Upload app.py

app.py

@@ -65,15 +65,15 @@ def perform_asde_inference(text, dataset, model_id):
         output = double_keybert_generator.generate(tokenized_text.input_ids,max_length=512)
         result = tokenizer_keybert.decode(output[0], skip_special_tokens=True)
     '''
-        pred_asp = [i.split(':')[0] for i in model_generated.split(',')]
-        pred_sent = [i.split(':')[1] for i in model_generated.split(',')]
-
-        pred_doubles = pd.DataFrame(list(map(list, zip(pred_asp, pred_sent))),columns=['Aspect','Sentiment'])
-        
-        if not text:
-            true_doubles = pd.DataFrame(list(map(list, zip(ast.literal_eval(true_aspect), ast.literal_eval(true_sentiment)))),columns=['Aspect','Sentiment'])
-        else:
-            true_doubles = pd.DataFrame()
+    pred_asp = [i.split(':')[0] for i in model_generated.split(',')]
+    pred_sent = [i.split(':')[1] for i in model_generated.split(',')]
+
+    pred_doubles = pd.DataFrame(list(map(list, zip(pred_asp, pred_sent))),columns=['Aspect','Sentiment'])
+
+    if not text:
+        true_doubles = pd.DataFrame(list(map(list, zip(ast.literal_eval(true_aspect), ast.literal_eval(true_sentiment)))),columns=['Aspect','Sentiment'])
+    else:
+        true_doubles = pd.DataFrame()
 
     return pred_doubles, true_doubles, text, model_generated