Update app.py

app.py

@@ -23,8 +23,8 @@ def inference(text):
     result = pd.DataFrame({
         'aspect': result[0]['aspect'],
         'sentiment': result[0]['sentiment'],
-        'confidence': round(result[0]['confidence'], 3),
-        'ref_sentiment': result[0]['ref_sentiment'],
+        'confidence': [round(c, 3) for c in result[0]['confidence']],
+        'ref_sentiment': ['' if ref == '-999' else ref for ref in result[0]['ref_sentiment']],
         'is_correct': result[0]['ref_check'],
     })
 
@@ -36,13 +36,10 @@ if __name__ == '__main__':
         fn=inference,
         inputs=["text"],
         examples=[
-            ['The [ASP]battery-life[ASP], and this [ASP]screen[ASP] is ok'],
-            ['The [ASP] battery-life [ASP] is bad'],
-            ['The [ASP] battery-life [ASP] is good'],
             ['Strong build though which really adds to its [ASP]durability[ASP] .'],  # !sent! Positive
             ['Strong [ASP]build[ASP] though which really adds to its durability . !sent! Positive'],
             ['The [ASP]battery life[ASP] is excellent - 6-7 hours without charging . !sent! Positive'],
-            ['I have had my computer for 2 weeks already and it [ASP]works[ASP] perfectly . !sent! Positive'],
+            ['I have had my [ASP]computer[ASP] for 2 weeks already and it [ASP]works[ASP] perfectly . !sent!  Positive, Positive'],
             ['And I may be the only one but I am really liking [ASP]Windows 8[ASP] . !sent! Positive'],
             ['This demo is trained on the laptop and restaurant and other review datasets from [ASP]ABSADatasets[ASP] (https://github.com/yangheng95/ABSADatasets)'],
             ['To fit on your data, please train the model on your own data, see the [ASP]PyABSA[ASP] (https://github.com/yangheng95/PyABSA)'],