Update app.py

app.py

@@ -1,22 +1,22 @@
-import streamlit as st
-from extract_pdf import extract_text_from_pdf
-from summarize import summarize_text
-from generate_answers import get_answer
-
-st.title("📄 PDF Question Answering with Bert Model and T5 Model")
-
-uploaded_file = st.file_uploader("Upload a PDF", type=["pdf"])
-if uploaded_file:
-    with st.spinner("Reading and summarizing document..."):
-        raw_text = extract_text_from_pdf(uploaded_file)
-        summary = summarize_text(raw_text)
-        st.success("Document summarized!")
-    
-    with st.expander("📄 View Summary"):
-        st.write(summary)
-
-    question = st.text_input("❓ Ask a question based on the document summary:")
-    if question:
-        with st.spinner("Generating answer..."):
-            answer = get_answer(question, summary)
-        st.markdown(f"**Answer:** {answer}")
+import streamlit as st
+from summarize import summarize_text
+from generate_answers import get_answer
+from utils import extract_text_from_pdf
+st.title("By:- Akshat Thakkar , Kartik Raghuvanshi")
+st.title("📄 BERT-based Question Answering on PDF (with T5 Summarization)")
+
+uploaded_file = st.file_uploader("Upload a PDF document", type="pdf")
+
+if uploaded_file:
+    raw_text = extract_text_from_pdf(uploaded_file)
+    summary = summarize_text(raw_text)
+    
+    st.subheader("📋 Summary of the Document")
+    st.write(summary)
+
+    question = st.text_input("❓ Ask a Question Based on the Summary")
+
+    if question:
+        answer = get_answer(question, summary)
+        st.subheader("✅ Answer")
+        st.write(answer)