Spaces:
Building
Building
File size: 5,291 Bytes
5b27273 d70e16b 5b27273 d70e16b 5b27273 d70e16b 5b27273 d70e16b 5b27273 d70e16b 5b27273 36713b7 5b27273 d70e16b f60b1f2 d70e16b 71e3f1c d70e16b 7d93964 d70e16b 7d93964 d70e16b 459aaf8 d70e16b a7a733e d70e16b 459aaf8 d70e16b 5b27273 d70e16b d2dff95 5b27273 d70e16b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 |
import gradio as gr
__all__ = ["block", "make_clickable_model", "make_clickable_user", "get_submissions"]
import numpy as np
import pandas as pd
from constants import *
from src.auto_leaderboard.model_metadata_type import ModelType
global data_component, filter_component, ref_dic
def upload_file(files):
file_paths = [file.name for file in files]
return file_paths
def read_xlsx_leaderboard():
df_dict = pd.read_excel(XLSX_DIR, sheet_name=None) # get all sheet
return df_dict
def get_specific_df(sheet_name):
df = read_xlsx_leaderboard()[sheet_name].sort_values(by="Overall", ascending=False)
return df
def get_link_df(sheet_name):
df = read_xlsx_leaderboard()[sheet_name]
return df
ref_df = get_link_df("main")
ref_dic = {}
for id, row in ref_df.iterrows():
ref_dic[
str(row["Model"])
] = f'<a href="{row["Link"]}" target="_blank" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{row["Model"]}</a>'
def wrap_model(func):
def wrapper(*args, **kwargs):
df = func(*args, **kwargs)
df["Model"] = df["Model"].apply(lambda x: ref_dic[x])
# cols_to_round = df.select_dtypes(include=[np.number]).columns.tolist()
# cols_to_round = [col for col in cols_to_round if col != "Model"]
# df[cols_to_round] = df[cols_to_round].apply(lambda x: np.round(x, 2))
all_cols = df.columns.tolist()
non_numeric_cols = df.select_dtypes(exclude=[np.number]).columns.tolist()
cols_to_round = [col for col in all_cols if col not in non_numeric_cols and col != "Model"]
df[cols_to_round] = df[cols_to_round].apply(lambda x: np.round(x, 2))
return df
return wrapper
@wrap_model
def get_base_zh_df():
return get_specific_df("base-zh")
@wrap_model
def get_base_en_df():
return get_specific_df("base-en")
@wrap_model
def get_attack_zh_df():
return get_specific_df("attack-zh")
@wrap_model
def get_attack_en_df():
return get_specific_df("attack-en")
def build_leaderboard(
TABLE_INTRODUCTION, TAX_COLUMNS, get_chinese_df, get_english_df
):
gr.Markdown(TABLE_INTRODUCTION, elem_classes="markdown-text")
data_spilt_radio = gr.Radio(
choices=["Chinese", "English"],
value="Chinese",
label=SELECT_SET_INTRO,
)
# 创建数据帧组件
data_component = gr.components.Dataframe(
value=get_chinese_df,
headers=OVERALL_INFO + TAX_COLUMNS,
type="pandas",
datatype=["markdown"] + ["number"] + ["number"] * len(TAX_COLUMNS),
interactive=False,
visible=True,
wrap=True,
column_widths=[250] + [100] + [150] * len(TAX_COLUMNS),
)
def on_data_split_radio(seleted_split):
if "Chinese" in seleted_split:
updated_data = get_chinese_df()
if "English" in seleted_split:
updated_data = get_english_df()
current_columns = data_component.headers # 获取的当前的column
current_datatype = data_component.datatype # 获取当前的datatype
filter_component = gr.components.Dataframe(
value=updated_data,
headers=current_columns,
type="pandas",
datatype=current_datatype,
interactive=False,
visible=True,
wrap=True,
column_widths=[250] + [100] + [150] * (len(current_columns) - 2),
)
return filter_component
# 关联处理函数
data_spilt_radio.change(
fn=on_data_split_radio, inputs=data_spilt_radio, outputs=data_component
)
def build_demo():
block = gr.Blocks()
with block:
gr.Markdown(LEADERBOARD_INTRODUCTION)
with gr.Tabs(elem_classes="tab-buttons") as tabs:
# first
with gr.TabItem(
"Base Risk Prompt Set Results",
elem_id="evalcrafter-benchmark-tab-table",
id=0,
):
build_leaderboard(
TABLE_INTRODUCTION_1,
risk_topic_1_columns,
get_base_zh_df,
get_base_en_df
)
# second
with gr.TabItem(
"Attack Prompt Set Results",
elem_id="evalcrafter-benchmark-tab-table",
id=1,
):
build_leaderboard(
TABLE_INTRODUCTION_2,
attack_columns,
get_attack_zh_df,
get_attack_en_df
)
# last table about
with gr.TabItem("📝 About", elem_id="evalcrafter-benchmark-tab-table", id=3):
gr.Markdown(LEADERBORAD_INFO, elem_classes="markdown-text")
with gr.Row():
with gr.Accordion("📙 Citation", open=True):
citation_button = gr.Textbox(
value=CITATION_BUTTON_TEXT,
label=CITATION_BUTTON_LABEL,
lines=10,
elem_id="citation-button",
show_label=True,
show_copy_button=True,
)
# block.launch(share=True)
block.launch()
if __name__ == "__main__":
build_demo()
|