Update app.py

app.py

@@ -17,9 +17,17 @@ def fetch_data_to_dataframe(query, limit=50):
         
         # Calculate z-scores of `df['Price']`
         df['z_score'] = stats.zscore(df['Price'])
-        
         # Filter out rows where z-score is greater than 2
-        df_filtered = df[df['z_score'] <= 2].drop(columns=['z_score'])
+        df_filtered = df[df['z_score'] <= 2]
+        
+        # Further filter df_filtered to keep titles closely matching the query
+        # Split the query into keywords and check if each title contains them
+        keywords = query.lower().split()
+        # Assuming all keywords in the query must be present in the title for it to be considered relevant
+        for keyword in keywords:
+            df_filtered = df_filtered[df_filtered['Title'].str.lower().str.contains(keyword)]
+        
+        df_filtered = df_filtered.drop(columns=['z_score'])
         
         median_price = df_filtered['Price'].median()
         return median_price, df_filtered