#!/usr/bin/env python3 """ Runner CLI pour ÈwéBench. Usage: python run_benchmark.py --endpoint URL --model MODEL_NAME [--api-key KEY] [--verbose] python run_benchmark.py --preset deepseek [--verbose] python run_benchmark.py --preset local --endpoint http://localhost:8080/v1/chat/completions python run_benchmark.py --compare result1.json result2.json Presets disponibles: deepseek — DeepSeek API (nécessite DEEPSEEK_API_KEY dans .env) gemini — Google Gemini (nécessite GEMINI_API_KEY dans .env) local — Modèle local (ollama, vllm, etc.) custom — API custom (nécessite --endpoint) """ import sys import os import json import argparse from pathlib import Path from dotenv import load_dotenv load_dotenv(Path(__file__).parent / ".env") from ewe_bench import EweBench, RESULTS_DIR PRESETS = { "deepseek": { "endpoint": "https://api.deepseek.com/chat/completions", "model": "deepseek-chat", "api_key_env": "DEEPSEEK_API_KEY" }, "deepseek-v4": { "endpoint": "https://api.deepseek.com/chat/completions", "model": "deepseek-ai/DeepSeek-V4-0324", "api_key_env": "DEEPSEEK_API_KEY" }, "gemini": { "endpoint": "https://generativelanguage.googleapis.com/v1beta/chat/completions", "model": "gemini-2.0-flash", "api_key_env": "GEMINI_API_KEY" }, "local": { "endpoint": "http://localhost:11434/v1/chat/completions", "model": "local-model", "api_key_env": None } } def print_comparison(report_a: dict, report_b: dict): """Affiche une comparaison visuelle entre deux rapports.""" print(f"\n{'='*70}") print(f" ÈwéBench — Comparaison de Modèles") print(f"{'='*70}") print(f"\n {'Catégorie':<30} {'Model A':<12} {'Model B':<12} {'Delta':<10}") print(f" {'':-<30} {'':-<12} {'':-<12} {'':-<10}") model_a = report_a.get("model", "Model A") model_b = report_b.get("model", "Model B") print(f" {'':30} {model_a:<12} {model_b:<12}") print() cats_a = report_a.get("categories", {}) cats_b = report_b.get("categories", {}) all_cats = set(list(cats_a.keys()) + list(cats_b.keys())) for cat in sorted(all_cats): score_a = cats_a.get(cat, {}).get("score", 0) score_b = cats_b.get(cat, {}).get("score", 0) delta = score_a - score_b indicator = "↑" if delta > 0 else "↓" if delta < 0 else "=" cat_display = cat.replace("_", " ").title()[:28] print(f" {cat_display:<30} {score_a:<12.1f} {score_b:<12.1f} {indicator} {abs(delta):.1f}") print(f"\n {'─'*70}") score_a = report_a.get("ewe_score", 0) score_b = report_b.get("ewe_score", 0) delta = score_a - score_b indicator = "↑" if delta > 0 else "↓" if delta < 0 else "=" print(f" {'ÈwéScore GLOBAL':<30} {score_a:<12.1f} {score_b:<12.1f} {indicator} {abs(delta):.1f}") print(f"\n Gagnant: {model_a if score_a > score_b else model_b} (+{abs(delta):.1f})") print(f"{'='*70}\n") def print_leaderboard(): """Affiche le leaderboard de tous les résultats existants.""" if not RESULTS_DIR.exists(): print("Aucun résultat trouvé.") return results = [] for f in RESULTS_DIR.glob("ewebench_*.json"): with open(f, "r", encoding="utf-8") as fh: data = json.load(fh) results.append({ "model": data.get("model", "?"), "score": data.get("ewe_score", 0), "tests": data.get("summary", {}).get("total_tests", 0), "passed": data.get("summary", {}).get("total_passed", 0), "date": data.get("timestamp", "?")[:10], "file": f.name }) if not results: print("Aucun résultat trouvé.") return results.sort(key=lambda x: x["score"], reverse=True) print(f"\n{'='*70}") print(f" ÈwéBench — Leaderboard") print(f"{'='*70}") print(f"\n {'#':<4} {'Modèle':<25} {'ÈwéScore':<10} {'Tests':<12} {'Date':<12}") print(f" {'':-<4} {'':-<25} {'':-<10} {'':-<12} {'':-<12}") for i, r in enumerate(results, 1): medal = "🥇" if i == 1 else "🥈" if i == 2 else "🥉" if i == 3 else f" {i}" pass_rate = f"{r['passed']}/{r['tests']}" print(f" {medal:<4} {r['model']:<25} {r['score']:<10.1f} {pass_rate:<12} {r['date']:<12}") print(f"\n{'='*70}\n") def main(): parser = argparse.ArgumentParser( description="ÈwéBench Runner — Évalue un LLM sur le benchmark Ewe", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=__doc__ ) parser.add_argument("--preset", choices=list(PRESETS.keys()), help="Utiliser un preset de configuration") parser.add_argument("--endpoint", help="URL de l'API du modèle") parser.add_argument("--model", help="Nom du modèle") parser.add_argument("--api-key", help="Clé API") parser.add_argument("--verbose", "-v", action="store_true", help="Mode détaillé") parser.add_argument("--category", "-c", help="Évaluer une seule catégorie") parser.add_argument("--compare", nargs=2, metavar="FILE", help="Comparer deux fichiers de résultats") parser.add_argument("--leaderboard", "-l", action="store_true", help="Afficher le leaderboard") args = parser.parse_args() if args.leaderboard: print_leaderboard() return if args.compare: with open(args.compare[0], "r") as f: report_a = json.load(f) with open(args.compare[1], "r") as f: report_b = json.load(f) print_comparison(report_a, report_b) return endpoint = args.endpoint model = args.model api_key = args.api_key if args.preset: preset = PRESETS[args.preset] endpoint = endpoint or preset["endpoint"] model = model or preset["model"] if not api_key and preset["api_key_env"]: api_key = os.getenv(preset["api_key_env"]) if not api_key: print(f"Erreur: {preset['api_key_env']} non trouvé dans .env") sys.exit(1) if not endpoint or not model: print("Erreur: --endpoint et --model requis (ou utilisez --preset)") parser.print_help() sys.exit(1) print(f"\n Initialisation ÈwéBench...") print(f" Endpoint: {endpoint}") print(f" Modèle: {model}") print(f" Catégorie: {args.category or 'TOUTES'}\n") bench = EweBench(endpoint, model, api_key) if args.category: result = bench.run_category(args.category, verbose=args.verbose) print(json.dumps(result, ensure_ascii=False, indent=2)) else: report = bench.run_full_benchmark(verbose=args.verbose) bench.results = report print(f"\n ÈwéScore: {report['ewe_score']}/100") if __name__ == "__main__": main()