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import gradio as gr
import json
import pandas as pd
from urllib.request import urlopen
from urllib.error import URLError
import re
from datetime import datetime
# Constants
CITATION_BUTTON_TEXT = r"""@misc{2023opencompass,
title={OpenCompass: A Universal Evaluation Platform for Foundation Models},
author={OpenCompass Contributors},
howpublished = {\url{https://github.com/open-compass/opencompass}},
year={2023}
}"""
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
# 开发环境
# DATA_URL_BASE = "http://opencompass.oss-cn-shanghai.aliyuncs.com/dev-assets/research-rank/research-data.REALTIME."
# DATA_URL_BASE = "./s1test"
# 生产环境
DATA_URL_BASE = "http://opencompass.oss-cn-shanghai.aliyuncs.com/assets/research-rank/research-data.REALTIME."
def find_latest_data_url():
"""Find the latest available data URL by trying different dates."""
today = datetime.now()
for i in range(365):
date = today.replace(day=today.day - i)
date_str = date.strftime("%Y%m%d")
url = f"{DATA_URL_BASE}{date_str}.json"
try:
urlopen(url)
return url, date_str
except URLError:
continue
breakpoint()
return None, None
def get_latest_data():
"""Get latest data URL and update time"""
data_url, update_time = find_latest_data_url()
if not data_url:
raise Exception("Could not find valid data URL")
formatted_update_time = datetime.strptime(update_time, "%Y%m%d").strftime("%Y-%m-%d")
return data_url, formatted_update_time
def get_leaderboard_title(update_time):
return f"# Supported Datasets List (Last Updated: {update_time})"
MAIN_DESCRIPTION = """## The List of Datasets Supported by OpenCompass
Testing line.
- All configurations and datsets can be found in [**OpenCompass**: A Toolkit for Evaluation of LLMs](https://github.com/open-compass/opencompass)🏆.
"""
def load_data(data_url):
response = urlopen(data_url)
with open('s1.json','r',encoding='utf8') as f:
data = json.load(f)
return data
def build_main_table(data):
df = pd.DataFrame(data).transpose()
columns = {
'name': 'Name', 'category': 'Category', 'article': 'Article Address',
}
df = df[list(columns.keys())].rename(columns=columns)
return df
DATA_CATEGORY = ['med', 'law', 'code']
def filter_table1(df, data_category):
filtered_df = df.copy()
if data_category:
mask = pd.Series(False, index=filtered_df.index)
for category in data_category:
mask |= filtered_df['Category'] == category
filtered_df = filtered_df[mask]
return filtered_df
def calculate_column_widths(df):
column_widths = []
for column in df.columns:
header_length = len(str(column))
max_content_length = df[column].astype(str).map(len).max()
width = max(header_length * 10, max_content_length * 8) + 20
width = max(160, min(400, width))
column_widths.append(width)
return column_widths
class DataState:
def __init__(self):
self.current_df = None
data_state = DataState()
def create_interface():
empty_df = pd.DataFrame(columns=[
'Name', 'Category', 'Article Address'
])
def load_initial_data():
try:
data_url, update_time = get_latest_data()
data = load_data(data_url)
new_df = build_main_table(data)
data_state.current_df = new_df
filtered_df = filter_table1(new_df, DATA_CATEGORY)
return get_leaderboard_title(update_time), filtered_df.sort_values("Name", ascending=True)
except Exception as e:
print(f"Error loading initial data: {e}")
return "# Supported Datasets List (Error loading data)", empty_df
def refresh_data():
try:
data_url, update_time = get_latest_data()
data = load_data(data_url)
new_df = build_main_table(data)
data_state.current_df = new_df
filtered_df = filter_table1(new_df, DATA_CATEGORY)
return get_leaderboard_title(update_time), filtered_df.sort_values("Name", ascending=True)
except Exception as e:
print(f"Error refreshing data: {e}")
return None, None
def update_table(category):
if data_state.current_df is None:
return empty_df
filtered_df = filter_table1(data_state.current_df, category)
return filtered_df.sort_values("Name", ascending=True)
initial_title, initial_data = load_initial_data()
with gr.Blocks() as demo:
title_comp = gr.Markdown(initial_title)
with gr.Tabs() as tabs:
with gr.TabItem("Dataset List", elem_id='main'):
gr.Markdown(MAIN_DESCRIPTION)
with gr.Row():
with gr.Column():
category_filter = gr.CheckboxGroup(
choices=DATA_CATEGORY,
value=DATA_CATEGORY,
label='Category',
interactive=True,
)
with gr.Column():
table = gr.DataFrame(
value=initial_data,
interactive=False,
wrap=False,
column_widths=calculate_column_widths(initial_data),
)
refresh_button = gr.Button("Refresh Data")
def refresh_and_update():
title, data = refresh_data()
return title, data
refresh_button.click(
fn=refresh_and_update,
outputs=[title_comp, table],
)
category_filter.change(
fn=update_table,
inputs=[category_filter],
outputs=table,
)
with gr.Row():
with gr.Accordion("Citation", open=False):
citation_button = gr.Textbox(
value=CITATION_BUTTON_TEXT,
label=CITATION_BUTTON_LABEL,
elem_id='citation-button',
lines=6, # 增加行数
max_lines=8, # 设置最大行数
show_copy_button=True # 添加复制按钮使其更方便使用
)
return demo
if __name__ == '__main__':
demo = create_interface()
demo.queue()
demo.launch(server_name='0.0.0.0')