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test_task_replay.py
Executable file
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test_task_replay.py
Executable file
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#!/usr/bin/env python3
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"""
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Test du système de rejeu de tâches.
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"""
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import asyncio
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import sys
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from pathlib import Path
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# Ajouter le chemin du projet
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sys.path.insert(0, str(Path(__file__).parent / "geniusia2"))
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from core.task_replay import TaskReplayEngine
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from core.learning_manager import LearningManager
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from core.embeddings_manager import EmbeddingsManager
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from core.utils.vision_utils import VisionUtils
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from core.utils.input_utils import InputUtils
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from core.logger import Logger
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from core.config import get_config
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async def test_list_tasks():
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"""Test de listage des tâches disponibles."""
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print("=== Test: Liste des tâches disponibles ===\n")
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# Charger la configuration
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config = get_config()
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# Initialiser les composants
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logger = Logger()
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embeddings_manager = EmbeddingsManager(logger=logger)
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learning_manager = LearningManager(
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embeddings_manager,
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logger,
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config,
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profiles_path="geniusia2/data/user_profiles"
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)
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vision_utils = VisionUtils(config)
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input_utils = InputUtils(logger, config)
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# Créer le moteur de rejeu
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replay_engine = TaskReplayEngine(
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learning_manager,
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embeddings_manager,
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vision_utils,
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input_utils,
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logger,
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config
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)
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# Lister les tâches
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tasks = replay_engine.list_available_tasks()
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print(f"Tâches disponibles: {len(tasks)}\n")
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for task in tasks:
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print(f"📋 {task['task_name']}")
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print(f" ID: {task['task_id']}")
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print(f" Observations: {task['observation_count']}")
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print(f" Confiance: {task['confidence']:.2%}")
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print()
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return tasks
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async def test_replay_task(task_id: str):
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"""Test de rejeu d'une tâche."""
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print(f"\n=== Test: Rejeu de la tâche {task_id} ===\n")
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# Charger la configuration
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config = get_config()
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# Initialiser les composants
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logger = Logger()
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embeddings_manager = EmbeddingsManager(logger=logger)
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learning_manager = LearningManager(
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embeddings_manager,
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logger,
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config,
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profiles_path="geniusia2/data/user_profiles"
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)
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vision_utils = VisionUtils(config)
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input_utils = InputUtils(logger, config)
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# Créer le moteur de rejeu
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replay_engine = TaskReplayEngine(
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learning_manager,
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embeddings_manager,
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vision_utils,
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input_utils,
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logger,
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config
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)
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print("⏳ Démarrage du rejeu dans 3 secondes...")
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print(" (Préparez l'interface si nécessaire)")
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await asyncio.sleep(3)
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# Rejouer la tâche
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results = await replay_engine.replay_task(task_id, interactive=False)
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print("\n📊 Résultats du rejeu:")
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print(f" Succès: {'✅' if results['success'] else '❌'}")
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print(f" Actions exécutées: {results['executed_actions']}/{results['total_actions']}")
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print(f" Actions échouées: {results['failed_actions']}")
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print("\n📝 Détails des actions:")
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for action in results['actions']:
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status = "✅" if action['success'] else "❌"
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print(f" {status} Étape {action['step']}: {action.get('action_type', 'unknown')}")
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if 'location' in action:
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loc = action['location']
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print(f" Position: ({loc['x']}, {loc['y']}) - Confiance: {loc['confidence']:.2%}")
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if 'error' in action:
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print(f" Erreur: {action['error']}")
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return results
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async def test_replay_with_monitoring(task_id: str):
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"""Test de rejeu avec monitoring en temps réel."""
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print(f"\n=== Test: Rejeu avec monitoring - {task_id} ===\n")
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# Charger la configuration
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config = get_config()
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# Initialiser les composants
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logger = Logger()
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embeddings_manager = EmbeddingsManager(logger=logger)
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learning_manager = LearningManager(
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embeddings_manager,
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logger,
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config,
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profiles_path="geniusia2/data/user_profiles"
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)
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vision_utils = VisionUtils(config)
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input_utils = InputUtils(logger, config)
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# Créer le moteur de rejeu
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replay_engine = TaskReplayEngine(
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learning_manager,
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embeddings_manager,
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vision_utils,
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input_utils,
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logger,
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config
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)
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# Callback pour monitoring
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def on_step(step_result):
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status_icon = {
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"success": "✅",
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"failed": "❌",
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"not_found": "🔍",
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"pending": "⏳"
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}.get(step_result["status"], "❓")
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print(f"{status_icon} Étape {step_result['step']}: {step_result['description']} - {step_result['status']}")
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print("⏳ Démarrage du rejeu dans 3 secondes...")
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await asyncio.sleep(3)
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# Rejouer avec monitoring
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results = await replay_engine.replay_task_with_monitoring(
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task_id,
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on_step_completed=on_step
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)
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print(f"\n📊 Résultat final: {'✅ Succès' if results['success'] else '❌ Échec'}")
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return results
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async def main():
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"""Fonction principale."""
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print("🎮 Test du système de rejeu de tâches\n")
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# 1. Lister les tâches disponibles
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tasks = await test_list_tasks()
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if not tasks:
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print("❌ Aucune tâche disponible pour le rejeu.")
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print(" Utilisez d'abord le système de capture pour apprendre des tâches.")
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return
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# 2. Demander quelle tâche rejouer
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print("\n" + "="*60)
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print("Quelle tâche voulez-vous rejouer ?")
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for i, task in enumerate(tasks, 1):
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print(f"{i}. {task['task_name']} ({task['task_id']})")
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try:
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choice = input("\nNuméro de la tâche (ou 'q' pour quitter): ").strip()
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if choice.lower() == 'q':
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print("Au revoir!")
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return
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task_index = int(choice) - 1
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if task_index < 0 or task_index >= len(tasks):
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print("❌ Choix invalide")
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return
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selected_task = tasks[task_index]
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task_id = selected_task['task_id']
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# 3. Rejouer la tâche avec monitoring
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await test_replay_with_monitoring(task_id)
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except KeyboardInterrupt:
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print("\n\n⚠️ Interruption par l'utilisateur")
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except Exception as e:
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print(f"\n❌ Erreur: {e}")
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import traceback
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traceback.print_exc()
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if __name__ == "__main__":
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asyncio.run(main())
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