Delete internal_stats.py

internal_stats.py

@@ -1,193 +0,0 @@
-import json
-from datetime import datetime, timezone
-from typing import Dict, Any
-from nc_py_api import Nextcloud
-import arena_config
-from leaderboard import load_leaderboard, get_human_readable_name, get_model_size
-
-def get_internal_stats() -> Dict[str, Any]:
-    leaderboard = load_leaderboard()
-    
-    total_battles = sum(
-        model_data['wins'] + model_data['losses']
-        for model_data in leaderboard.values()
-    )
-    
-    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    
-    active_models = len(leaderboard)
-    
-    most_battles = max(
-        (model_data['wins'] + model_data['losses'], model)
-        for model, model_data in leaderboard.items()
-    )
-    
-    highest_win_rate = max(
-        (model_data['wins'] / (model_data['wins'] + model_data['losses']) if (model_data['wins'] + model_data['losses']) > 0 else 0, model)
-        for model, model_data in leaderboard.items()
-    )
-    
-    most_diverse_opponent = max(
-        (len(model_data['opponents']), model)
-        for model, model_data in leaderboard.items()
-    )
-    
-    stats = {
-        "timestamp": timestamp,
-        "total_battles": total_battles,
-        "active_models": active_models,
-        "most_battles": {
-            "model": get_human_readable_name(most_battles[1]),
-            "battles": most_battles[0]
-        },
-        "highest_win_rate": {
-            "model": get_human_readable_name(highest_win_rate[1]),
-            "win_rate": f"{highest_win_rate[0]:.2%}"
-        },
-        "most_diverse_opponent": {
-            "model": get_human_readable_name(most_diverse_opponent[1]),
-            "unique_opponents": most_diverse_opponent[0]
-        }
-    }
-    
-    return stats
-
-def save_internal_stats(stats: Dict[str, Any]) -> bool:
-    nc = Nextcloud(
-        nextcloud_url=arena_config.NEXTCLOUD_URL,
-        nc_auth_user=arena_config.NEXTCLOUD_USERNAME,
-        nc_auth_pass=arena_config.NEXTCLOUD_PASSWORD
-    )
-    
-    try:
-        json_data = json.dumps(stats, indent=2)
-        nc.files.upload(arena_config.NEXTCLOUD_INTERNAL_STATS_PATH, json_data.encode('utf-8'))
-        return True
-    except Exception as e:
-        print(f"Error saving internal stats to Nextcloud: {str(e)}")
-        return False
-
-def save_local_stats(stats: Dict[str, Any], filename: str = "internal_stats.json") -> bool:
-    try:
-        with open(filename, 'w') as f:
-            json.dump(stats, f, indent=2)
-        return True
-    except Exception as e:
-        print(f"Error saving internal stats to local file: {str(e)}")
-        return False
-
-def get_fun_stats() -> Dict[str, Any]:
-    leaderboard = load_leaderboard()
-    
-    total_battles = sum(
-        model_data['wins'] + model_data['losses']
-        for model_data in leaderboard.values()
-    )
-    
-    timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC")
-    
-    active_models = len(leaderboard)
-    
-    most_battles = max(
-        (model_data['wins'] + model_data['losses'], model)
-        for model, model_data in leaderboard.items()
-    )
-    
-    highest_win_rate = max(
-        (model_data['wins'] / (model_data['wins'] + model_data['losses']) if (model_data['wins'] + model_data['losses']) > 0 else 0, model)
-        for model, model_data in leaderboard.items()
-    )
-    
-    most_diverse_opponent = max(
-        (len(model_data['opponents']), model)
-        for model, model_data in leaderboard.items()
-    )
-    
-    # Existing fun stats
-    underdog_champion = min(
-        ((get_model_size(model), model_data['wins'] / (model_data['wins'] + model_data['losses'])) if (model_data['wins'] + model_data['losses']) > 0 else (get_model_size(model), 0), model)
-        for model, model_data in leaderboard.items()
-    )
-    
-    most_consistent = min(
-        (abs(model_data['wins'] - model_data['losses']), model)
-        for model, model_data in leaderboard.items()
-        if (model_data['wins'] + model_data['losses']) > 10  # Minimum battles threshold
-    )
-    
-    biggest_rivalry = max(
-        (results['wins'] + results['losses'], (model, opponent))
-        for model, data in leaderboard.items()
-        for opponent, results in data['opponents'].items()
-    )
-    
-    # New fun stats
-    david_vs_goliath = max(
-        ((get_model_size(opponent) - get_model_size(model), model_data['opponents'][opponent]['wins']), (model, opponent))
-        for model, model_data in leaderboard.items()
-        for opponent in model_data['opponents']
-        if get_model_size(opponent) > get_model_size(model) and model_data['opponents'][opponent]['wins'] > 0
-    )
-    
-    comeback_king = max(
-        (model_data['wins'] - model_data['losses'], model)
-        for model, model_data in leaderboard.items()
-        if model_data['losses'] > model_data['wins']
-    )
-    
-    pyrrhic_victor = min(
-        (model_data['wins'] / (model_data['wins'] + model_data['losses']) if (model_data['wins'] + model_data['losses']) > 0 else float('inf'), model)
-        for model, model_data in leaderboard.items()
-        if model_data['wins'] > model_data['losses'] and (model_data['wins'] + model_data['losses']) > 10
-    )
-    
-    stats = {
-        "timestamp": timestamp,
-        "total_battles": total_battles,
-        "active_models": active_models,
-        "most_battles": {
-            "model": get_human_readable_name(most_battles[1]),
-            "battles": most_battles[0]
-        },
-        "highest_win_rate": {
-            "model": get_human_readable_name(highest_win_rate[1]),
-            "win_rate": f"{highest_win_rate[0]:.2%}"
-        },
-        "most_diverse_opponent": {
-            "model": get_human_readable_name(most_diverse_opponent[1]),
-            "unique_opponents": most_diverse_opponent[0]
-        },
-        "underdog_champion": {
-            "model": get_human_readable_name(underdog_champion[1]),
-            "size": f"{underdog_champion[0][0]}B",
-            "win_rate": f"{underdog_champion[0][1]:.2%}"
-        },
-        "most_consistent": {
-            "model": get_human_readable_name(most_consistent[1]),
-            "win_loss_difference": most_consistent[0]
-        },
-        "biggest_rivalry": {
-            "model1": get_human_readable_name(biggest_rivalry[1][0]),
-            "model2": get_human_readable_name(biggest_rivalry[1][1]),
-            "total_battles": biggest_rivalry[0]
-        },
-        "david_vs_goliath": {
-            "david": get_human_readable_name(david_vs_goliath[1][0]),
-            "goliath": get_human_readable_name(david_vs_goliath[1][1]),
-            "size_difference": f"{david_vs_goliath[0][0]:.1f}B",
-            "wins": david_vs_goliath[0][1]
-        },
-        "comeback_king": {
-            "model": get_human_readable_name(comeback_king[1]),
-            "comeback_margin": comeback_king[0]
-        },
-        "pyrrhic_victor": {
-            "model": get_human_readable_name(pyrrhic_victor[1]),
-            "win_rate": f"{pyrrhic_victor[0]:.2%}"
-        }
-    }
-    
-    return stats
-
-if __name__ == "__main__":
-    stats = get_internal_stats()