Update app.py

app.py

@@ -1,15 +1,19 @@
 import streamlit as st
 from transformers import pipeline
+from huggingface_hub import login
 
-# Title and Description
+# Title of the Streamlit app
 st.title("WhiteRabbitNEO Q&A App")
-st.write("Ask any question, and WhiteRabbitNEO will provide an answer.")
 
-# Initialize the model pipeline
+# Hugging Face API token input (only required if the model is private)
+token = st.text_input("Enter your Hugging Face token (if required):", type="password")
+
+# Load the model
 @st.cache_resource
 def load_model():
     try:
-        # Simple model pipeline initialization
+        if token:
+            login(token=token)
         model = pipeline("question-answering", model="WhiteRabbitNEO")
         return model
     except Exception as e:
@@ -17,25 +21,21 @@ def load_model():
         return None
 
 # Load the model
-qa_pipeline = load_model()
+model = load_model()
 
-# Simple input section: Ask question and provide context
-if qa_pipeline:
-    question = st.text_input("Your question:")
-    context = st.text_area("Context (provide background info for the question):")
+if model:
+    question = st.text_input("Ask a question:")
+    context = st.text_area("Provide context for your question:")
 
-    # Button to trigger the model for prediction
     if st.button("Get Answer"):
         if question and context:
             try:
-                # Get prediction from the model
-                result = qa_pipeline(question=question, context=context)
-                # Display the answer
-                st.write(f"**Answer:** {result['answer']}")
-                st.write(f"**Confidence Score:** {result['score']:.2f}")
+                answer = model(question=question, context=context)
+                st.write("Answer:", answer['answer'])
             except Exception as e:
                 st.error(f"Error generating answer: {e}")
         else:
-            st.warning("Please fill both the question and context fields.")
+            st.warning("Please provide both a question and context.")
 else:
     st.error("Model could not be loaded. Please check your configuration.")
+