Upload app.py

app.py

@@ -34,14 +34,9 @@ def perform_asde_inference(text, dataset, model_id):
         df = pd.read_csv('pyabsa_english.csv')
         random_i = np.random.randint(low=0, high=df.shape[0], size=(1,)).flat[0]
         selected_df = df.iloc[random_i]
-        print(selected_df.head())
-        print(type(selected_df['clean_text']))
-        print(selected_df['clean_text'])
-        print(selected_df['actual_aspects'])
-        print(selected_df['actual_sentiments'])
-        text = str(selected_df['clean_text'].iloc[0])
-        true_aspect = str(selected_df['actual_aspects'].iloc[0])
-        true_sentiment = str(selected_df['actual_sentiments'].iloc[0])
+        text = selected_df['clean_text']
+        true_aspect = selected_df['actual_aspects']
+        true_sentiment = selected_df['actual_sentiments']
         
 
     bos_instruction = """Definition: The output will be the aspects (both implicit and explicit) and the aspects sentiment polarity. In cases where there are no aspects the output should be noaspectterm:none.