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| import json | |
| import pandas as pd | |
| from pathlib import Path | |
| def load_leaderboard_from_json(json_path="leaderboard_data.json"): | |
| """Load leaderboard data from JSON file""" | |
| try: | |
| with open(json_path, 'r', encoding='utf-8') as f: | |
| data = json.load(f) | |
| return data['leaderboard'] | |
| except FileNotFoundError: | |
| print(f"JSON file {json_path} not found") | |
| return [] | |
| except json.JSONDecodeError: | |
| print(f"Error decoding JSON file {json_path}") | |
| return [] | |
| def create_leaderboard_df(json_path="leaderboard_data.json"): | |
| """Create a pandas DataFrame from JSON leaderboard data""" | |
| leaderboard_data = load_leaderboard_from_json(json_path) | |
| if not leaderboard_data: | |
| return pd.DataFrame() | |
| # Convert to DataFrame | |
| df = pd.DataFrame(leaderboard_data) | |
| # Sort by ACC score (descending) | |
| df = df.sort_values('acc', ascending=False).reset_index(drop=True) | |
| # Add ranking icons and make model names clickable links to papers | |
| def add_ranking_icon_and_link(index, model_name, paper_link): | |
| if index == 0: | |
| return f'π₯ <a href="{paper_link}" target="_blank">{model_name}</a>' | |
| elif index == 1: | |
| return f'π₯ <a href="{paper_link}" target="_blank">{model_name}</a>' | |
| elif index == 2: | |
| return f'π₯ <a href="{paper_link}" target="_blank">{model_name}</a>' | |
| else: | |
| return f'<a href="{paper_link}" target="_blank">{model_name}</a>' | |
| # Format the DataFrame for display | |
| display_df = pd.DataFrame({ | |
| 'Model': [add_ranking_icon_and_link(i, model, link) for i, (model, link) in enumerate(zip(df['model'], df['link']))], | |
| 'Release Date': df['release_date'], | |
| 'HF Model': df['hf'].apply(lambda x: f'<a href="{x}" target="_blank">π€</a>' if x != "-" else "-"), | |
| 'MoE': df['moe'].apply(lambda x: '-' if x == '-' else ('β' if x else 'β')), | |
| 'Parameters': df['params'], | |
| 'Open Source': df['open_source'].apply(lambda x: 'β' if x else 'β'), | |
| 'ACC Score': df['acc'].apply(lambda x: f"{x:.1f}") | |
| }) | |
| return display_df | |
| def get_leaderboard_stats(json_path="leaderboard_data.json"): | |
| """Get statistics about the leaderboard""" | |
| leaderboard_data = load_leaderboard_from_json(json_path) | |
| if not leaderboard_data: | |
| return {} | |
| df = pd.DataFrame(leaderboard_data) | |
| stats = { | |
| 'total_models': len(df), | |
| 'open_source_models': df['open_source'].sum(), | |
| 'moe_models': df['moe'].apply(lambda x: 1 if x is True else 0).sum(), | |
| 'avg_acc': df['acc'].mean(), | |
| 'max_acc': df['acc'].max(), | |
| 'min_acc': df['acc'].min() | |
| } | |
| return stats | |