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277
generer_taches_demo.py
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277
generer_taches_demo.py
Executable file
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#!/usr/bin/env python3
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"""
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Script pour générer des tâches de démonstration dans RPA Vision V2.
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Crée des tâches fictives avec embeddings pour tester le système de suggestions.
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"""
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import sys
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import os
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import numpy as np
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from datetime import datetime
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from pathlib import Path
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# Ajouter le chemin vers geniusia2
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'geniusia2'))
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from core.logger import Logger
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from core.embeddings_manager import EmbeddingsManager
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from core.learning_manager import LearningManager
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from core.config import get_config, ensure_directories
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from PIL import Image
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import cv2
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def creer_image_demo(texte: str, couleur=(100, 150, 200)) -> np.ndarray:
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"""
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Crée une image de démonstration avec du texte.
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Args:
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texte: Texte à afficher
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couleur: Couleur de fond (BGR)
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Returns:
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Image numpy array
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"""
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# Créer une image 400x300
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img = np.zeros((300, 400, 3), dtype=np.uint8)
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img[:] = couleur
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# Ajouter du texte
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font = cv2.FONT_HERSHEY_SIMPLEX
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cv2.putText(img, texte, (50, 150), font, 1, (255, 255, 255), 2, cv2.LINE_AA)
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return img
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def generer_taches_demo():
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"""Génère des tâches de démonstration."""
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print("🎨 Génération de tâches de démonstration...")
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print("=" * 60)
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# Initialiser les composants
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print("\n1. Initialisation des composants...")
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ensure_directories()
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config = get_config()
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logger = Logger()
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embeddings_manager = EmbeddingsManager(logger=logger)
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learning_manager = LearningManager(embeddings_manager, logger, config)
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print(" ✓ Composants initialisés")
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# Définir les tâches de démonstration
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taches_demo = [
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{
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"nom": "Ouvrir Calculatrice",
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"description": "Ouvre l'application calculatrice",
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"actions": [
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{"type": "key_press", "key": "super", "texte": "Menu"},
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{"type": "key_press", "key": "c", "texte": "Calc"},
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{"type": "key_press", "key": "enter", "texte": "Enter"}
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],
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"couleur": (100, 150, 200)
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},
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{
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"nom": "Calcul Simple",
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"description": "Effectue un calcul simple (2+2)",
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"actions": [
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{"type": "mouse_click", "x": 150, "y": 200, "texte": "Bouton 2"},
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{"type": "mouse_click", "x": 200, "y": 250, "texte": "Bouton +"},
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{"type": "mouse_click", "x": 150, "y": 200, "texte": "Bouton 2"},
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{"type": "mouse_click", "x": 250, "y": 250, "texte": "Bouton ="}
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],
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"couleur": (150, 100, 200)
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},
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{
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"nom": "Ouvrir Navigateur",
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"description": "Ouvre le navigateur web",
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"actions": [
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{"type": "key_press", "key": "super", "texte": "Menu"},
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{"type": "key_press", "key": "f", "texte": "Firefox"},
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{"type": "key_press", "key": "enter", "texte": "Enter"}
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],
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"couleur": (200, 150, 100)
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},
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{
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"nom": "Recherche Google",
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"description": "Effectue une recherche sur Google",
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"actions": [
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{"type": "mouse_click", "x": 400, "y": 100, "texte": "Barre recherche"},
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{"type": "key_press", "key": "r", "texte": "RPA"},
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{"type": "key_press", "key": "p", "texte": ""},
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{"type": "key_press", "key": "a", "texte": ""},
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{"type": "key_press", "key": "enter", "texte": "Rechercher"}
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],
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"couleur": (100, 200, 150)
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},
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{
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"nom": "Fermer Fenêtre",
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"description": "Ferme la fenêtre active",
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"actions": [
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{"type": "key_press", "key": "alt+f4", "texte": "Alt+F4"}
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],
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"couleur": (200, 100, 100)
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}
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]
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print(f"\n2. Création de {len(taches_demo)} tâches de démonstration...")
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taches_creees = []
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for i, tache_def in enumerate(taches_demo, 1):
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print(f"\n 📝 Tâche {i}/{len(taches_demo)}: {tache_def['nom']}")
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# Créer les signatures pour chaque action
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signatures = []
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for j, action in enumerate(tache_def['actions']):
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# Créer une image de démonstration
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img = creer_image_demo(action['texte'], tache_def['couleur'])
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# Générer l'embedding
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embedding = embeddings_manager.encode_image(img)
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# Créer la signature
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signature = {
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"action_type": action['type'],
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"x": action.get('x', 0),
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"y": action.get('y', 0),
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"key": action.get('key', ''),
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"embedding": embedding,
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"screenshot": img,
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"window": "Demo Window",
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"timestamp": datetime.now().isoformat()
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}
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signatures.append(signature)
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print(f" ✓ Action {j+1}: {action['type']} - {action['texte']}")
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# Créer la tâche
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try:
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task = learning_manager.create_task_from_signatures(
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signatures,
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description=tache_def['nom']
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)
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# Marquer comme observée plusieurs fois pour permettre le rejeu
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for _ in range(25): # Plus que le seuil de 20
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task.observation_count += 1
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# Sauvegarder (méthode privée mais accessible)
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learning_manager._save_task(task)
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taches_creees.append(task)
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print(f" ✅ Tâche créée: {task.task_id}")
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print(f" Observations: {task.observation_count}")
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except Exception as e:
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print(f" ❌ Erreur: {e}")
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import traceback
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traceback.print_exc()
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# Sauvegarder l'index FAISS
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print(f"\n3. Sauvegarde de l'index FAISS...")
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try:
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embeddings_manager.save_index()
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print(" ✓ Index FAISS sauvegardé")
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except Exception as e:
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print(f" ⚠️ Erreur lors de la sauvegarde: {e}")
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# Résumé
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print("\n" + "=" * 60)
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print("✅ GÉNÉRATION TERMINÉE")
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print("=" * 60)
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print(f"\n📊 Résumé:")
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print(f" - Tâches créées: {len(taches_creees)}")
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print(f" - Embeddings générés: {sum(len(t.signatures) for t in taches_creees)}")
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print(f" - Index FAISS: {embeddings_manager.faiss_index.ntotal} embeddings")
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print(f"\n💡 Prochaines étapes:")
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print(f" 1. Lancez l'application: cd geniusia2 && ./run.sh")
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print(f" 2. L'application devrait maintenant avoir des tâches à suggérer")
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print(f" 3. Effectuez des actions similaires pour voir les suggestions")
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print(f"\n📁 Fichiers créés:")
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print(f" - geniusia2/data/embeddings/faiss_index.bin")
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print(f" - geniusia2/data/embeddings/metadata.pkl")
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print(f" - geniusia2/data/tasks/*.json")
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return taches_creees
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def verifier_taches():
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"""Vérifie les tâches créées."""
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print("\n🔍 Vérification des tâches créées...")
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print("=" * 60)
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try:
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config = get_config()
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logger = Logger()
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embeddings_manager = EmbeddingsManager(logger=logger)
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learning_manager = LearningManager(embeddings_manager, logger, config)
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# Lister les tâches
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tasks = learning_manager.get_all_tasks()
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print(f"\n📋 Tâches disponibles: {len(tasks)}")
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for i, task in enumerate(tasks, 1):
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print(f"\n {i}. {task.task_name}")
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print(f" ID: {task.task_id}")
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print(f" Actions: {len(task.signatures)}")
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print(f" Observations: {task.observation_count}")
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print(f" Prêt pour rejeu: {'✅ Oui' if task.observation_count >= 20 else '❌ Non'}")
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# Vérifier l'index FAISS
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print(f"\n📊 Index FAISS:")
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print(f" - Embeddings: {embeddings_manager.faiss_index.ntotal}")
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print(f" - Métadonnées: {len(embeddings_manager.metadata_store)}")
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return True
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except Exception as e:
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print(f"\n❌ Erreur lors de la vérification: {e}")
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import traceback
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traceback.print_exc()
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return False
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def main():
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"""Point d'entrée principal."""
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import argparse
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parser = argparse.ArgumentParser(description='Génère des tâches de démonstration')
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parser.add_argument(
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'--verifier',
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action='store_true',
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help='Vérifie les tâches existantes au lieu de les créer'
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)
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args = parser.parse_args()
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try:
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if args.verifier:
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verifier_taches()
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else:
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taches = generer_taches_demo()
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# Vérification automatique
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if taches:
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print("\n")
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verifier_taches()
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print("\n✅ Script terminé avec succès!")
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except KeyboardInterrupt:
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print("\n\n⚠️ Interruption par l'utilisateur")
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sys.exit(1)
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except Exception as e:
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print(f"\n❌ Erreur fatale: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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if __name__ == "__main__":
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main()
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