Update app.py

app.py

@@ -149,16 +149,14 @@
 
 
 import streamlit as st
-import os
 from langchain_community.chat_models import ChatHuggingFace
 from langchain_community.llms import HuggingFaceHub
 from langchain_core.messages import HumanMessage, SystemMessage
 
-# Set token from Streamlit secrets
-HF_TOKEN = st.secrets["keys"]
-os.environ["HUGGINGFACEHUB_API_TOKEN"] = HF_TOKEN  # Optional but okay to set
+# ✅ Load your secret token from Hugging Face Space secrets
+HF_TOKEN = st.secrets["Final_key"]
 
-# Load the model using the token
+# ✅ Initialize the LLM with your token
 llm = HuggingFaceHub(
     repo_id="meta-llama/Llama-3.2-3B-Instruct",
     huggingfacehub_api_token=HF_TOKEN,
@@ -167,20 +165,21 @@ llm = HuggingFaceHub(
 
 chat_model = ChatHuggingFace(llm=llm)
 
-# Streamlit UI
-st.title("🧪 Simple LLaMA Chat Test")
+# ✅ Streamlit UI
+st.title("🧠 LLaMA Chat (Data Science Mentor)")
 
-question = st.text_input("Ask a gaming-related question:", "Give me name of top 10 PC games of all time with description")
+question = st.text_input("Ask any question about data science topics:")
 
 if st.button("Ask"):
     messages = [
-        SystemMessage(content="Answer like you are a hardcore PC gamer"),
+        SystemMessage(content="You are a data science mentor."),
         HumanMessage(content=question)
     ]
     response = chat_model.invoke(messages)
-    st.write("### Response:")
+    st.write("### Mentor's Response:")
     st.write(response.content)
 
+
 # import streamlit as st
 # from langchain_community.chat_models import ChatHuggingFace
 # from langchain_community.llms import HuggingFaceHub