Update app.py

app.py

@@ -140,9 +140,12 @@ with gr.Blocks(title="Task Caching Demo", theme=gr.themes.Default(font=[gr.theme
     gr.Markdown("Demonstrates the effect of using a dynamically generated cheatsheet (Task Caching) on model inference. Uses SambaNova API via `litellm`.")
 
     training_data_example = '''
-Solve for 24: 1 2 3 4
-Solve for 24: 3 4 5 6
-Solve for 24: 4 5 6 7
+{"benchmark": "FinanceBench", "question": "What was 3M's net sales in 2018?", "answer": "3M's net sales in 2018 were $32,765 million.", "evidence_text": "Net sales of $32,765 million, up 3.5 percent from $31,657 million in 2017."}
+
+{"benchmark": "FinanceBench", "question": "What was the total amount of cash and cash equivalents for 3M at the end of 2018?", "answer": "At the end of 2018, 3M had $3,567 million in cash and cash equivalents.", "evidence_text": "Cash and cash equivalents totaled $3,567 million at December 31, 2018 compared to $3,291 million at December 31, 2017."}
+
+{"benchmark": "FinanceBench", "question": "What is 3M's strategy regarding acquisitions and divestitures?", "answer": "3M's strategy includes pursuing acquisitions and divestitures to strengthen its portfolio and create shareholder value. This involves identifying and acquiring businesses that align with its strategic priorities and divesting non-core assets.", "evidence_text": "Our strategy includes the active management of our portfolio through acquisitions and divestitures. We seek to acquire businesses that align with our strategic priorities and offer attractive returns, and we may divest businesses that are no longer core to our strategy or do not meet our performance expectations."}
+
 '''
     with gr.Tabs():
         model_name_input = gr.Textbox(