DontPlanToEnd
commited on
Commit
β’
2c172cf
1
Parent(s):
889773e
Update app.py
Browse files
app.py
CHANGED
@@ -42,7 +42,27 @@ WRITING_STYLE_COLS = ['#P', 'Model', 'Reg+MyScore π', 'Reg+Int π', 'MyScor
|
|
42 |
ANIME_RATING_COLS = ['#P', 'Model', 'Score π', 'Dif', 'Cor', 'Std']
|
43 |
|
44 |
# Load the leaderboard data from a CSV file
|
45 |
-
def
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
46 |
filtered_df = df.copy()
|
47 |
if param_ranges:
|
48 |
param_mask = pd.Series(False, index=filtered_df.index)
|
@@ -65,9 +85,6 @@ def update_table(df: pd.DataFrame, query: str, param_ranges: list, w10_range: li
|
|
65 |
param_mask |= (filtered_df['Params'] >= 65)
|
66 |
filtered_df = filtered_df[param_mask]
|
67 |
|
68 |
-
# Apply W/10 filter
|
69 |
-
filtered_df = filtered_df[(filtered_df['W/10 π'] >= w10_range[0]) & (filtered_df['W/10 π'] <= w10_range[1])]
|
70 |
-
|
71 |
if query:
|
72 |
filtered_df = filtered_df[filtered_df['Model'].str.contains(query, case=False, na=False)]
|
73 |
|
@@ -103,15 +120,6 @@ with GraInter:
|
|
103 |
interactive=True,
|
104 |
elem_id="filter-columns-size",
|
105 |
)
|
106 |
-
with gr.Row():
|
107 |
-
w10_slider = gr.Slider(
|
108 |
-
minimum=0,
|
109 |
-
maximum=10,
|
110 |
-
value=[0, 10],
|
111 |
-
step=0.1,
|
112 |
-
label="W/10 Range",
|
113 |
-
elem_id="w10-slider"
|
114 |
-
)
|
115 |
|
116 |
# Load the initial leaderboard data
|
117 |
leaderboard_df = load_leaderboard_data("ugi-leaderboard-data.csv")
|
@@ -231,36 +239,30 @@ with GraInter:
|
|
231 |
**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.
|
232 |
""")
|
233 |
|
234 |
-
def update_all_tables(query, param_ranges
|
235 |
-
ugi_table = update_table(leaderboard_df, query, param_ranges,
|
236 |
|
237 |
ws_df = leaderboard_df.sort_values(by='Reg+MyScore π', ascending=False)
|
238 |
-
ws_table = update_table(ws_df, query, param_ranges,
|
239 |
|
240 |
arp_df = leaderboard_df.sort_values(by='Score π', ascending=False)
|
241 |
arp_df_na = arp_df[arp_df[['Dif', 'Cor']].isna().any(axis=1)]
|
242 |
arp_df = arp_df[~arp_df[['Dif', 'Cor']].isna().any(axis=1)]
|
243 |
|
244 |
-
arp_table = update_table(arp_df, query, param_ranges,
|
245 |
-
arp_na_table = update_table(arp_df_na, query, param_ranges,
|
246 |
|
247 |
return ugi_table, ws_table, arp_table, arp_na_table
|
248 |
|
249 |
search_bar.change(
|
250 |
fn=update_all_tables,
|
251 |
-
inputs=[search_bar, filter_columns_size
|
252 |
outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
|
253 |
)
|
254 |
|
255 |
filter_columns_size.change(
|
256 |
fn=update_all_tables,
|
257 |
-
inputs=[search_bar, filter_columns_size
|
258 |
-
outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
|
259 |
-
)
|
260 |
-
|
261 |
-
w10_slider.change(
|
262 |
-
fn=update_all_tables,
|
263 |
-
inputs=[search_bar, filter_columns_size, w10_slider],
|
264 |
outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
|
265 |
)
|
266 |
|
|
|
42 |
ANIME_RATING_COLS = ['#P', 'Model', 'Score π', 'Dif', 'Cor', 'Std']
|
43 |
|
44 |
# Load the leaderboard data from a CSV file
|
45 |
+
def load_leaderboard_data(csv_file_path):
|
46 |
+
try:
|
47 |
+
df = pd.read_csv(csv_file_path)
|
48 |
+
df['Model'] = df.apply(lambda row: f'<a href="{row["Link"]}" target="_blank" style="color: blue; text-decoration: none;">{row["Model"]}</a>' if pd.notna(row["Link"]) else row["Model"], axis=1)
|
49 |
+
df.drop(columns=['Link'], inplace=True)
|
50 |
+
|
51 |
+
# Round numeric columns to 3 decimal places
|
52 |
+
numeric_columns = df.select_dtypes(include=[np.number]).columns
|
53 |
+
df[numeric_columns] = df[numeric_columns].round(3)
|
54 |
+
|
55 |
+
# Round the W/10 column to 1 decimal place
|
56 |
+
if 'W/10 π' in df.columns:
|
57 |
+
df['W/10 π'] = df['W/10 π'].round(1)
|
58 |
+
|
59 |
+
return df
|
60 |
+
except Exception as e:
|
61 |
+
print(f"Error loading CSV file: {e}")
|
62 |
+
return pd.DataFrame(columns=UGI_COLS + WRITING_STYLE_COLS + ANIME_RATING_COLS)
|
63 |
+
|
64 |
+
# Update the leaderboard table based on the search query and parameter range filters
|
65 |
+
def update_table(df: pd.DataFrame, query: str, param_ranges: list, columns: list) -> pd.DataFrame:
|
66 |
filtered_df = df.copy()
|
67 |
if param_ranges:
|
68 |
param_mask = pd.Series(False, index=filtered_df.index)
|
|
|
85 |
param_mask |= (filtered_df['Params'] >= 65)
|
86 |
filtered_df = filtered_df[param_mask]
|
87 |
|
|
|
|
|
|
|
88 |
if query:
|
89 |
filtered_df = filtered_df[filtered_df['Model'].str.contains(query, case=False, na=False)]
|
90 |
|
|
|
120 |
interactive=True,
|
121 |
elem_id="filter-columns-size",
|
122 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
123 |
|
124 |
# Load the initial leaderboard data
|
125 |
leaderboard_df = load_leaderboard_data("ugi-leaderboard-data.csv")
|
|
|
239 |
**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.
|
240 |
""")
|
241 |
|
242 |
+
def update_all_tables(query, param_ranges):
|
243 |
+
ugi_table = update_table(leaderboard_df, query, param_ranges, UGI_COLS)
|
244 |
|
245 |
ws_df = leaderboard_df.sort_values(by='Reg+MyScore π', ascending=False)
|
246 |
+
ws_table = update_table(ws_df, query, param_ranges, WRITING_STYLE_COLS)
|
247 |
|
248 |
arp_df = leaderboard_df.sort_values(by='Score π', ascending=False)
|
249 |
arp_df_na = arp_df[arp_df[['Dif', 'Cor']].isna().any(axis=1)]
|
250 |
arp_df = arp_df[~arp_df[['Dif', 'Cor']].isna().any(axis=1)]
|
251 |
|
252 |
+
arp_table = update_table(arp_df, query, param_ranges, ANIME_RATING_COLS)
|
253 |
+
arp_na_table = update_table(arp_df_na, query, param_ranges, ANIME_RATING_COLS).fillna('NA')
|
254 |
|
255 |
return ugi_table, ws_table, arp_table, arp_na_table
|
256 |
|
257 |
search_bar.change(
|
258 |
fn=update_all_tables,
|
259 |
+
inputs=[search_bar, filter_columns_size],
|
260 |
outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
|
261 |
)
|
262 |
|
263 |
filter_columns_size.change(
|
264 |
fn=update_all_tables,
|
265 |
+
inputs=[search_bar, filter_columns_size],
|
|
|
|
|
|
|
|
|
|
|
|
|
266 |
outputs=[leaderboard_table_ugi, leaderboard_table_ws, leaderboard_table_arp, leaderboard_table_arp_na]
|
267 |
)
|
268 |
|