Update app.py

app.py

@@ -11,34 +11,45 @@ def load_model():
 
 qa_pipeline = load_model()
 
-st.title("📄 Document Question Answering App")
-st.write("Upload a PDF file, enter a question, and get answers from the document.")
+st.title("\ud83d\udcc4 Document Question Answering App")
+st.write("Upload a PDF or Image file, enter a question, and get answers from the document.")
 
-# Upload PDF
-pdf_file = st.file_uploader("Upload PDF", type=["pdf"])
+# Upload PDF or image
+uploaded_file = st.file_uploader("Upload PDF or Image", type=["pdf", "png", "jpg", "jpeg"])
 
 # Ask a question
 question = st.text_input("Ask a question about the document:")
 
-if pdf_file and question:
-    # Convert first page of PDF to image using PyMuPDF
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
-        tmp_file.write(pdf_file.read())
-        pdf_path = tmp_file.name
+if uploaded_file and question:
+    # Handle PDF file
+    if uploaded_file.type == "application/pdf":
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
+            tmp_file.write(uploaded_file.read())
+            pdf_path = tmp_file.name
 
-    doc = fitz.open(pdf_path)
-    page = doc.load_page(0)  # just first page for now
-    pix = page.get_pixmap(dpi=150)
-    img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
+        doc = fitz.open(pdf_path)
+        page = doc.load_page(0)  # just first page for now
+        pix = page.get_pixmap(dpi=150)
+        img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
+        st.image(img, caption="Page 1 of PDF")
 
-    # Show the rendered page
-    st.image(img, caption="Page 1 of PDF")
+    # Handle image file
+    else:
+        img = Image.open(uploaded_file)
+        st.image(img, caption="Uploaded Image")
 
     # Run the pipeline
     with st.spinner("Searching for the answer..."):
-        result = qa_pipeline(img, question)
-        if result:
-            top_answer = result[0]  # get the highest-scoring answer
+        results = qa_pipeline(img, question)
+
+        if results:
+            top_answer = results[0]  # get the highest-scoring answer
             st.success(f"**Answer:** {top_answer['answer']} (score: {top_answer['score']:.2f})")
+
+            # Show top 3 options if available
+            if len(results) > 1:
+                st.markdown("\n**Other possible answers:**")
+                for idx, ans in enumerate(results[1:3], start=2):
+                    st.markdown(f"- Option {idx}: {ans['answer']} (score: {ans['score']:.2f})")
         else:
-            st.warning("No answer found.")
+            st.warning("No answer found.")