Update app.py

corrected this error

app.py

@@ -3,34 +3,43 @@ from pipeline import run_with_chain
 from my_memory_logic import memory, restatement_chain
 
 def chat_history_fn(user_input, history):
-    # Convert `history` (list of [user, ai] pairs) into memory messages
+    """
+    Gradio calls this function each time the user submits a message.
+    'history' is a list of (user_msg, ai_msg) pairs from previous turns.
+    We'll add them to memory, restate the user_input if needed,
+    run the pipeline, store the new turn, then return a list of
+    message dicts that Gradio's ChatInterface accepts.
+    """
+    # 1) Convert existing history into memory
     for user_msg, ai_msg in history:
         memory.chat_memory.add_user_message(user_msg)
         memory.chat_memory.add_ai_message(ai_msg)
     
-    # 1) Restate the user question with chat history
+    # 2) Restate the new user question with chat history
     reformulated_q = restatement_chain.run({
         "chat_history": memory.chat_memory.messages,
         "input": user_input
     })
     
-    # 2) Pass the reformulated question to your pipeline
+    # 3) Pass the reformulated question to your pipeline
     answer = run_with_chain(reformulated_q)
     
-    # 3) Update memory
+    # 4) Update memory with the new turn
     memory.chat_memory.add_user_message(user_input)
     memory.chat_memory.add_ai_message(answer)
     
-    # 4) Convert the updated history to a list of message dicts.
-    #    This is what Gradio's ChatInterface expects (instead of returning a tuple).
+    # 5) Update the 'history' list with (user, ai)
     history.append((user_input, answer))
+    
+    # 6) Gradio's ChatInterface expects a list of message dicts:
+    #    [{"role": "user"|"assistant", "content": "..."} ...]
+    #    We'll build that from our (user_msg, ai_msg) pairs in 'history'.
     message_dicts = []
-    for user_msg, ai_msg in history:
-        # user turn
-        message_dicts.append({"role": "user", "content": user_msg})
-        # AI turn
+    for usr_msg, ai_msg in history:
+        message_dicts.append({"role": "user", "content": usr_msg})
         message_dicts.append({"role": "assistant", "content": ai_msg})
     
+    # 7) Return the message dictionary list
     return message_dicts
 
 demo = gr.ChatInterface(