Update app.py

app.py

@@ -5,11 +5,6 @@ from langchain_core.messages import HumanMessage,SystemMessage,AIMessage
 
 hf_token = os.getenv("HF_TOKEN")
 
-deep_seek_model = HuggingFaceEndpoint(repo_id = 'deepseek-ai/DeepSeek-R1', provider = 'nebius', temperature = 0.7, max_new_tokens = 100, task ='conversational')
-ds_model = ChatHuggingFace(llm = deep_seek_model, repo_id = 'deepseek-ai/DeepSeek-R1', provider = 'nebius', temperature = 0.7, max_new_tokens = 100, task ='conversational')
-
-# st.title("ChatGenius Hub: Master Every Data Skills")
-
 
 # Set the default page in session state
 if "page" not in st.session_state:
@@ -28,8 +23,9 @@ if st.session_state.page == "home":
     with col1:
         if st.button("Python 🐍"):
             switch_page("python")
-        if st.button("Power BI 📊"):
-            switch_page("powerbi")
+        if st.button("Machine Learning 🤖"):
+            switch_page("ml")
+        
 
     with col2:
         if st.button("SQL 🛢️"):
@@ -38,8 +34,8 @@ if st.session_state.page == "home":
             switch_page("deeplearning")
 
     with col3:
-        if st.button("Machine Learning 🤖"):
-            switch_page("ml")
+        if st.button("Power BI 📊"):
+            switch_page("powerbi")        
         if st.button("Statistics 📈"):
             switch_page("statistics")
 
@@ -71,39 +67,6 @@ elif st.session_state.page == "statistics":
     st.button("⬅️ Back to Home", on_click=lambda: switch_page("home"))
 
 
-# message = [SystemMessage(content = "Answer like a data scientist"),
-#           HumanMessage(content = "Tell me about Support Vector")]
-# result =  ds_model.invoke(message)
-# print(result.content)
-
-
-
-# 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 = ds_model.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}")