Updated to have games as drop-down list

app.py

@@ -26,83 +26,51 @@ if os.path.exists(RESULTS_TRACKER_FILE):
         results_tracker = json.load(f)
 else:
     results_tracker = {
-        llm: {game: {"wins": 0, "ties": 0, "losses": 0, "games": 0} for game in games_list}
+        llm: {game: {"games": 0, "moves/game": 0, "illegal-moves": 0,
+                     "win-rate": 0, "vs Random": 0} for game in games_list}
         for llm in llm_models
     }
 
-
 def save_results_tracker():
     """Save the results tracker to a JSON file."""
     with open(RESULTS_TRACKER_FILE, "w") as f:
         json.dump(results_tracker, f, indent=4)
 
-
-def calculate_leaderboard():
-    """Generate a structured leaderboard table summarizing LLM performance across games."""
+def calculate_leaderboard(selected_game: str) -> pd.DataFrame:
+    """Generate a structured leaderboard table for the selected game."""
+    leaderboard_df = pd.DataFrame(index=llm_models, 
+                                  columns=["# games", "moves/game", 
+                                           "illegal-moves", "win-rate", "vs Random"])
     
-    # Create a DataFrame where rows are LLMs and columns are games
-    leaderboard_df = pd.DataFrame(index=llm_models, columns=games_list)
-
     for llm in llm_models:
-        for game in games_list:
-            games_played = max(1, results_tracker[llm][game]['games'])  # Avoid division by zero
-            wins = (results_tracker[llm][game]['wins'] / games_played) * 100
-            ties = (results_tracker[llm][game]['ties'] / games_played) * 100
-            losses = (results_tracker[llm][game]['losses'] / games_played) * 100
-
-            # Format as percentage string
-            leaderboard_df.loc[llm, game] = f"{wins:.1f}% W / {ties:.1f}% T / {losses:.1f}% L"
-
-    # Ensure LLM names appear in the first column
+        game_stats = results_tracker[llm].get(selected_game, {})
+        leaderboard_df.loc[llm] = [
+            game_stats.get("games", 0),
+            game_stats.get("moves/game", 0),
+            game_stats.get("illegal-moves", 0),
+            f"{game_stats.get('win-rate', 0):.1f}%",
+            f"{game_stats.get('vs Random', 0):.1f}%"
+        ]
+    
     leaderboard_df = leaderboard_df.reset_index()
     leaderboard_df.rename(columns={"index": "LLM Model"}, inplace=True)
-
     return leaderboard_df
 
-
-def get_model_details(model_name):
-    """Returns detailed performance breakdown of the selected LLM model."""
-    if model_name not in results_tracker:
-        return "No data available for this model."
-
-    details = f"### {model_name} Performance Breakdown\n"
-    for game, record in results_tracker[model_name].items():
-        total_games = record["games"]
-        details += (
-            f"- **{game.capitalize()}**: {record['wins']} Wins, "
-            f"{record['ties']} Ties, {record['losses']} Losses (Total: {total_games})\n"
-        )
-
-    return details
-
-
 # Gradio Interface
 with gr.Blocks() as interface:
     with gr.Tab("Game Arena"):
         gr.Markdown("# LLM Game Arena\nPlay against LLMs or other players in classic games!")
 
-        # (Game selection and play functionality remains unchanged)
-
     with gr.Tab("Leaderboard"):
         gr.Markdown("# LLM Model Leaderboard\nTrack performance across different games!")
-
-        leaderboard_table = gr.Dataframe(value=calculate_leaderboard(), label="Leaderboard")
-
-        with gr.Row():
-            model_dropdown = gr.Dropdown(choices=llm_models, label="Select LLM Model")
-        details_output = gr.Textbox(label="Model Performance Details", interactive=False)
-
-        def update_leaderboard():
-            """Updates the leaderboard table."""
-            return calculate_leaderboard()
-
-        def update_details(model_name):
-            """Updates the details section when an LLM is selected."""
-            return get_model_details(model_name)
-
-        update_leaderboard_button = gr.Button("Refresh Leaderboard")
-        update_leaderboard_button.click(fn=update_leaderboard, inputs=[], outputs=[leaderboard_table])
-
-        model_dropdown.change(fn=update_details, inputs=[model_dropdown], outputs=[details_output])
+        
+        game_dropdown = gr.Dropdown(choices=games_list, label="Select Game", value=games_list[0])
+        leaderboard_table = gr.Dataframe(value=calculate_leaderboard(games_list[0]), label="Leaderboard")
+        
+        def update_leaderboard(selected_game):
+            """Updates the leaderboard table based on the selected game."""
+            return calculate_leaderboard(selected_game)
+        
+        game_dropdown.change(fn=update_leaderboard, inputs=[game_dropdown], outputs=[leaderboard_table])
 
 interface.launch()