Update app.py

app.py

@@ -241,7 +241,7 @@ def calculate_relevance_score(page_content, query, co):
 def normalize_url(url):
     return url.rstrip('/').lower()
 
-def analyze_competitors(row, co, custom_url=None, country_code=None):
+def analyze_competitors(row, co, country_code):
     query = row['query']
     our_url = normalize_url(row['page'])
     
@@ -258,8 +258,12 @@ def analyze_competitors(row, co, custom_url=None, country_code=None):
             'is_our_url': competitor_url == our_url
         })
     
-    our_content = fetch_content(our_url, query)
-    our_score = calculate_relevance_score(our_content, query, co)
+    # Use the existing relevancy score if available, otherwise calculate it
+    if pd.notna(row['relevancy_score']) and row['relevancy_score'] != 0:
+        our_score = row['relevancy_score']
+    else:
+        our_content = fetch_content(our_url, query)
+        our_score = calculate_relevance_score(our_content, query, co)
     
     if not any(r['is_our_url'] for r in results):
         results.append({
@@ -519,7 +523,7 @@ def show_model_type_selector():
         key='model_type_selector'
     )
 
-def calculate_single_relevancy(row):
+def calculate_single_relevancy(row, co):
     page_content = fetch_content(row['page'], row['query'])
     query = row['query']
     score = calculate_relevance_score(page_content, query, co)
@@ -632,7 +636,7 @@ def show_tabular_data(df, co, country_code):
         with st.spinner('Calculating relevancy scores...'):
             for index in selected_indices:
                 if pd.isna(df.iloc[index]['relevancy_score']) or df.iloc[index]['relevancy_score'] == 0:
-                    df.iloc[index, df.columns.get_loc('relevancy_score')] = calculate_single_relevancy(df.iloc[index])
+                    df.iloc[index, df.columns.get_loc('relevancy_score')] = calculate_single_relevancy(df.iloc[index], co)
         st.success(f"Calculated relevancy scores for {len(selected_indices)} selected rows.")
         st.experimental_rerun()
     
@@ -687,6 +691,9 @@ def show_tabular_data(df, co, country_code):
                     our_url_mask = results_df['URL'].str.contains('Our URL')
                     results_df.loc[our_url_mask, 'Position'] = row.position
                     
+                    # Ensure our URL's score matches the main table
+                    results_df.loc[our_url_mask, 'Score'] = row.relevancy_score
+                    
                     # Create a custom style function to highlight only our URL's row
                     def highlight_our_url(row):
                         if 'Our URL' in row['URL']: