updated app.py to a sortable dataframe

app.py

@@ -1,49 +1,72 @@
 import gradio as gr
-import pandas as pd
-import numpy as np
-import json
 import requests
+import pandas as pd
+
+class MultiURLData:
+    def __init__(self, file_path):
+        self.file_path = file_path
+
+    def fetch_data(self):
+        # Read URLs from a file, one per line
+        with open(self.file_path, 'r') as f:
+            file_urls = [line.strip() for line in f.readlines()]
+
+        dataframes = []
+        for url in file_urls:
+            # Derive column names from the URLs
+            column_name = url.split('/')[-1].split('_')[0]
+
+            # Load data from URL
+            response = requests.get(url)
+            data = response.json()
 
-# Read URLs from a file, one per line
-with open('file_urls.txt', 'r') as f:
-    file_urls = [line.strip() for line in f.readlines()]
+            # Convert data into a DataFrame
+            df = pd.DataFrame(data['results']).T
 
-dataframes = []
+            # Rename 'acc' column to respective file names
+            df = df.rename(columns={'acc': column_name})
 
-for url in file_urls:
-    # Derive column names from the URLs
-    column_name = url.split('/')[-1].split('_')[0]
+            # Remove 'hendrycksTest-' from the index
+            df.index = df.index.str.replace('hendrycksTest-', '')
+            print(f"dype df {type(df)}")
 
-    # Load data from URL
-    response = requests.get(url)
-    data = response.json()
+            dataframes.append(df[[column_name]])  # keep only the column of interest
 
-    # Convert data into a DataFrame
-    df = pd.DataFrame(data['results']).T
+        # Merge the dataframes
+        # Merge the dataframes on index
+        data = pd.concat(dataframes, axis=1)
+        print(f"dype data {type(data)}")
 
-    # Rename 'acc' column to respective file names
-    df = df.rename(columns={'acc': column_name})
+        # Transpose the dataframe to swap rows and columns
+        data = data.transpose()
 
-    # Remove 'hendrycksTest-' from the index
-    df.index = df.index.str.replace('hendrycksTest-', '')
+        # Select only columns 'moral_scenarios' and 'moral_disputes'
+        data = data[['moral_scenarios', 'moral_disputes']]
 
-    dataframes.append(df[[column_name]])  # keep only the column of interest
+        ## add a column with the index of the dataframe
+        data['Model Name'] = data.index
 
-# Merge the dataframes on index
-data = pd.concat(dataframes, axis=1)
+        # move the column to the front of the dataframe
+        cols = data.columns.tolist()
+        cols = cols[-1:] + cols[:-1]
+        data = data[cols]
 
-# Transpose the dataframe to swap rows and columns
-data = data.transpose()
+        return data
 
-# Select only columns 'moral_scenarios' and 'moral_disputes'
-data = data[['moral_scenarios', 'moral_disputes']]
+data_provider = MultiURLData("file_urls.txt")
 
-def show_leaderboard():
-    # Convert dataframe to html so that it can be displayed properly in Gradio
-    return data.to_html()
+block = gr.Blocks()
 
-iface = gr.Interface(fn=show_leaderboard, inputs=[], outputs="html")
+with block:    
+    gr.Markdown("""Leaderboard""")
+    with gr.Tabs():
+        with gr.TabItem("Leaderboard"):
+            with gr.Row():
+                data = gr.outputs.Dataframe(type="pandas")
+            with gr.Row():
+                data_run = gr.Button("Refresh")
+                data_run.click(data_provider.fetch_data, inputs=None, outputs=data)
+    # running the function on page load in addition to when the button is clicked
+    block.load(data_provider.fetch_data, inputs=None, outputs=data)               
 
-# Run the interface. 
-# Note: you don't need to use .launch() in Hugging Face Spaces, this is for local testing.
-iface.launch()
+block.launch()