Update app.py

app.py

@@ -11,14 +11,14 @@ dataset_api = project.get_dataset_api()
 dataset = load_dataset("torileatherman/sentiment_analysis_batch_predictions", split='train')
 predictions_df = pd.DataFrame(dataset)
 grouped_predictions = predictions_df.groupby(predictions_df.Sentiment)
-positive_preds = grouped_predictions.get_group(2)
-neutral_preds = grouped_predictions.get_group(1)
+#positive_preds = grouped_predictions.get_group(2)
+#neutral_preds = grouped_predictions.get_group(1)
 negative_preds = grouped_predictions.get_group(0)
 
 
 def article_selection(sentiment):
     if sentiment == "Positive":
-        predictions = positive_preds
+        predictions = negative_preds
         predictions_urls = predictions['Url'][0:3]
         return predictions_urls
     elif sentiment == "Negative":
@@ -26,7 +26,7 @@ def article_selection(sentiment):
         predictions_urls = predictions['Url'][0:3]
         return predictions_urls
     else:
-        predictions = neutral_preds
+        predictions = negative_preds
         predictions_urls = predictions['Url'][0:3]
         return predictions_urls