try feeback block again

app.py

@@ -22,18 +22,18 @@ def chat(message, history):
 
 
 def feedback(text):
-    # # tokenized_phrases = grammar_tokenizer([text], return_tensors='pt', padding=True)
-    # # corrections = grammar_model.generate(**tokenized_phrases)
-    # # corrections = grammar_tokenizer.batch_decode(corrections, skip_special_tokens=True)
-    # batch =  grammar_tokenizer([text],truncation=True,padding='max_length',max_length=64, return_tensors="pt").to(torch_device)
-    # corrections= grammar_model.generate(**batch,max_length=64,num_beams=2, num_return_sequences=num_return_sequences, temperature=1.5)
-    # print("The corrections are: ", corrections)
-    # if len(corrections) == 0:
-    #     feedback = f'Looks good! Keep up the good work'
-    # else:
-    #     suggestion = tokenizer.batch_decode(corrections[0], skip_special_tokens=True)
-    #     feedback = f'\'{suggestion}\' might be a little better'
-    # return f'FEEDBACK:  {feedback}'
+    # tokenized_phrases = grammar_tokenizer([text], return_tensors='pt', padding=True)
+    # corrections = grammar_model.generate(**tokenized_phrases)
+    # corrections = grammar_tokenizer.batch_decode(corrections, skip_special_tokens=True)
+    batch =  grammar_tokenizer([text],truncation=True,padding='max_length',max_length=64, return_tensors="pt")
+    corrections= grammar_model.generate(**batch,max_length=64,num_beams=2, num_return_sequences=num_return_sequences, temperature=1.5)
+    print("The corrections are: ", corrections)
+    if len(corrections) == 0:
+        feedback = f'Looks good! Keep up the good work'
+    else:
+        suggestion = tokenizer.batch_decode(corrections[0], skip_special_tokens=True)
+        feedback = f'\'{suggestion}\' might be a little better'
+    return f'FEEDBACK:  {feedback}'
     return "Great stuff"
 
 iface = gr.Interface(