tests add for api
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Максим Туревич
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api/test-api.py
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197
api/test-api.py
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import requests
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import time
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import json
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from datasets import load_dataset
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from datetime import datetime
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# Конфигурация API
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API_URL = "http://localhost:8088/api/browser/tasks"
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HEADERS = {"Content-Type": "application/json"}
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# Загружаем датасет
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dataset = load_dataset("iMeanAI/Mind2Web-Live", split="train")
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# Для теста берем первые N задач (замените на полный датасет при необходимости)
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TEST_SIZE = 10 # или len(dataset) для полного бенчмарка
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dataset = dataset.select(range(TEST_SIZE))
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print(f"Загружено задач: {len(dataset)}")
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print(f"Поля: {dataset[0].keys()}\n")
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cnt = 3
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results = []
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for idx, item in enumerate(dataset):
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if cnt > 0:
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cnt -=1
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continue
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# Поля из датасета
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task_desc = item['task'] # Описание задачи
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ref_length = item['reference_task_length'] # Эталонная длина в шагах
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evaluation = item['evaluation'] # Критерии оценки
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# ID задачи (используем index + timestamp для уникальности)
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task_id_orig = f"mind2web_{idx}_{int(time.time())}"
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print(f"\n[{idx + 1}/{len(dataset)}] Task: {task_desc[:70]}...")
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print(f" Эталонная длина: {ref_length} шагов")
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start_time = time.time()
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# 1. Создаем задачу через API
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try:
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resp = requests.post(
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API_URL,
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json={
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"task": task_desc,
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"timeout": 300, # Увеличим таймаут для сложных задач
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"metadata": {
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"source": "mind2web",
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"reference_length": ref_length
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}
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},
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headers=HEADERS,
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timeout=10
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)
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if resp.status_code != 202:
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print(f" ❌ Ошибка создания задачи: {resp.status_code}")
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print(f" Ответ: {resp.text}")
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continue
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api_task_id = resp.json()["task_id"]
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created_at = time.time()
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queue_time = created_at - start_time
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print(f" 📝 Task ID: {api_task_id} | Очередь: {queue_time:.2f}с")
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# 2. Ожидание завершения с прогрессом
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status = "queued"
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poll_count = 0
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while status in ["queued", "running"]:
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time.sleep(2) # Интервал опроса
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poll_count += 1
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try:
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status_resp = requests.get(f"{API_URL}/{api_task_id}", timeout=5)
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if status_resp.status_code == 200:
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status_data = status_resp.json()
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status = status_data.get("status", "unknown")
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# Показываем прогресс каждые 5 опросов
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if poll_count % 5 == 0:
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elapsed = time.time() - start_time
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print(f" ⏳ Статус: {status} | Прошло: {elapsed:.1f}с")
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except Exception as e:
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print(f" ⚠️ Ошибка опроса: {e}")
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pass
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end_time = time.time()
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execution_time = end_time - start_time
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# 3. Получение результата
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result_resp = requests.get(f"{API_URL}/{api_task_id}/result", timeout=10)
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result_data = None
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if result_resp.status_code == 200:
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try:
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result_data = result_resp.json()
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except:
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result_data = result_resp.text
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# 4. Запись метрик
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result = {
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"index": idx,
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"original_task_id": task_id_orig,
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"api_task_id": api_task_id,
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"task_description": task_desc,
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"reference_length": ref_length,
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"status": status,
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"queue_time_sec": round(queue_time, 2),
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"execution_time_sec": round(execution_time, 2),
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"total_time_sec": round(end_time - start_time, 2),
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"result": result_data,
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"timestamp": datetime.now().isoformat()
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}
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results.append(result)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"mind2web_benchmark.json"
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with open(filename, "w", encoding="utf-8") as f:
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json.dump(results, f, indent=2, ensure_ascii=False)
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# Эмодзи статуса
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status_emoji = "✅" if status == "succeeded" else "❌"
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print(f" {status_emoji} Статус: {status} | Время: {execution_time:.1f}с")
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except requests.exceptions.Timeout:
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print(f" ❌ Таймаут при создании задачи")
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except Exception as e:
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print(f" ❌ Ошибка: {type(e).__name__}: {e}")
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continue
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# Сохранение детальных результатов
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"mind2web_benchmark_{timestamp}.json"
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with open(filename, "w", encoding="utf-8") as f:
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json.dump(results, f, indent=2, ensure_ascii=False)
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print("\n" + "=" * 60)
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print("📊 ИТОГОВЫЕ МЕТРИКИ СКОРОСТИ")
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print("=" * 60)
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# Статистика по статусам
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completed = [r for r in results if r["status"] == "completed"]
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failed = [r for r in results if r["status"] == "failed"]
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unknown = [r for r in results if r["status"] not in ["completed", "failed"]]
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print(f"\n📈 СТАТУСЫ:")
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print(f" Всего задач: {len(results)}")
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print(f" ✅ Успешно: {len(completed)} ({len(completed) / max(len(results), 1) * 100:.1f}%)")
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print(f" ❌ Провалено: {len(failed)} ({len(failed) / max(len(results), 1) * 100:.1f}%)")
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if unknown:
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print(f" ❓ Неизвестный статус: {len(unknown)}")
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if completed:
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total_times = [r["total_time_sec"] for r in completed]
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queue_times = [r["queue_time_sec"] for r in completed]
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exec_times = [r["execution_time_sec"] for r in completed]
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print(f"\n⏱️ ВРЕМЯ ВЫПОЛНЕНИЯ:")
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print(f" Среднее: {sum(total_times) / len(total_times):.2f} сек")
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print(f" Медиана (p50): {sorted(total_times)[len(total_times) // 2]:.2f} сек")
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if len(total_times) >= 20:
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print(f" p95: {sorted(total_times)[int(len(total_times) * 0.95)]:.2f} сек")
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print(f" Мин: {min(total_times):.2f} сек")
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print(f" Макс: {max(total_times):.2f} сек")
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print(f"\n📊 ПРОИЗВОДИТЕЛЬНОСТЬ:")
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print(f" Среднее время в очереди: {sum(queue_times) / len(queue_times):.2f} сек")
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tasks_per_hour = 3600 / (sum(total_times) / len(total_times))
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print(f" Скорость выполнения: {tasks_per_hour:.1f} задач/час")
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# Эффективность относительно эталонной длины
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if all("reference_length" in r for r in completed):
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avg_ref_length = sum(r["reference_length"] for r in completed) / len(completed)
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time_per_step = (sum(total_times) / len(total_times)) / avg_ref_length
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print(f" Среднее время на шаг: {time_per_step:.2f} сек")
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print(f"\n💾 Результаты сохранены в: {filename}")
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# Создание краткого отчета для сравнения
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summary = {
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"benchmark": "Online-Mind2Web",
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"timestamp": timestamp,
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"api_endpoint": API_URL,
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"total_tasks": len(results),
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"completed": len(completed),
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"failed": len(failed),
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"success_rate": len(completed) / max(len(results), 1) * 100,
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"avg_time_sec": sum(total_times) / len(total_times) if completed else None,
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"median_time_sec": sorted(total_times)[len(total_times) // 2] if completed else None,
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"tasks_per_hour": 3600 / (sum(total_times) / len(total_times)) if completed else None
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}
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summary_file = f"mind2web_summary_{timestamp}.json"
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with open(summary_file, "w", encoding="utf-8") as f:
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json.dump(summary, f, indent=2, ensure_ascii=False)
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print(f"📋 Краткий отчет сохранен в: {summary_file}")
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