Update app.py

app.py

@@ -20,7 +20,7 @@ llm = HuggingFaceEndpoint(
 # Streamlit UI setup
 st.set_page_config(page_title="🧠 HuggingFace Chatbot", page_icon="🤖")
 st.title("🤖 HuggingFace Chatbot")
-st.caption("Built with Streamlit + LangChain (No schema!)")
+st.caption("Built with Streamlit + LangChain (no schema, limited to 50 words per answer)")
 
 # Initialize session state for chat history
 if "messages" not in st.session_state:
@@ -35,20 +35,19 @@ for msg in st.session_state.messages:
 
 # Handle user input
 if prompt := st.chat_input("Type your message here..."):
-    # Add user message
     st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
         st.markdown(prompt)
 
-    context = ""
+    # Build the conversation history with a system-like instruction
+    instruction = "You are a helpful and concise assistant. Always respond in 50 words or fewer.\n\n"
+    chat_history = ""
     for msg in st.session_state.messages:
         role = "User" if msg["role"] == "user" else "Assistant"
-        context += f"{role}: {msg['content']}\n"
+        chat_history += f"{role}: {msg['content']}\n"
+    context = instruction + chat_history + "Assistant:"
 
-    # Add explicit instruction to limit response
-    context += "Assistant: (Please answer in 50 words or fewer.)"
-
-    # Generate response from LLM
+    # Generate response
     with st.chat_message("assistant"):
         response = llm.invoke(context)
         st.markdown(response)