Update app.py

app.py

@@ -177,11 +177,14 @@ def analyze_competitors(row, co):
     
     results = []
     for url in competitor_urls:
-        content = fetch_content(url)
-        score = calculate_relevance_score(content, query, co)
-        results.append({'url': url, 'relevancy_score': score})
+        if url != our_url:  # Skip our URL if it's in the SERP results
+            content = fetch_content(url)
+            score = calculate_relevance_score(content, query, co)
+            results.append({'url': url, 'relevancy_score': score})
     
+    # Add our page's data
     results.append({'url': our_url, 'relevancy_score': our_score})
+    
     results_df = pd.DataFrame(results).sort_values('relevancy_score', ascending=False)
     
     logger.info(f"Competitor analysis completed. {len(results)} results obtained.")
@@ -196,8 +199,16 @@ def show_competitor_analysis(row, co):
             st.dataframe(results_df)
             
             our_rank = results_df.index[results_df['url'] == row['page']].tolist()[0] + 1
-            logger.info(f"Our page ranks {our_rank} out of {len(results_df)} in terms of relevancy score.")
-            st.write(f"Our page ranks {our_rank} out of {len(results_df)} in terms of relevancy score.")
+            total_results = len(results_df)
+            logger.info(f"Our page ranks {our_rank} out of {total_results} in terms of relevancy score.")
+            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.")
 
 
 def analyze_competitors(row, co):