Update app.py

app.py

@@ -1,25 +1,42 @@
 import streamlit as st
 from transformers import pipeline
+from huggingface_hub import login
+import os
 
-# Set up the Hugging Face model pipeline (text generation or QA)
+# 🚨 Replace this with your actual Hugging Face access token
+HF_TOKEN = "your_huggingface_access_token_here"  # <-- Insert your token here securely
+
+# Login to Hugging Face Hub
+login(HF_TOKEN)
+
+# App Title & Description
 st.title("🤖📟 Arduino Expert Chatbot")
 st.markdown("Get help with Arduino code, circuit diagrams, and projects.")
 
-# Load the model (e.g., 'mistralai/Mixtral-8x7B-Instruct-v0.1' or any suitable)
+# Load the model securely
 @st.cache_resource
 def load_model():
-    return pipeline("text-generation", model="mistralai/Mixtral-8x7B-Instruct-v0.1")
+    try:
+        return pipeline("text-generation", model="mistralai/Mixtral-8x7B-Instruct-v0.1", token=HF_TOKEN)
+    except Exception as e:
+        st.error("🚫 Failed to load the model. Using fallback model (GPT-2).")
+        return pipeline("text-generation", model="gpt2")  # fallback public model
 
+# Load model once
 model = load_model()
 
-# User input
+# User Input
 query = st.text_area("Ask your Arduino question here 👇", height=150)
 
+# Generate Answer
 if st.button("Get Answer"):
-    if query:
+    if query.strip():
         with st.spinner("Thinking... 🤖"):
-            response = model(query, max_length=512, do_sample=True, temperature=0.7)
-            st.success(response[0]['generated_text'])
+            try:
+                response = model(query, max_length=512, do_sample=True, temperature=0.7)
+                st.success(response[0]['generated_text'])
+            except Exception as e:
+                st.error(f"❌ Error generating response: {e}")
     else:
         st.warning("Please enter a question about your Arduino project.")