Update app.py

app.py

@@ -83,7 +83,17 @@ with demo:
                 - <u>**CrossEncoder Context Retrieval**</u>: All Contexts + Question -> Top K Relevant Contexts best suited for answering question
                 - <u>**UnifiedQA**</u>: Most Relevant Contexts + Supplied Question -> Predict Set of Probable Answers
                 ''')
-
+                examples = [
+                    ['examples/1909.00694.pdf', 'What is the seed lexicon?', 5],
+                    ['examples/1909.00694.pdf', 'How big is seed lexicon used for training?', 5],
+                    ['examples/1810.04805.pdf', 'What is this paper about?', 5],
+                    ['examples/1810.04805.pdf', 'What is the model size?', 5],
+                    ['examples/2105.03011.pdf', 'How many questions are in this dataset?', 5],
+                    ['examples/1909.00694.pdf', 'How are relations used to propagate polarity?', 5],
+                ]
+                gr.Examples(examples=examples,
+                            inputs=[input_pdf_file, input_question_text, input_k_percent])
+        
         with gr.Column():
             with gr.Row():
                 output_gallery = gr.Gallery(label='DiT Predicted Entities')
@@ -105,17 +115,4 @@ with demo:
                 
     button_run.click(fn=run_fn, inputs=[input_pdf_file, input_question_text, input_k_percent], outputs=[output_gallery, output_contexts, output_ranked_contexts, output_qa_results])
     
-    examples = [
-        ['examples/1909.00694.pdf', 'What is the seed lexicon?', 5],
-        ['examples/1909.00694.pdf', 'How big is seed lexicon used for training?', 5],
-        ['examples/1810.04805.pdf', 'What is this paper about?', 5],
-        ['examples/1810.04805.pdf', 'What is the model size?', 5],
-        ['examples/2105.03011.pdf', 'How many questions are in this dataset?', 5],
-        ['examples/1909.00694.pdf', 'How are relations used to propagate polarity?', 5],
-
-    ]
-    gr.Examples(examples=examples,
-                inputs=[input_pdf_file, input_question_text, input_k_percent])
-    
-    # examples = gr.Dataset(components=[input_pdf_file, input_question_text], samples=[[open('examples/1810.04805.pdf', mode='rb'), 'How many parameters are in the model?']])
     demo.launch(enable_queue=True)