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| import os | |
| import json | |
| import sqlite3 | |
| import glob | |
| import pandas as pd | |
| import gradio as gr | |
| from datetime import datetime | |
| from typing import Dict, List | |
| # Directory to store SQLite results | |
| db_dir = "results/" | |
| def find_or_download_db(): | |
| """Check if SQLite .db files exist; if not, attempt to download from cloud storage.""" | |
| if not os.path.exists(db_dir): | |
| os.makedirs(db_dir) | |
| db_files = glob.glob(os.path.join(db_dir, "*.db")) | |
| # Ensure the random bot database exists | |
| if "results/random_None.db" not in db_files: | |
| raise FileNotFoundError("Please upload results for the random agent in a file named 'random_None.db'.") | |
| return db_files | |
| def extract_agent_info(filename: str): | |
| """Extract agent type and model name from the filename.""" | |
| base_name = os.path.basename(filename).replace(".db", "") | |
| parts = base_name.split("_", 1) | |
| if len(parts) == 2: | |
| agent_type, model_name = parts | |
| else: | |
| agent_type, model_name = parts[0], "Unknown" | |
| return agent_type, model_name | |
| def extract_leaderboard_stats(game_name: str) -> pd.DataFrame: | |
| """Extract and aggregate leaderboard stats from all SQLite databases.""" | |
| db_files = find_or_download_db() | |
| all_stats = [] | |
| for db_file in db_files: | |
| conn = sqlite3.connect(db_file) | |
| agent_type, model_name = extract_agent_info(db_file) | |
| if game_name == "Total Performance": | |
| query = "SELECT game_name, COUNT(DISTINCT episode) AS games_played, " \ | |
| "AVG(generation_time) AS avg_gen_time, SUM(reward) AS total_rewards " \ | |
| "FROM game_results GROUP BY game_name" | |
| else: | |
| query = "SELECT COUNT(DISTINCT episode) AS games_played, " \ | |
| "AVG(generation_time) AS avg_gen_time, SUM(reward) AS total_rewards " \ | |
| "FROM game_results WHERE game_name = ?" | |
| df = pd.read_sql_query(query, conn, params=(game_name,) if game_name != "Total Performance" else None) | |
| df["agent_name"] = model_name | |
| df["agent_type"] = agent_type | |
| all_stats.append(df) | |
| conn.close() | |
| leaderboard_df = pd.concat(all_stats, ignore_index=True) if all_stats else pd.DataFrame() | |
| return leaderboard_df | |
| def generate_leaderboard_json(): | |
| """Generate a JSON file containing leaderboard stats.""" | |
| leaderboard = extract_leaderboard_stats("Total Performance").to_dict(orient="records") | |
| json_file = "results/leaderboard_stats.json" | |
| with open(json_file, "w", encoding="utf-8") as f: | |
| json.dump({"timestamp": datetime.utcnow().isoformat(), "leaderboard": leaderboard}, f, indent=4) | |
| return json_file | |
| with gr.Blocks() as interface: | |
| with gr.Tab("Leaderboard"): | |
| gr.Markdown("# Leaderboard") | |
| leaderboard_game_dropdown = gr.Dropdown(["Total Performance", "tic_tac_toe"], label="Select Game") | |
| leaderboard_table = gr.Dataframe() | |
| download_button = gr.File(label="Download Leaderboard") | |
| refresh_button = gr.Button("Refresh Leaderboard") | |
| leaderboard_game_dropdown.change(extract_leaderboard_stats, inputs=[leaderboard_game_dropdown], outputs=[leaderboard_table]) | |
| refresh_button.click(extract_leaderboard_stats, inputs=[leaderboard_game_dropdown], outputs=[leaderboard_table]) | |
| download_button.click(generate_leaderboard_json, outputs=[download_button]) | |
| interface.launch() | |