Update app.py

app.py

@@ -6,11 +6,11 @@ from langchain_community.chat_message_histories import StreamlitChatMessageHisto
 from langchain.memory import ConversationBufferMemory
 from langchain.chat_models import ChatOpenAI
 
-# Load OpenAI API key
+# Load API key
 load_dotenv()
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
 
-# Initialize OpenAI Chat Model (e.g., gpt-3.5-turbo)
+# Initialize model
 llm = ChatOpenAI(
     openai_api_key=OPENAI_API_KEY,
     model_name="gpt-4o-mini",
@@ -18,34 +18,31 @@ llm = ChatOpenAI(
     max_tokens=50,
 )
 
-# Streamlit UI
-st.set_page_config(page_title="LangChain Chatbot with Memory")
-st.title("🤖 LangChain Chatbot with Memory (OpenAI)")
+# Page config
+st.set_page_config(page_title="LangChain Chatbot")
+st.title("🤖 LangChain Chatbot (OpenAI)")
 
-# Message history
+# History and memory
 history = StreamlitChatMessageHistory(key="chat_messages")
+memory = ConversationBufferMemory(chat_memory=history, return_messages=True)
+conversation = ConversationChain(llm=llm, memory=memory)
+
+# 💬 Display chat history (before new user input)
 for msg in history.messages:
     if msg.type == "human":
         st.chat_message("user").write(msg.content)
-    else:
+    elif msg.type == "ai":
         st.chat_message("assistant").write(msg.content)
 
-# Memory setup
-memory = ConversationBufferMemory(chat_memory=history, return_messages=True)
-
-# Create conversation chain
-conversation = ConversationChain(llm=llm, memory=memory)
-
-# Chat input
+# 🔥 Chat input AFTER displaying history
 if prompt := st.chat_input("Say something..."):
-    # Display and store user message
-    history.add_user_message(prompt)
+    # Display + store user message
     st.chat_message("user").write(prompt)
+    history.add_user_message(prompt)
 
-    # Add 50-word limit prompt
-    limited_prompt = f"{prompt}\n\nPlease respond in no more than 50 words."
-    response = conversation.predict(input=limited_prompt)
-
-    # Display and store assistant message
-    history.add_ai_message(response)
+    # Response with word limit
+    response = conversation.predict(input=f"{prompt}\n\nPlease respond in complete sentence in no more than 50 words.")
+    
+    # Display + store assistant message
     st.chat_message("assistant").write(response)
+    history.add_ai_message(response)