updated all

app.py

@@ -1,10 +1,9 @@
 import streamlit as st
+from transformers import pipeline
 
 # Set page config FIRST — must be the first Streamlit command
 st.set_page_config(page_title="BERT QA", layout="wide")
 
-from transformers import pipeline
-
 # Load QA pipeline with BERT model
 @st.cache_resource
 def load_qa_pipeline():
@@ -30,4 +29,4 @@ if st.button("Get Answer"):
         QA_input = {"question": question, "context": context}
         result = nlp(QA_input)
         st.success(f"🧠 **Answer**: {result['answer']}")
-        st.caption(f"Score: {result['score']:.2f} | Start: {result['start']}, End: {result['end']}")
+        st.caption(f"Score: {result['score']:.2f} | Start: {result['start']}, End: {result['end']}")