deliverable2.py

@@ -79,39 +79,39 @@ class URLValidator:
 
         return " ".join(reasons) if reasons else "This source is highly credible and relevant."
 
-   def rate_url_validity(user_query: str, url: str):
-    """ Main function to evaluate the validity of a webpage. """ 
-    content = fetch_page_content(url)  # ✅ Add a properly indented block here
-
-    # Handle errors
-    if "Error" in content:
-        return {"Validation Error": content}
-
-    domain_trust = get_domain_trust(url, content)
-    similarity_score = compute_similarity_score(user_query, content)
-    fact_check_score = check_facts(content)
-    bias_score = detect_bias(content)
-
-    final_score = (
-        (0.3 * domain_trust) +
-        (0.3 * similarity_score) +
-        (0.2 * fact_check_score) +
-        (0.2 * bias_score)
-    )
-
-    stars, icon = get_star_rating(final_score)
-    explanation = generate_explanation(domain_trust, similarity_score, fact_check_score, bias_score, final_score)
-
-    return {
-        "raw_score": {  
-            "Domain Trust": domain_trust,
-            "Content Relevance": similarity_score,
-            "Fact-Check Score": fact_check_score,
-            "Bias Score": bias_score,
-            "Final Validity Score": final_score
-        },
-        "stars": {
-            "icon": icon
-        },
-        "explanation": explanation
-    }
+    def rate_url_validity(self, user_query: str, url: str):
+        """ Main function to evaluate the validity of a webpage. """ 
+        content = self.fetch_page_content(url)  # ✅ Properly indented and referenced with self
+
+        # Handle errors
+        if "Error" in content:
+            return {"Validation Error": content}
+
+        domain_trust = self.get_domain_trust(url, content)
+        similarity_score = self.compute_similarity_score(user_query, content)
+        fact_check_score = self.check_facts(content)
+        bias_score = self.detect_bias(content)
+
+        final_score = (
+            (0.3 * domain_trust) +
+            (0.3 * similarity_score) +
+            (0.2 * fact_check_score) +
+            (0.2 * bias_score)
+        )
+
+        stars, icon = self.get_star_rating(final_score)
+        explanation = self.generate_explanation(domain_trust, similarity_score, fact_check_score, bias_score, final_score)
+
+        return {
+            "raw_score": {  
+                "Domain Trust": domain_trust,
+                "Content Relevance": similarity_score,
+                "Fact-Check Score": fact_check_score,
+                "Bias Score": bias_score,
+                "Final Validity Score": final_score
+            },
+            "stars": {
+                "icon": icon
+            },
+            "explanation": explanation
+        }