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archive/old_tests/test_workflow_suggestion.py
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273
archive/old_tests/test_workflow_suggestion.py
Executable file
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#!/usr/bin/env python3
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"""
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Test de la suggestion de workflows dans le Mode Assisté
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"""
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import sys
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import time
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import numpy as np
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from pathlib import Path
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from datetime import datetime, timedelta
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sys.path.insert(0, str(Path(__file__).parent / "geniusia2"))
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from core.logger import Logger
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from core.config import get_config
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from core.event_capture import EventCapture
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from core.suggestion_manager import SuggestionManager
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from core.learning_manager import LearningManager
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from core.embeddings_manager import EmbeddingsManager
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def create_mock_learning_manager(logger, config):
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"""Crée un mock du LearningManager pour les tests"""
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class MockLearningManager:
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def __init__(self):
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self.embeddings_manager = EmbeddingsManager(logger, config)
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def load_task(self, task_id):
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return None
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def confirm_action(self, data):
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pass
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return MockLearningManager()
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def simulate_workflow_actions(event_capture, base_time):
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"""
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Simule une séquence d'actions qui correspond à un workflow
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"""
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actions = [
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{
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"action_type": "click",
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"position": (100, 50),
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"window": "Desktop",
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"timestamp": (base_time + timedelta(seconds=0)).isoformat(),
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"description": "Clic sur lanceur"
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},
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{
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"action_type": "type",
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"text": "office",
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"window": "Desktop",
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"timestamp": (base_time + timedelta(seconds=2)).isoformat(),
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"description": "Tape 'office'"
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},
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{
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"action_type": "click",
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"position": (150, 100),
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"window": "Desktop",
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"timestamp": (base_time + timedelta(seconds=4)).isoformat(),
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"description": "Clic sur OnlyOffice"
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}
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]
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for action in actions:
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event_capture.capture_event(action)
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return actions
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def main():
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print("\n" + "="*60)
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print(" 🧪 TEST DE SUGGESTION DE WORKFLOWS")
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print("="*60 + "\n")
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# Initialiser les composants
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config = get_config()
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logger = Logger()
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# EventCapture avec workflows
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event_capture = EventCapture(
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logger=logger,
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pattern_threshold=3,
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max_history=1000,
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config=config
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)
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# Mock du LearningManager
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learning_manager = create_mock_learning_manager(logger, config)
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# SuggestionManager
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suggestion_manager = SuggestionManager(
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learning_manager=learning_manager,
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embeddings_manager=learning_manager.embeddings_manager,
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logger=logger,
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config=config
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)
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# Callback pour les suggestions
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suggestions_created = []
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def on_suggestion_created(suggestion):
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suggestions_created.append(suggestion)
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print(f"\n🎉 SUGGESTION CRÉÉE !")
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print(f" Type: {suggestion.get('type', 'unknown')}")
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if suggestion.get('type') == 'workflow':
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print(f" Workflow: {suggestion['workflow_name']}")
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print(f" Étape: {suggestion['current_step']}/{suggestion['total_steps']}")
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print(f" Prochaine action: {suggestion['next_action']['description']}")
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print(f" Confiance: {suggestion['confidence']:.2%}")
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print(f" Répétitions: {suggestion['repetitions']}x")
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else:
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print(f" Tâche: {suggestion.get('task_name', 'Unknown')}")
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print(f" Confiance: {suggestion['confidence']:.2%}")
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suggestion_manager.on_suggestion_created = on_suggestion_created
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print("📋 Phase 1: Créer des workflows répétés...\n")
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# Créer 3 sessions similaires pour établir un workflow
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base_times = [
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datetime.now() - timedelta(hours=3),
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datetime.now() - timedelta(hours=2),
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datetime.now() - timedelta(hours=1)
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]
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for i, base_time in enumerate(base_times, 1):
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print(f"Session {i} - {base_time.strftime('%H:%M')}")
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# Créer les actions
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actions = [
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{
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"action_type": "click",
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"position": (100, 50),
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"window": "Desktop",
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"timestamp": (base_time + timedelta(seconds=0)).isoformat(),
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"description": "Clic sur lanceur"
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},
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{
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"action_type": "type",
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"text": "office",
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"window": "Desktop",
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"timestamp": (base_time + timedelta(seconds=2)).isoformat(),
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"description": "Tape 'office'"
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},
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{
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"action_type": "click",
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"position": (150, 100),
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"window": "Desktop",
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"timestamp": (base_time + timedelta(seconds=4)).isoformat(),
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"description": "Clic sur OnlyOffice"
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},
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{
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"action_type": "click",
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"position": (200, 150),
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"window": "OnlyOffice",
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"timestamp": (base_time + timedelta(seconds=8)).isoformat(),
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"description": "Nouveau document"
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},
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{
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"action_type": "type",
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"text": "Bonjour",
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"window": "OnlyOffice",
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"timestamp": (base_time + timedelta(seconds=10)).isoformat(),
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"description": "Tape du texte"
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}
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]
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# Ajouter les actions
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for action in actions:
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event_capture.session_manager.add_action(action)
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# Finaliser la session
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event_capture.session_manager.force_finalize_session()
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print(f" ✅ {len(actions)} actions ajoutées")
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# Analyser pour détecter des workflows
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print(f"\n🔍 Analyse des sessions pour détecter des workflows...")
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recent_sessions = event_capture.session_manager.get_recent_sessions(10)
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event_capture.workflow_detector.analyze_sessions(recent_sessions)
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# Vérifier les workflows détectés
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workflows = event_capture.get_workflows()
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print(f"\n📊 Workflows détectés: {len(workflows)}")
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if workflows:
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for workflow in workflows:
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print(f" - {workflow.name} ({workflow.repetitions}x, {workflow.confidence:.2%})")
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print(f" Étapes: {len(workflow.steps)}")
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else:
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print(" ❌ Aucun workflow détecté")
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print("\n⚠️ Le test ne peut pas continuer sans workflows")
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return
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print(f"\n📋 Phase 2: Simuler le début d'un workflow...\n")
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# Créer une nouvelle session qui commence comme le workflow
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print("Début d'une nouvelle session...")
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current_time = datetime.now()
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# Première action du workflow
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action1 = {
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"action_type": "click",
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"position": (100, 50),
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"window": "Desktop",
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"timestamp": current_time.isoformat(),
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"description": "Clic sur lanceur"
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}
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event_capture.session_manager.add_action(action1)
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print(f" ✅ Action 1: {action1['description']}")
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time.sleep(0.5)
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# Deuxième action du workflow
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action2 = {
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"action_type": "type",
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"text": "office",
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"window": "Desktop",
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"timestamp": (current_time + timedelta(seconds=2)).isoformat(),
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"description": "Tape 'office'"
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}
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event_capture.session_manager.add_action(action2)
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print(f" ✅ Action 2: {action2['description']}")
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print(f"\n🔍 Vérification de suggestion de workflow...\n")
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# Créer un contexte pour la suggestion
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context = {
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"event_capture": event_capture,
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"embedding": np.random.rand(512), # Mock embedding
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"window": "Desktop",
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"timestamp": datetime.now()
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}
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# Chercher une suggestion
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suggestion = suggestion_manager.find_suggestion(context)
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if suggestion:
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print(f"✅ Suggestion trouvée !")
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print(f" Type: {suggestion.get('type')}")
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if suggestion.get('type') == 'workflow':
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print(f" Workflow: {suggestion['workflow_name']}")
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print(f" Étape actuelle: {suggestion['current_step']}/{suggestion['total_steps']}")
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print(f" Prochaine action: {suggestion['next_action']['description']}")
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print(f" Actions restantes: {suggestion['remaining_steps']}")
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print(f" Confiance: {suggestion['confidence']:.2%}")
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# Créer la suggestion dans le manager
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suggestion_manager.create_suggestion(context)
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print(f"\n📈 Statistiques:")
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stats = suggestion_manager.get_stats()
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print(f" Suggestion active: {stats['has_active_suggestion']}")
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else:
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print(f"❌ Aucune suggestion trouvée")
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print(f"\n🔍 Debug:")
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print(f" Workflows: {len(workflows)}")
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print(f" Session courante: {event_capture.session_manager.current_session}")
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if event_capture.session_manager.current_session:
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print(f" Actions dans session: {event_capture.session_manager.current_session.action_count}")
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print(f"\n" + "="*60)
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print(f" ✅ TEST TERMINÉ")
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print(f" Suggestions créées: {len(suggestions_created)}")
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print(f"="*60)
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if __name__ == "__main__":
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main()
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