Update app.py

app.py

@@ -146,8 +146,18 @@ def user_input(user_question, api_key):
     model = AutoModelForCausalLM.from_pretrained(model_name_or_path)
     tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
 
+    # Define the prompt template
+    prompt_template = f"""
+    Transform the following response into a more conversational tone without adding new information:
+    
+    Response:
+    {response_gemini["output_text"]}
+    
+    Transformed Response:
+    """
+
     # Tokenize the prompt
-    inputs = tokenizer(prompt_template.format(response_gemini["output_text"]), return_tensors="pt", max_length=100, truncation=True)
+    inputs = tokenizer(prompt_template, return_tensors="pt", max_length=100, truncation=True)
 
     # Generate the transformed response using the Hugging Face model
     outputs = model.generate(**inputs)
@@ -156,10 +166,8 @@ def user_input(user_question, api_key):
     transformed_response = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
     # Display the transformed response
-    st.write("Reply: ", transformed_response)
+    st.write("Reply: ", transforme
 
-    # Update chat history
-    update_chat_history(user_question, transformed_response)