Update app.py

app.py

@@ -4,28 +4,25 @@ from langchain_community.chat_models import ChatHuggingFace
 from langchain_community.llms import HuggingFaceEndpoint
 from langchain_core.messages import HumanMessage, SystemMessage, AIMessage
 
+# --- Load API Token ---
+hf_token = os.getenv("Data_science")
+if not hf_token:
+    st.error("❌ Hugging Face token not found. Please set the 'Data_science' environment variable.")
+    st.stop()
 
-hf_token = os.getenv("Data_science")  
 os.environ["HUGGINGFACEHUB_API_KEY"] = hf_token
 os.environ["HF_TOKEN"] = hf_token
 
-
+# --- Load Hugging Face model (Qwen) ---
 model = HuggingFaceEndpoint(
     repo_id="Qwen/Qwen3-32B",
     provider="nebius",
     temperature=0.6,
-    max_new_tokens=300,
-    task="conversational"
+    max_new_tokens=500,
+    task="text-generation"
 )
 
-chat_model = ChatHuggingFace(
-    llm=model,
-    repo_id="Qwen/Qwen3-32B",
-    provider="nebius",
-    temperature=0.6,
-    max_new_tokens=300,
-    task="conversational"
-)
+chat_model = ChatHuggingFace(llm=model)
 
 # --- Streamlit styles ---
 st.markdown("""
@@ -67,15 +64,15 @@ for i, subject in enumerate(subjects):
         st.session_state.selected_subject = subject
         st.session_state.message_history = []  # Reset chat on subject change
 
-# --- System Message ---
-system_prompt = f"""
+# --- Set system message based on subject & experience ---
+if not st.session_state.message_history:
+    system_prompt = f"""
 You are a highly knowledgeable data science mentor specialized in {st.session_state.selected_subject}.
 Your job is to guide a {experience.lower()} learner with clear, concise, and actionable advice.
 Explain concepts, best practices, and answer questions with patience and professionalism.
 If relevant, include example code, use-cases, or tips.
 """
-if not st.session_state.message_history:
-    st.session_state.message_history.append(SystemMessage(content=system_prompt))
+    st.session_state.message_history.append(SystemMessage(content=system_prompt.strip()))
 
 # --- Chat Input ---
 user_question = st.text_input(f"💬 Ask your {st.session_state.selected_subject} question:")