Update app.py

app.py

@@ -27,11 +27,13 @@ def predict(text):
     df_sum=pd.DataFrame(pred1)
     
     df_sum
+    df_sum['score_finetuned_CBERT']=df_sum['score']
     df_sum2=pd.DataFrame(pred2)
-    
+    df_sum2['score_Bio_CBERT']=df_sum2['score']
     df_sum2
 
     df_sum3= pd.DataFrame(pred3)
+    df_sum3['score_CBERT']=df_sum3['score']
     
     # # join the two dataframes on token do outer join
     
@@ -42,14 +44,14 @@ def predict(text):
     df_join['sum_sequence']=df_join['sequence_x'].fillna(df_join['sequence_y'])
     df_join['sum_sequence']=df_join['sum_sequence'].fillna(df_join['sequence'])
     df_join=df_join.fillna(0)
-    df_join['score_sum']=(df_join['score_x']+df_join['score_y']+df_join['score'])/3
+    df_join['score_average']=(df_join['score_finetuned_CBERT']+df_join['score_Bio_CBERT']+df_join['score_CBERT'])/3
     
-    df_join=df_join.sort_values(by='score_sum',ascending=False)
+    df_join=df_join.sort_values(by='score_average',ascending=False)
     df_join=df_join.reset_index(drop=True)
     # df_join=df_join.dropna()
     # df_join=df_join.fillna(0)
     df=df_join.copy()
-    df_join=df_join[['score_sum','token_str','sum_sequence']]
+    df_join=df_join[['score_finetuned_CBERT','score_Bio_CBERT','score_CBERT','score_average','token_str']]
 
     # gr.Interface(fn=lambda: df_join, inputs=None, outputs=gr.Dataframe(headers=df_join.columns)).launch()
     
@@ -69,9 +71,9 @@ demo = gr.Interface(
 
      # outputs=gr.Dataframe(headers=['title', 'author', 'text']), allow_flagging='never')
 
-  title="Filling Missing Clinincal/Medical Data ",
+  title="Filling Missing Clinical/Medical Data ",
     examples=[ ['The  high blood pressure was due to [MASK]  which is critical.'],
-              ['The [MASK] caused headace and dizziness.']
+              ['The  patient is suffering from throat infection causing [MASK] and cough.']
              ],
     description="This application fills any missing words in the medical domain",
   # fn=lambda: df, inputs=None, outputs=gr.Dataframe(headers=df_join.columns)