Update app.py

app.py

@@ -19,16 +19,23 @@ negative_preds = grouped_predictions.get_group(0)
 def article_selection(sentiment):
     if sentiment == "Positive":
         predictions = negative_preds
-        predictions_urls = predictions['Url'][0:3]
-        return predictions_urls
+        predictions_df_url0 = predictions['Url'].iloc[0]
+        predictions_df_url1 = predictions['Url'].iloc[1]
+        predictions_df_url2 = predictions['Url'].iloc[2]
+        return predictions_df_url0, predictions_df_url1, predictions_df_url2
     elif sentiment == "Negative":
         predictions = negative_preds
-        predictions_urls = predictions['Url'][0:3]
-        return predictions_urls
+        predictions_df_url0 = predictions['Url'].iloc[0]
+        predictions_df_url1 = predictions['Url'].iloc[1]
+        predictions_df_url2 = predictions['Url'].iloc[2]
+        return predictions_df_url0, predictions_df_url1, predictions_df_url2
+
     else:
         predictions = negative_preds
-        predictions_urls = predictions['Url'][0:3]
-        return predictions_urls
+        predictions_df_url0 = predictions['Url'].iloc[0]
+        predictions_df_url1 = predictions['Url'].iloc[1]
+        predictions_df_url2 = predictions['Url'].iloc[2]
+        return predictions_df_url0, predictions_df_url1, predictions_df_url2
 
 def thanks(url, sentiment):
     thanks_text = "Thank you for making our model better!"
@@ -49,7 +56,7 @@ suggestion_demo = gr.Interface(
     fn=article_selection,
     title = 'Recommending News Articles',
     inputs = gr.Dropdown(["Positive","Negative","Neutral"], label="What type of news articles would you like recommended?"),
-    outputs = gr.Textbox(label="Recommended News Articles", lines=3),
+    outputs = [gr.Textbox(label="Recommended News Articles"),gr.Textbox(),gr.Textbox()]
     description = description1
 )