DontPlanToEnd commited on
Commit
89b4b95
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1 Parent(s): 166ac61

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +13 -19
app.py CHANGED
@@ -2,6 +2,7 @@ import gradio as gr
2
  import pandas as pd
3
  import numpy as np
4
  from functools import partial
 
5
 
6
  custom_css = """
7
  .tab-nav button {
@@ -63,7 +64,7 @@ def load_leaderboard_data(csv_file_path):
63
  return pd.DataFrame(columns=UGI_COLS + WRITING_STYLE_COLS + ANIME_RATING_COLS)
64
 
65
  # Update the leaderboard table based on the search query and parameter range filters
66
- def update_table(df: pd.DataFrame, query: str, param_ranges: list, columns: list, w10_min: float, w10_max: float) -> pd.DataFrame:
67
  filtered_df = df.copy()
68
  if param_ranges:
69
  param_mask = pd.Series(False, index=filtered_df.index)
@@ -91,7 +92,7 @@ def update_table(df: pd.DataFrame, query: str, param_ranges: list, columns: list
91
 
92
  # Apply W/10 filtering
93
  if 'W/10 πŸ‘' in filtered_df.columns:
94
- filtered_df = filtered_df[(filtered_df['W/10 πŸ‘'] >= w10_min) & (filtered_df['W/10 πŸ‘'] <= w10_max)]
95
 
96
  return filtered_df[columns]
97
 
@@ -126,8 +127,7 @@ with GraInter:
126
  elem_id="filter-columns-size",
127
  )
128
  with gr.Row():
129
- w10_min = gr.Slider(minimum=0, maximum=10, value=0, step=0.1, label="Min W/10")
130
- w10_max = gr.Slider(minimum=0, maximum=10, value=10, step=0.1, label="Max W/10")
131
 
132
  # Load the initial leaderboard data
133
  leaderboard_df = load_leaderboard_data("ugi-leaderboard-data.csv")
@@ -247,42 +247,36 @@ with GraInter:
247
  **NA:** When models either reply with one number for every anime, give ratings not between 1 and 10, or don't give every anime in the list a rating.
248
  """)
249
 
250
- def update_all_tables(query, param_ranges, w10_min, w10_max):
251
- ugi_table = update_table(leaderboard_df, query, param_ranges, UGI_COLS, w10_min, w10_max)
252
 
253
  ws_df = leaderboard_df.sort_values(by='Reg+MyScore πŸ†', ascending=False)
254
- ws_table = update_table(ws_df, query, param_ranges, WRITING_STYLE_COLS, w10_min, w10_max)
255
 
256
  arp_df = leaderboard_df.sort_values(by='Score πŸ†', ascending=False)
257
  arp_df_na = arp_df[arp_df[['Dif', 'Cor']].isna().any(axis=1)]
258
  arp_df = arp_df[~arp_df[['Dif', 'Cor']].isna().any(axis=1)]
259
 
260
- arp_table = update_table(arp_df, query, param_ranges, ANIME_RATING_COLS, w10_min, w10_max)
261
- arp_na_table = update_table(arp_df_na, query, param_ranges, ANIME_RATING_COLS, w10_min, w10_max).fillna('NA')
262
 
263
  return ugi_table, ws_table, arp_table, arp_na_table
264
 
265
  search_bar.change(
266
  fn=update_all_tables,
267
- inputs=[search_bar, filter_columns_size, w10_min, w10_max],
268
  outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
269
  )
270
 
271
  filter_columns_size.change(
272
  fn=update_all_tables,
273
- inputs=[search_bar, filter_columns_size, w10_min, w10_max],
274
  outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
275
  )
276
 
277
- w10_min.change(
278
  fn=update_all_tables,
279
- inputs=[search_bar, filter_columns_size, w10_min, w10_max],
280
- outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
281
- )
282
-
283
- w10_max.change(
284
- fn=update_all_tables,
285
- inputs=[search_bar, filter_columns_size, w10_min, w10_max],
286
  outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
287
  )
288
 
 
2
  import pandas as pd
3
  import numpy as np
4
  from functools import partial
5
+ from gradio_rangeslider import RangeSlider
6
 
7
  custom_css = """
8
  .tab-nav button {
 
64
  return pd.DataFrame(columns=UGI_COLS + WRITING_STYLE_COLS + ANIME_RATING_COLS)
65
 
66
  # Update the leaderboard table based on the search query and parameter range filters
67
+ def update_table(df: pd.DataFrame, query: str, param_ranges: list, columns: list, w10_range: tuple) -> pd.DataFrame:
68
  filtered_df = df.copy()
69
  if param_ranges:
70
  param_mask = pd.Series(False, index=filtered_df.index)
 
92
 
93
  # Apply W/10 filtering
94
  if 'W/10 πŸ‘' in filtered_df.columns:
95
+ filtered_df = filtered_df[(filtered_df['W/10 πŸ‘'] >= w10_range[0]) & (filtered_df['W/10 πŸ‘'] <= w10_range[1])]
96
 
97
  return filtered_df[columns]
98
 
 
127
  elem_id="filter-columns-size",
128
  )
129
  with gr.Row():
130
+ w10_range = RangeSlider(minimum=0, maximum=10, value=(0, 10), step=0.1, label="W/10 Range")
 
131
 
132
  # Load the initial leaderboard data
133
  leaderboard_df = load_leaderboard_data("ugi-leaderboard-data.csv")
 
247
  **NA:** When models either reply with one number for every anime, give ratings not between 1 and 10, or don't give every anime in the list a rating.
248
  """)
249
 
250
+ def update_all_tables(query, param_ranges, w10_range):
251
+ ugi_table = update_table(leaderboard_df, query, param_ranges, UGI_COLS, w10_range)
252
 
253
  ws_df = leaderboard_df.sort_values(by='Reg+MyScore πŸ†', ascending=False)
254
+ ws_table = update_table(ws_df, query, param_ranges, WRITING_STYLE_COLS, w10_range)
255
 
256
  arp_df = leaderboard_df.sort_values(by='Score πŸ†', ascending=False)
257
  arp_df_na = arp_df[arp_df[['Dif', 'Cor']].isna().any(axis=1)]
258
  arp_df = arp_df[~arp_df[['Dif', 'Cor']].isna().any(axis=1)]
259
 
260
+ arp_table = update_table(arp_df, query, param_ranges, ANIME_RATING_COLS, w10_range)
261
+ arp_na_table = update_table(arp_df_na, query, param_ranges, ANIME_RATING_COLS, w10_range).fillna('NA')
262
 
263
  return ugi_table, ws_table, arp_table, arp_na_table
264
 
265
  search_bar.change(
266
  fn=update_all_tables,
267
+ inputs=[search_bar, filter_columns_size, w10_range],
268
  outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
269
  )
270
 
271
  filter_columns_size.change(
272
  fn=update_all_tables,
273
+ inputs=[search_bar, filter_columns_size, w10_range],
274
  outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
275
  )
276
 
277
+ w10_range.change(
278
  fn=update_all_tables,
279
+ inputs=[search_bar, filter_columns_size, w10_range],
 
 
 
 
 
 
280
  outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
281
  )
282