Update app.py

app.py

@@ -12,11 +12,15 @@ dataset_api = project.get_dataset_api()
 dataset_api.download("Resources/batch_data_predictions.csv")
 dataset = load_dataset("csv", data_files="batch_data_predictions.csv")
 predictions_df = pd.DataFrame(dataset,columns=['Headlines', 'URL','Predictions'],)
-predictions_df_url = predictions_df['URL']
+predictions_df_url0 = predictions_df['URL'][0]
+predictions_df_url1 = predictions_df['URL'][1]
+predictions_df_url2 = predictions_df['URL'][3]
+
+
 
 def article_selection(sentiment):
     if sentiment == "Positive":
-        return predictions_df_url #f"""The sentence you requested is Positive!"""
+            return predictions_df_url0, predictions_df_url1, predictions_df_url2 #f"""The sentence you requested is Positive!"""
     #elif sentiment == "Negative":
      #   return f"""The sentence you requested is Negative!""" 
     #else: