Update app.py

app.py

@@ -80,15 +80,53 @@ def extract_leaderboard_stats(game_name: str) -> pd.DataFrame:
         
         # Calculate win rate against random bot
         vs_random_query = """
-            SELECT COUNT(*) FROM game_results gr
-            JOIN moves m ON gr.game_name = m.game_name AND gr.episode = m.episode
-            WHERE gr.game_name = ? AND m.opponent = 'random_None' AND gr.reward > 0
+            SELECT COUNT(*) FROM game_results 
+            WHERE game_name = ? AND opponent = 'random_None' AND reward > 0
         """
         total_vs_random_query = """
-            SELECT COUNT(*) FROM game_results gr
-            JOIN moves m ON gr.game_name = m.game_name AND gr.episode = m.episode
-            WHERE gr.game_name = ? AND m.opponent = 'random_None'
+            SELECT COUNT(*) FROM game_results 
+            WHERE game_name = ? AND opponent = 'random_None'
         """
         wins_vs_random = conn.execute(vs_random_query, (game_name,)).fetchone()[0] or 0
         total_vs_random = conn.execute(total_vs_random_query, (game_name,)).fetchone()[0] or 0
-        vs_random_rate = (wins_vs_random / total_vs_random
+        vs_random_rate = (wins_vs_random / total_vs_random * 100) if total_vs_random > 0 else 0
+        
+        df["agent_name"] = model_name
+        df["agent_type"] = agent_type
+        df["avg_generation_time"] = round(avg_gen_time, 2)
+        df["vs_random"] = round(vs_random_rate, 2)
+        
+        all_stats.append(df)
+        conn.close()
+    
+    leaderboard_df = pd.concat(all_stats, ignore_index=True) if all_stats else pd.DataFrame()
+    
+    if leaderboard_df.empty:
+        leaderboard_df = pd.DataFrame(columns=["LLM Model", "# games", "total rewards", "avg gen time", "win-rate", "vs Random"])
+    
+    return leaderboard_df
+
+def generate_leaderboard_json():
+    """Generate a JSON file containing leaderboard stats."""
+    available_games = get_available_games()
+    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("# LLM Model Leaderboard\nTrack performance across different games!")
+        available_games = get_available_games()
+        leaderboard_game_dropdown = gr.Dropdown(available_games, label="Select Game", value="Total Performance")
+        leaderboard_table = gr.Dataframe(headers=["LLM Model", "# games", "total rewards", "avg gen time", "win-rate", "vs Random"])
+        generate_button = gr.Button("Generate Leaderboard JSON")
+        download_component = gr.File(label="Download Leaderboard JSON")
+        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])
+        generate_button.click(generate_leaderboard_json, outputs=[download_component])
+
+interface.launch()