Update app.py

app.py

@@ -80,4 +80,58 @@ elif st.session_state.page == "genai":
 
 
 
-
+def  python_page():
+    st.title("Python Chatbot")
+    hf_token = os.getenv("HUGGINGFACEHUB_API_TOKEN") or os.getenv("HF_TOKEN")
+    if not hf_token:
+        st.error("Please add your Hugging Face API token to Secrets (HUGGINGFACEHUB_API_TOKEN or HF_TOKEN).")
+        st.stop()
+
+# Setup the LangChain HuggingFaceEndpoint and ChatHuggingFace LLM
+    deep_seek_model = HuggingFaceEndpoint(
+    repo_id="deepseek-ai/DeepSeek-R1",
+    provider="nebius",
+    temperature=0.7,
+    max_new_tokens=100,
+    task="conversational",
+    huggingfacehub_api_token=hf_token,
+    )
+
+    deepseek = ChatHuggingFace(
+    llm=deep_seek_model,
+    repo_id="deepseek-ai/DeepSeek-R1",
+    provider="nebius",
+    temperature=0.7,
+    max_new_tokens=100,
+    task="conversational"
+    )
+# Initialize session state for chat history
+    if "messages" not in st.session_state:
+        st.session_state.messages = [
+        SystemMessage(content="Answer like a data scientist")
+    ]
+
+    def generate_response(user_input):
+    # Append user message
+        st.session_state.messages.append(HumanMessage(content=user_input))
+    # Invoke the model
+        response = deepseek.invoke(st.session_state.messages)
+    # Append AI response
+        st.session_state.messages.append(AIMessage(content=response))
+        return response
+
+# User input
+    user_input = st.text_input("Ask a question about Data Science:")
+
+    if user_input:
+        with st.spinner("Getting answer..."):
+            answer = generate_response(user_input)
+        st.markdown(f"**Answer:** {answer}")
+
+# Display chat history
+    if st.session_state.messages:
+        for msg in st.session_state.messages[1:]:  # skip initial SystemMessage
+            if isinstance(msg, HumanMessage):
+                st.markdown(f"**You:** {msg.content}")
+            elif isinstance(msg, AIMessage):
+                st.markdown(f"**Bot:** {msg.content}")