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| import pandas as pd | |
| import html | |
| import json | |
| import gradio as gr | |
| def create_html_with_tooltip(id, prompt): | |
| escaped_prompt = html.escape(prompt.replace("\n", "<br />")) | |
| return f'<span class="tooltip" data-id="{id}" data-prompt="{escaped_prompt}">{id}</span>' | |
| 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': [create_html_with_tooltip(prompt['id'], prompt['prompt'].replace("\n","<br />")) for prompt in prompts], | |
| 'Rouge Score': [prompt['metric']['Rouge'] for prompt in prompts], | |
| 'Winning Rate': winning_rate, | |
| 'Authors': [prompt['author'] 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(id, prompt): | |
| escaped_prompt = html.escape(prompt.replace("\n", "<br />")) | |
| return f'<span class="tooltip" data-id="{id}" data-prompt="{escaped_prompt}">{id}</span>' | |
| def update_leaderboard(sort_by): | |
| sorted_df = df.sort_values(by=sort_by, ascending=False, ignore_index=True) | |
| sorted_df['Rank'] = range(1, len(sorted_df) + 1) | |
| # Convert DataFrame to HTML with clickable headers for sorting and without escaping | |
| table_html = sorted_df.to_html(index=False, escape=False) | |
| # Add sorting links to column headers | |
| for column in sorted_df.columns: | |
| table_html = table_html.replace(f'<th>{column}</th>', | |
| f'<th><a href="#" onclick="sortBy(\'{column}\'); return false;">{column}</a></th>') | |
| # Load the HTML template | |
| with open('pages/leaderboard_template.html', 'r') as file: | |
| template = file.read() | |
| # Create the sortBy function in JavaScript | |
| sort_by_function = f""" | |
| function sortBy(column) {{ | |
| const gradioEl = document.querySelector('gradio-app'); | |
| const dropdown = gradioEl.querySelector('select'); | |
| dropdown.value = column; | |
| dropdown.dispatchEvent(new Event('change')); | |
| }} | |
| """ | |
| # Insert the table HTML and sortBy function into the template | |
| full_html = template.replace('<div id="leaderboard-container"></div>', | |
| f'<div id="leaderboard-container">{table_html}</div>') | |
| full_html = full_html.replace('// This function will be implemented in Python and injected here', | |
| sort_by_function) | |
| return full_html | |
| def create_leaderboard(): | |
| with gr.Blocks(css=""" | |
| .tooltip { cursor: pointer; color: blue; text-decoration: underline; } | |
| """) 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 Qwen2-1.5b. These summaries are then evaluated by Rouge and Winning Rate from the arena") | |
| 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 | |
| if __name__ == "__main__": | |
| demo = create_leaderboard() | |
| demo.launch() |