Trail2 app.py

app.py

@@ -68,8 +68,7 @@ def memory_chat(user_input, person_name):
     history = memory_db[name]["history"]
     past_text = "\n\n".join([f"- {h['message']}\n  -> {h['interpretation']}" for h in history])
 
-    chat_prompt = f"""You are a smart advisor trained on past conversations with {name}.\n
-Here is the message history:\n{past_text}\n\nUser asks: {user_input}\n\nGive a thoughtful answer using patterns or emotional tone from the past history."""
+    chat_prompt = f"""You are a relationship and social communication expert.\n\nYou remember all past messages and responses exchanged with {name}.\nThis is the known message history:\n{past_text}\n\nNow the user wants to understand more about what {name} might be thinking or feeling deep down,\nbased on what they've said before and how they usually act.\n\nUser’s question: {user_input}\n\nUse what you know from the history to infer hidden meaning, emotional tone, and behavior patterns.\nGive a thoughtful and emotionally intelligent answer. Avoid repeating the user's feelings."""
 
     response = interpreter(chat_prompt, max_new_tokens=200)[0]["generated_text"]
     return response
@@ -114,4 +113,4 @@ with gr.Blocks(title="Textual Chemistry") as app:
     chatbot_btn = gr.Button("Ask Memory Bot")
     chatbot_btn.click(fn=memory_chat, inputs=[chatbot_input, person_name], outputs=chatbot_output)
 
-app.launch()
+app.launch()