Update app.py

app.py

@@ -23,15 +23,15 @@ from src.init import get_all_requested_models, load_all_info_from_hub
 def get_leaderboard_df():
     
     data = {
-        'Datasets': ['SOTA(FT)', 'SOTA(ZS)', 'FLAN-T5', 'GPT-3', 'GPT-3.5v2', 'GPT-3.5v3', 'ChatGPT', 'GPT-4'],
-        'KQApro': ['93.85', '94.20', '37.27', '38.28', '38.01', '40.35', '47.93', '57.20'],
-        'LC-quad2': ['33.10', '-', '30.14', '33.04', '33.77', '39.04', '42.76', '54.95'],
-        'WQSP': ['73.10', '62.98', '59.87', '67.68', '72.34', '79.60', '83.70', '90.45'],
-        'CWQ': ['72.20', '-', '46.69', '51.77', '53.96', '57.54', '64.02', '71.00'],
-        'GrailQA': ['76.31', '-', '29.02', '27.58', '30.50', '35.43', '46.77', '51.40'],
-        'GraphQ': ['41.30', '-', '32.27', '38.32', '40.85', '47.95', '53.10', '63.20'],
-        'QALD-9': ['67.82', '-', '30.17', '38.54', '44.96', '46.19', '45.71', '57.20'],
-        'MKQA': ['46.00', '-', '20.17', '26.97', '30.14', '39.05', '44.30', '59.20']
+        'Datasets': ['metrics','SOTA(FT)', 'SOTA(ZS)', 'FLAN-T5', 'GPT-3', 'GPT-3.5v2', 'GPT-3.5v3', 'ChatGPT', 'GPT-4'],
+        'KQApro': ['Acc','93.85', '94.20', '37.27', '38.28', '38.01', '40.35', '47.93', '57.20'],
+        'LC-quad2': ['F1','33.10', '-', '30.14', '33.04', '33.77', '39.04', '42.76', '54.95'],
+        'WQSP': ['Acc','73.10', '62.98', '59.87', '67.68', '72.34', '79.60', '83.70', '90.45'],
+        'CWQ': ['Acc','72.20', '-', '46.69', '51.77', '53.96', '57.54', '64.02', '71.00'],
+        'GrailQA': ['Acc','76.31', '-', '29.02', '27.58', '30.50', '35.43', '46.77', '51.40'],
+        'GraphQ': ['Acc','41.30', '-', '32.27', '38.32', '40.85', '47.95', '53.10', '63.20'],
+        'QALD-9': ['F1','67.82', '-', '30.17', '38.54', '44.96', '46.19', '45.71', '57.20'],
+        'MKQA': ['Acc','46.00', '-', '20.17', '26.97', '30.14', '39.05', '44.30', '59.20']
     }
 
     df = pd.DataFrame(data)
@@ -41,14 +41,11 @@ def get_leaderboard_df():
 original_df = get_leaderboard_df()
 leaderboard_df = original_df.copy()
 
-
 def search_table(df, query):
     if query == "":
         return df
     else:
-        return df[df.apply(lambda row: query.lower() in row.astype(str).str.lower().any(), axis=1)]
-
-
+        return df[df.apply(lambda row: query.lower() in row.astype(str).lower(), axis=1).any()]
 
 
 demo = gr.Blocks(css=custom_css)