Update app.py

app.py

@@ -173,9 +173,7 @@ def search(query: str, k: int):
         k (int): Number of top results to return (1–10).
 
     Returns:
-        tuple:
-            - results (list[tuple[PIL.Image.Image, str]]): List of (page_image, caption) pairs for a gallery.
-            - ai_response (str): Answer grounded only in retrieved pages, with citations (page numbers).
+        ai_response (str): Answer grounded only in retrieved pages, with citations (page numbers).
 
     Notes:
         • Requires that a PDF has been indexed first.
@@ -208,7 +206,7 @@ def search(query: str, k: int):
 
     # Generate grounded response
     ai_response = query_gpt(query, results)
-    return results, ai_response
+    return ai_response
 
 
 # -----------------------------
@@ -269,13 +267,12 @@ This demo lets you **upload a PDF or load a sample**, then **search** for the mo
             query = gr.Textbox(placeholder="Enter your query here", label="Query")
             k_slider = gr.Slider(minimum=1, maximum=10, step=1, label="Number of results", value=5)
             search_button = gr.Button("🔍 Search", variant="primary")
-            output_gallery = gr.Gallery(label="Retrieved Pages", height=600, show_label=True)
             output_text = gr.Textbox(label="AI Response", placeholder="Generated response based on retrieved documents")
 
     # Wiring
     index_btn.click(handle_upload, inputs=[pdf_input], outputs=[status_box, pdf_view])
     index_url_btn.click(handle_url, inputs=[url_box], outputs=[status_box, pdf_view])
-    search_button.click(search, inputs=[query, k_slider], outputs=[output_gallery, output_text])
+    search_button.click(search, inputs=[query, k_slider], outputs=[output_text])
 
 if __name__ == "__main__":
     # Optional: pre-load the default sample at startup.