Update app.py

app.py

@@ -270,7 +270,8 @@ def analyze_competitors(row, co):
     our_url = row['page']
     our_score = row['relevancy_score']
     
-    competitor_urls = get_serp_results(query)[:5]  # Get top 5 competitors
+    competitor_urls = get_serp_results(query)
+    competitor_urls = [url for url in competitor_urls if not url.startswith('/search')][:5]  # Get top 5 valid competitors
     
     results = []
     for url in competitor_urls:
@@ -504,7 +505,8 @@ def show_tabular_data(df, co):
         our_url = row['page']
         our_score = row['relevancy_score']
         
-        competitor_urls = get_serp_results(query)[:5]  # Get top 5 competitors
+        competitor_urls = get_serp_results(query)
+        competitor_urls = [url for url in competitor_urls if not url.startswith('/search')][:5]  # Get top 5 valid competitors
         
         results = []
         for url in competitor_urls:
@@ -543,7 +545,15 @@ def show_tabular_data(df, co):
                     st.dataframe(results_df)
                     
                     our_rank = results_df.index[results_df['url'] == row['page']].tolist()[0] + 1
-                    st.write(f"Our page ranks {our_rank} out of {len(results_df)} in terms of relevancy score.")
+                    total_results = len(results_df)
+                    st.write(f"Our page ranks {our_rank} out of {total_results} in terms of relevancy score.")
+                    
+                    if our_rank == 1:
+                        st.success("Your page has the highest relevancy score!")
+                    elif our_rank <= 3:
+                        st.info("Your page is among the top 3 most relevant results.")
+                    elif our_rank > total_results / 2:
+                        st.warning("Your page's relevancy score is in the lower half of the results. Consider optimizing your content.")
 
     return df  # Return the updated dataframe