Update app.py

app.py

@@ -3,7 +3,6 @@ import ast
 import argparse
 import glob
 import pickle
-
 import gradio as gr
 import numpy as np
 import pandas as pd
@@ -11,8 +10,6 @@ import os
 from collections import defaultdict
 from matplotlib.colors import LinearSegmentedColormap
 
-
-
 def make_default_md():
     leaderboard_md = f"""
 # 🔎📚🪡📚❓ BABIlong Leaderboard 🏆
@@ -23,12 +20,10 @@ def make_default_md():
 """
     return leaderboard_md
 
-
 def make_arena_leaderboard_md(total_models):
-    leaderboard_md = f"""Total #models: **{total_models}**. Last updated: Mar 29, 2024."""
+    leaderboard_md = f"""Total #models: **{total_models}**. Last updated: May 09, 2024."""
     return leaderboard_md
 
-
 def make_model_desc_md(f_len):
     desc_md = make_arena_leaderboard_md(f_len)
     models = next(os.walk('info'))[2]
@@ -36,15 +31,12 @@ def make_model_desc_md(f_len):
         model_name = model.split('.md')[0]
         with open(os.path.join('info', model), 'r') as f:
             description = f.read()
-
         desc_md += f"\n\n### {model_name}\n{description}"
     return desc_md
 
-
 def model_hyperlink(model_name, link):
     return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'
 
-
 def load_model(folders, tab_name, msg_lengths):
     results = defaultdict(list)
 
@@ -53,7 +45,7 @@ def load_model(folders, tab_name, msg_lengths):
             return '-'
         def __float__(self):
             return 0.0
-        
+       
     mean_score = []
 
     for i, folder in enumerate(folders):
@@ -71,11 +63,8 @@ def load_model(folders, tab_name, msg_lengths):
     for rank, i in enumerate(np.argsort(mean_score)):
         results['Rank'][i] = rank + 1
 
-
     return pd.DataFrame(results).sort_values(['Rank'])
     
-
-
 def build_leaderboard_tab(folders):
     default_md = make_default_md()
     md_1 = gr.Markdown(default_md, elem_id="leaderboard_markdown")
@@ -93,7 +82,7 @@ def build_leaderboard_tab(folders):
     }
 
     with gr.Tabs() as tabs:
-        for tab_id, tab_name in enumerate(['qa1','qa2', 'qa3', 'qa4', 'qa2']):
+        for tab_id, tab_name in enumerate(['qa1','qa2', 'qa3', 'qa4', 'qa5']):
                 df = load_model(folders, tab_name, msg_lengths)
                 cmap = LinearSegmentedColormap.from_list('ryg', ["red", "yellow", "green"], N=256)
 
@@ -125,7 +114,7 @@ def build_leaderboard_tab(folders):
                         wrap=True,
                     )
 
-        with gr.Tab("Model description", id=tab_id + 1):
+        with gr.Tab("Description", id=tab_id + 1):
             desc_md = make_model_desc_md(len(folders))
             gr.Markdown(desc_md, elem_id="leaderboard_markdown")
 
@@ -169,8 +158,6 @@ footer {
 }
 """
 
-
-
 def build_demo(folders):
     text_size = gr.themes.sizes.text_lg