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import json
import gradio as gr
import pandas as pd
from pages.summarization_playground import custom_css
css = '''
.tooltip-wrapper {
position: relative;
display: inline-block;
border-bottom: 1px dotted black;
}
.tooltip-wrapper .tooltip {
visibility: hidden;
width: 120px;
background-color: black;
color: #fff;
text-align: center;
border-radius: 6px;
padding: 5px 0;
position: absolute;
z-index: 1;
bottom: 125%;
left: 50%;
margin-left: -60px;
opacity: 0;
transition: opacity 0.3s;
}
.tooltip-wrapper:hover .tooltip {
visibility: visible;
opacity: 1;
}
'''
with open("prompt/prompt.json", "r") as file:
json_data = file.read()
prompts = json.loads(json_data)# Sample data for the leaderboard
winning_rate = [prompt['metric']['winning_number'] for prompt in prompts]
winning_rate = [num / sum(winning_rate) for num in winning_rate]
data = {
'Rank': [i+1 for i in range(len(prompts))],
'Methods': [prompt['id'] for prompt in prompts],
'Rouge Score': [prompt['metric']['Rouge'] for prompt in prompts],
'Winning Rate': winning_rate,
'Authors': [prompt['author'] for prompt in prompts],
'Prompts': [prompt['prompt'] for prompt in prompts]
}
df = pd.DataFrame(data)
df.sort_values(by='Rouge Score', ascending=False, inplace=True, ignore_index=True)
df['Rank'] = range(1, len(df) + 1)
# Define a list of medal emojis
medals = ['🏅', '🥈', '🥉']
for i in range(3):
df.loc[i, 'Authors'] = f"{medals[i]} {df.loc[i, 'Authors']}"
def create_html_with_tooltip(text, tooltip):
return f'''
<div class="tooltip-wrapper">
{text}
<span class="tooltip">{tooltip}</span>
</div>
'''
def show_tooltip():
text_with_tooltip = create_html_with_tooltip("Hover over me", "This is a tooltip!")
return text_with_tooltip
def update_leaderboard(sort_by):
# In a real implementation, this would filter the data based on the category
sorted_df = df.sort_values(by=sort_by, ascending=False, ignore_index=True)
# Update ranks based on new sorting
sorted_df['Rank'] = range(1, len(sorted_df) + 1)
# Create hover effect for Methods column
sorted_df['Methods'] = sorted_df.apply(lambda row: create_html_with_tooltip(row['Methods'], row['Prompts']), axis=1)
# Drop the 'Prompts' column as we don't want to display it directly
sorted_df = sorted_df.drop(columns=['Prompts'])
# Convert DataFrame to HTML with clickable headers for sorting
html = sorted_df.to_html(index=False, escape=False)
# Add sorting links to column headers
for column in sorted_df.columns:
html = html.replace(f'<th>{column}</th>',
f'<th><a href="#" onclick="sortBy(\'{column}\'); return false;">{column}</a></th>')
return html
def create_leaderboard():
with gr.Blocks(css=custom_css) as demo:
gr.Markdown("# 🏆 Summarization Arena Leaderboard")
with gr.Row():
gr.Markdown("[Blog](placeholder) | [GitHub](placeholder) | [Paper](placeholder) | [Dataset](placeholder) | [Twitter](placeholder) | [Discord](placeholder)")
gr.Markdown("Welcome to our open platform for evaluating LLM summarization capabilities. We use the DATASET_NAME_PLACEHOLDER dataset to generate summaries with MODEL_NAME_PLACEHOLDER. These summaries are then evaluated by STRONGER_MODEL_NAME_PLACEHOLDER using the METRIC1_PLACEHOLDER and METRIC2_PLACEHOLDER metrics")
sort_by = gr.Dropdown(list(df.columns), label="Sort by", value="Rouge Score")
gr.Markdown("**Performance**\n\n**methods**: 5, **questions**: 15")
leaderboard = gr.HTML(update_leaderboard("Rouge Score"), elem_id="leaderboard")
sort_by.change(update_leaderboard, inputs=[sort_by], outputs=[leaderboard])
return demo |