Update app.py

updating prompt

app.py

@@ -5,7 +5,7 @@ client = InferenceClient(
     "mistralai/Mistral-7B-Instruct-v0.2"
 )
 
-
+"""
 def format_prompt(message, history):
   prompt = "<s>"
   for user_prompt, bot_response in history:
@@ -13,6 +13,54 @@ def format_prompt(message, history):
     prompt += f" {bot_response}</s> "
   prompt += f"[INST] {message} [/INST]"
   return prompt
+"""
+
+def format_prompt(message, history):
+  """
+  Formats a prompt for the chatbot based on history and a provided template.
+
+  Args:
+      message (str): The user's current message.
+      history (list): A list of tuples containing past user prompts and bot responses.
+
+  Returns:
+      str: The formatted prompt for the chatbot.
+  """
+
+  prompt = "<s>[INST]\n"  # Newline after opening prompt tag for readability
+
+  # Introduction (replace placeholders with actual content if needed)
+  prompt += f"""**Introduction:**
+
+  Hi there! I'm Bard, your friendly AI assistant. I'm conducting a product survey 
+  to understand customer preferences for recently purchased items. 
+
+  This survey focuses on phones. Could you tell me a bit about the phone you 
+  recently purchased?
+  \n"""
+
+  # Add past conversation history
+  for user_prompt, bot_response in history:
+    prompt += f"[INST] {user_prompt} [/INST]\n{bot_response}\n"
+
+  # Add current user message
+  prompt += f"[INST] {message} [/INST]\n"
+
+  # Prompt continuation based on current survey stage
+  # (Replace with your logic to determine the next question based on history)
+  current_question = len(history) + 1
+  if current_question == 1:
+    prompt += "1. What type of phone did you purchase (brand and model)?"
+  elif current_question == 2:
+    prompt += "2. Where did you buy your phone from (online store or physical store)?"
+  # ... Add logic for remaining questions (3-13) ...
+  else:
+    prompt += "Thank you for your participation! The survey is now complete."
+
+  prompt += "\n[/INST]</s>"  # Closing prompt and tags
+
+  return prompt
+
 
 def generate(
     prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,