Update app.py

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
 import hopsworks
 from datasets import load_dataset
+import numpy as np 
+import pandas as pd
 
 project = hopsworks.login()
 fs = project.get_feature_store()
@@ -9,10 +11,12 @@ 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']
 
 def article_selection(sentiment):
     if sentiment == "Positive":
-        return dataset #f"""The sentence you requested is Positive!"""
+        return predictions_df_url #f"""The sentence you requested is Positive!"""
     #elif sentiment == "Negative":
      #   return f"""The sentence you requested is Negative!""" 
     #else: