Update app.py

app.py

@@ -4,7 +4,6 @@ from langchain.memory import ConversationBufferMemory
 from langchain.chains import ConversationChain
 from langchain_google_genai import ChatGoogleGenerativeAI
 
-# Get Gemini API key from environment variable
 GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
 
 st.set_page_config(page_title="Conversational AI Data Science Tutor", page_icon="🤖")
@@ -15,13 +14,10 @@ st.write("Ask me any **Data Science** related question!")
 if not GEMINI_API_KEY:
     st.error("❌ GEMINI_API_KEY not found. Please add it in Hugging Face → Settings → Variables and secrets.")
 else:
-    # Initialize Gemini LLM
     llm = ChatGoogleGenerativeAI(
         model="gemini-1.5-pro",
         google_api_key=GEMINI_API_KEY
     )
-
-    # Add memory for conversation awareness
     memory = ConversationBufferMemory()
     conversation = ConversationChain(
         llm=llm,
@@ -29,23 +25,18 @@ else:
         verbose=False
     )
 
-    # Initialize chat history in session_state
+    
     if "messages" not in st.session_state:
         st.session_state.messages = []
 
-    # Display previous messages
+    
     for msg in st.session_state.messages:
         st.chat_message(msg["role"]).markdown(msg["content"])
 
-    # User input with chat-style box
+
     if prompt := st.chat_input("Ask a data science question..."):
-        # Save user message
         st.session_state.messages.append({"role": "user", "content": prompt})
         st.chat_message("user").markdown(prompt)
-
-        # Get model response
         response = conversation.predict(input=prompt)
-
-        # Save assistant message
         st.session_state.messages.append({"role": "assistant", "content": response})
         st.chat_message("assistant").markdown(response)