Update app.py

app.py

@@ -10,21 +10,22 @@ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
 def generate_questions(email):
   """Generates questions based on the input email."""
-  # Encode the email with tokenizer
-  inputs = tokenizer(email, return_tensors="pt")
+  # Encode the email and prompt together with tokenizer
+  inputs = tokenizer(email, return_tensors="pt", add_special_tokens=True)
+  inputs["input_ids"] = [tokenizer.cls_token_id] + inputs["input_ids"]  # Add CLS token at the beginning
 
-  # Generate questions using model with specific prompt
+  # Generate questions using model
   generation = model.generate(
-      input_ids=inputs["input_ids"],
+      **inputs,  # Unpack the entire inputs dictionary
       max_length=256,  # Adjust max length as needed
       num_beams=5,  # Adjust beam search for better quality (slower)
       early_stopping=True,
-      prompt="What are the important questions or things that need to be addressed in this email:\n",
   )
 
   # Decode the generated text
   return tokenizer.decode(generation[0], skip_special_tokens=True)
 
+
 def generate_answers(questions):
   """Generates possible answers to the input questions."""
   # Encode each question with tokenizer, separated by newline