Update app.py

app.py

@@ -4,32 +4,27 @@ from my_memory_logic import run_with_session_memory
 
 def chat_interface_fn(message, history, session_id):
     """
-    A single-turn chat function for Gradio's ChatInterface.
-    We rely on session_id to store the conversation in our my_memory_logic store.
+    Single-turn function for Gradio's ChatInterface.
+    'session_id' is used to store conversation across turns.
     """
-    # 1) We call run_with_session_memory with user message and session_id
     answer = run_with_session_memory(message, session_id)
-
-    # 2) Append the turn to the 'history' so Gradio UI displays it
+    # Update local 'history' for the UI
     history.append((message, answer))
-    
-    # 3) Convert into message dicts if ChatInterface is using openai-style messages
-    #    or we can just return a single string. Let's do openai-style message dicts:
+
+    # Convert to openai-style message dicts
     message_dicts = []
     for user_msg, ai_msg in history:
         message_dicts.append({"role": "user", "content": user_msg})
         message_dicts.append({"role": "assistant", "content": ai_msg})
     return message_dicts, history
 
-# We'll define a small Gradio Blocks or ChatInterface
 with gr.Blocks() as demo:
     session_id_box = gr.Textbox(label="Session ID", value="abc123", interactive=True)
+    
     chat_interface = gr.ChatInterface(
-        fn=lambda message, history: chat_interface_fn(
-            message, history, session_id_box.value
-        ),
+        fn=lambda msg, hist: chat_interface_fn(msg, hist, session_id_box.value),
         title="DailyWellnessAI (Session-based Memory)",
-        description="Ask your questions. The session_id determines your stored memory."
+        description="Multi-turn chat using session ID and RunnableWithMessageHistory."
     )
 
 demo.launch()