Add application files

app.py

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+from apscheduler.schedulers.background import BackgroundScheduler
+import gradio as gr
+import pandas as pd
+
+def show_leaderboard():
+    # Load the leaderboard data from the CSV
+    df = pd.read_csv("leaderboard.csv")
+
+    # Convert the dataframe to a markdown table for easy display in Gradio
+    markdown_table = df.to_markdown()
+
+    return markdown_table
+
+def launch_gradio():
+    # Define Gradio interface
+    iface = gr.Interface(
+        fn=show_leaderboard, 
+        inputs=[], 
+        outputs="markdown"
+    )
+
+    # Run the interface
+    iface.queue(concurrency_count=40).launch()
+
+# Define the scheduler
+scheduler = BackgroundScheduler()
+scheduler.add_job(launch_gradio, "interval", seconds=3600)
+scheduler.start()
+
+# Call launch_gradio to start the first Gradio app immediately
+launch_gradio()

leaderboard.csv

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+Dataset,Metrics,GPT NeoX,OPT 66B,BLOOM,Chat GPT,GPT 4,Bloomberg GPT,FinMA 7B,FinMA 30B,FinMA 7B-full
+FPB,Acc,-,-,-,0.78,0.76,-,0.86,0.87,0.87
+FPB,F1,0.45,0.49,0.50,0.78,0.78,0.51,0.86,0.88,0.87
+FiQA-SA,F1,0.51,0.52,0.53,-,-,0.75,0.84,0.87,0.79
+Headline,AvgF1,0.73,0.79,0.77,0.77,0.86,0.82,0.98,0.97,0.97
+NER,EntityF1,0.61,0.57,0.56,0.77,0.83,0.61,0.75,0.62,0.69
+FinQA,EmAcc,-,-,-,0.58,0.63,-,0.06,0.11,0.04
+ConvFinQA,EmAcc,0.28,0.30,0.36,0.60,0.76,0.43,0.25,0.40,0.20
+BigData22,Acc,-,-,-,0.53,0.54,-,0.48,0.47,0.49
+BigData22,MCC,-,-,-,-0.025,0.03,-,0.04,0.04,0.01
+ACL18,Acc,-,-,-,0.50,0.52,-,0.50,0.49,0.56
+ACL18,MCC,-,-,-,0.005,0.02,-,0.00,0.00,0.10
+CIKM18,Acc,-,-,-,0.55,0.57,-,0.56,0.43,0.53
+CIKM18,MCC,-,-,-,0.01,0.02,-,-0.02,-0.05,-0.03

requirements.txt

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+aiofiles==23.1.0
+aiohttp==3.8.4
+aiosignal==1.3.1
+APScheduler==3.10.1
+gradio==3.27.0
+gradio_client==0.1.3
+pandas==2.0.0