Update app.py

app.py

@@ -4,20 +4,20 @@ import pandas as pd
 from math import isnan
 
 ROWS = [
-    {"Team_name":"Nguyen Quang Thao","vi-law-nli (4-shot)":0.5816,"vi-law-qa (4 shot)":0.8217,"vilaw-syllo scale":0.38,"Final Result":0.5944333333},
-    {"Team_name":"NHK","vi-law-nli (4-shot)":0.9333,"vi-law-qa (4 shot)":0.8683,"vilaw-syllo scale":0.3275,"Final Result":0.7097},
-    {"Team_name":"Innovation-LLM","vi-law-nli (4-shot)":0.9567,"vi-law-qa (4 shot)":0.8367,"vilaw-syllo scale":0.541666667,"Final Result":0.7783555556},
-    {"Team_name":"Bosch@AI Team","vi-law-nli (4-shot)":0.97,"vi-law-qa (4 shot)":0.9267,"vilaw-syllo scale":0.535833333,"Final Result":0.8108444444},
-    {"Team_name":"URAx","vi-law-nli (4-shot)":0.945,"vi-law-qa (4 shot)":0.8333,"vilaw-syllo scale":0.576666667,"Final Result":0.7849888889},
-    {"Team_name":"Abe","vi-law-nli (4-shot)":0.82,"vi-law-qa (4 shot)":0.84,"vilaw-syllo scale":0.2875,"Final Result":0.6491666667},
-    {"Team_name":"PSLV-Warrior","vi-law-nli (4-shot)":0.565,"vi-law-qa (4 shot)":0.0333,"vilaw-syllo scale":0.525,"Final Result":0.3744333333},
-    {"Team_name":"MinLegal","vi-law-nli (4-shot)":0.98,"vi-law-qa (4 shot)":0.8733,"vilaw-syllo scale":0.530833333,"Final Result":0.7947111111},
-    {"Team_name":"NLPhi","vi-law-nli (4-shot)":0.6517,"vi-law-qa (4 shot)":0.815,"vilaw-syllo scale":0.479166667,"Final Result":0.6486222222},
-    {"Team_name":"LICTU","vi-law-nli (4-shot)":0.8467,"vi-law-qa (4 shot)":0.8067,"vilaw-syllo scale":0.5375,"Final Result":0.7303},
+    {"Team_name":"Nguyen Quang Thao","vi-law-nli (4-shot)":0.5816,"vi-law-qa (4 shot)":0.8217,"vilaw-syllo":0.38,"Final Result":0.5944333333},
+    {"Team_name":"NHK","vi-law-nli (4-shot)":0.9333,"vi-law-qa (4 shot)":0.8683,"vilaw-syllo":0.3275,"Final Result":0.7097},
+    {"Team_name":"Innovation-LLM","vi-law-nli (4-shot)":0.9567,"vi-law-qa (4 shot)":0.8367,"vilaw-syllo":0.541666667,"Final Result":0.7783555556},
+    {"Team_name":"Bosch@AI Team","vi-law-nli (4-shot)":0.97,"vi-law-qa (4 shot)":0.9267,"vilaw-syllo":0.535833333,"Final Result":0.8108444444},
+    {"Team_name":"URAx","vi-law-nli (4-shot)":0.945,"vi-law-qa (4 shot)":0.8333,"vilaw-syllo":0.576666667,"Final Result":0.7849888889},
+    {"Team_name":"Abe","vi-law-nli (4-shot)":0.82,"vi-law-qa (4 shot)":0.84,"vilaw-syllo":0.2875,"Final Result":0.6491666667},
+    {"Team_name":"PSLV-Warrior","vi-law-nli (4-shot)":0.565,"vi-law-qa (4 shot)":0.0333,"vilaw-syllo":0.525,"Final Result":0.3744333333},
+    {"Team_name":"MinLegal","vi-law-nli (4-shot)":0.98,"vi-law-qa (4 shot)":0.8733,"vilaw-syllo":0.530833333,"Final Result":0.7947111111},
+    {"Team_name":"NLPhi","vi-law-nli (4-shot)":0.6517,"vi-law-qa (4 shot)":0.815,"vilaw-syllo":0.479166667,"Final Result":0.6486222222},
+    {"Team_name":"LICTU","vi-law-nli (4-shot)":0.8467,"vi-law-qa (4 shot)":0.8067,"vilaw-syllo":0.5375,"Final Result":0.7303},
 ]
 BASE_DF = pd.DataFrame(ROWS)
 
-NUM_COLS = ["vi-law-nli (4-shot)", "vi-law-qa (4 shot)", "vilaw-syllo scale", "Final Result"]
+NUM_COLS = ["vi-law-nli (4-shot)", "vi-law-qa (4 shot)", "vilaw-syllo", "Final Result"]
 
 def _prep_df(df: pd.DataFrame) -> pd.DataFrame:
     out = df.copy()
@@ -43,7 +43,7 @@ def _render_table(df: pd.DataFrame) -> str:
             f"<td class='team'>{row['Team_name']}</td>",
             f"<td>{_bar_html(row['vi-law-nli (4-shot)'])}</td>",
             f"<td>{_bar_html(row['vi-law-qa (4 shot)'])}</td>",
-            f"<td>{_bar_html(row['vilaw-syllo scale'])}</td>",
+            f"<td>{_bar_html(row['vilaw-syllo'])}</td>",
             f"<td>{_bar_html(row['Final Result'])}</td>",
         ]
         rows_html.append(f"<tr>{''.join(tds)}</tr>")