feat(agent_chat): Intégration exécution réelle avec ActionExecutor
- Import des composants d'exécution (ActionExecutor, ExecutionLoop, etc.) - Initialisation complète du pipeline d'exécution au démarrage - Remplacement de la simulation par exécution réelle : - Capture d'écran avec ScreenCapturer - Exécution des actions avec ActionExecutor - Gestion des erreurs et fallback en mode simulé - Mode dégradé automatique si composants non disponibles Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Dom
@@ -48,6 +48,17 @@ try:
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except ImportError:
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GPU_AVAILABLE = False
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# Execution components (optional - pour exécution réelle)
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try:
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from core.execution import ActionExecutor, TargetResolver, ErrorHandler
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from core.execution.execution_loop import ExecutionLoop, ExecutionMode as ExecMode, ExecutionState
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from core.pipeline.workflow_pipeline import WorkflowPipeline
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from core.capture import ScreenCapturer
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EXECUTION_AVAILABLE = True
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except ImportError as e:
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logger.warning(f"Composants d'exécution non disponibles: {e}")
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EXECUTION_AVAILABLE = False
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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@@ -63,6 +74,12 @@ confirmation_loop: Optional[ConfirmationLoop] = None
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response_generator: Optional[ResponseGenerator] = None
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conversation_manager: Optional[ConversationManager] = None
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# Execution components
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workflow_pipeline = None
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action_executor = None
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execution_loop = None
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screen_capturer = None
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execution_status = {
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"running": False,
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"workflow": None,
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@@ -110,6 +127,47 @@ def init_system():
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response_generator = ResponseGenerator()
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conversation_manager = ConversationManager()
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# 4. Composants d'exécution réelle
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global workflow_pipeline, action_executor, execution_loop, screen_capturer
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if EXECUTION_AVAILABLE:
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try:
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# Pipeline de workflow (matching + actions)
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workflow_pipeline = WorkflowPipeline()
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logger.info("✓ WorkflowPipeline initialisé")
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# Capture d'écran
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screen_capturer = ScreenCapturer()
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logger.info("✓ ScreenCapturer initialisé")
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# Résolveur de cibles et gestionnaire d'erreurs
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target_resolver = TargetResolver()
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error_handler = ErrorHandler()
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# Exécuteur d'actions
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action_executor = ActionExecutor(
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target_resolver=target_resolver,
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error_handler=error_handler,
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verify_postconditions=True
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)
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logger.info("✓ ActionExecutor initialisé")
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# Boucle d'exécution (pour mode automatique)
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execution_loop = ExecutionLoop(
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pipeline=workflow_pipeline,
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action_executor=action_executor,
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screen_capturer=screen_capturer
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)
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logger.info("✓ ExecutionLoop initialisé")
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except Exception as e:
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logger.warning(f"⚠ Composants d'exécution partiels: {e}")
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# Mode dégradé: simulation uniquement
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workflow_pipeline = None
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action_executor = None
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execution_loop = None
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else:
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logger.info("ℹ Mode simulation (composants d'exécution non disponibles)")
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# =============================================================================
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# Routes Web
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@@ -580,34 +638,34 @@ def handle_cancel():
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# =============================================================================
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def execute_workflow(match, params):
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"""Exécuter un workflow avec le vrai système."""
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"""Exécuter un workflow avec le vrai système d'exécution."""
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global execution_status
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import time
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try:
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# Charger le workflow
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with open(match.workflow_path, 'r') as f:
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workflow_data = json.load(f)
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# Créer le VariableManager et injecter les paramètres
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var_manager = VariableManager()
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var_manager.set_variables(params)
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# Substituer les variables
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workflow_data = var_manager.substitute_dict(workflow_data)
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# Obtenir les étapes (edges)
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edges = workflow_data.get("edges", [])
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total_steps = len(edges) if edges else 5
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total_steps = len(edges) if edges else 1
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# Étape 1: Initialisation
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update_progress(10, "Initialisation", 1, total_steps + 2)
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time.sleep(0.5)
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time.sleep(0.3)
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# Étape 2: Préparation GPU (si disponible)
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if gpu_manager and GPU_AVAILABLE:
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update_progress(20, "Préparation GPU...", 2, total_steps + 2)
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update_progress(15, "Préparation GPU...", 2, total_steps + 2)
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try:
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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@@ -615,36 +673,187 @@ def execute_workflow(match, params):
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loop.close()
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except Exception as e:
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logger.warning(f"GPU mode change failed: {e}")
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# Exécuter chaque étape du workflow
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for i, edge in enumerate(edges):
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if not execution_status["running"]:
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break
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action = edge.get("action", {})
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action_type = action.get("type", "unknown")
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progress = int(20 + (i + 1) / total_steps * 70)
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step_name = f"Étape {i+1}: {action_type}"
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update_progress(progress, step_name, i + 3, total_steps + 2)
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# Simuler l'exécution de l'action
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# TODO: Connecter au vrai ActionExecutor
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time.sleep(0.8)
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# Vérifier si l'exécution réelle est disponible
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use_real_execution = (
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EXECUTION_AVAILABLE and
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action_executor is not None and
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screen_capturer is not None
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)
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if use_real_execution:
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logger.info(f"🚀 Exécution RÉELLE du workflow: {match.workflow_name}")
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_execute_workflow_real(workflow_data, edges, total_steps, params)
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else:
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logger.info(f"🎭 Exécution SIMULÉE du workflow: {match.workflow_name}")
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_execute_workflow_simulated(edges, total_steps)
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# Finalisation
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update_progress(95, "Finalisation...", total_steps + 1, total_steps + 2)
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time.sleep(0.3)
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# Terminé avec succès
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finish_execution(match.workflow_name, True, "Workflow terminé avec succès")
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if execution_status["running"]:
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update_progress(95, "Finalisation...", total_steps + 1, total_steps + 2)
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time.sleep(0.2)
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finish_execution(match.workflow_name, True, "Workflow terminé avec succès")
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except Exception as e:
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logger.error(f"Execution error: {e}")
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import traceback
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traceback.print_exc()
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finish_execution(match.workflow_name, False, f"Erreur: {str(e)}")
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def _execute_workflow_real(workflow_data, edges, total_steps, params):
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"""Exécution réelle avec ActionExecutor."""
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import time
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from dataclasses import dataclass
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# Capturer l'écran initial
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update_progress(20, "Capture écran initial...", 2, total_steps + 2)
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try:
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screenshot_path = screen_capturer.capture()
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logger.info(f"📸 Screenshot capturé: {screenshot_path}")
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except Exception as e:
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logger.warning(f"Capture écran échouée: {e}, utilisation mode dégradé")
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_execute_workflow_simulated(edges, total_steps)
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return
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# Créer le ScreenState pour l'exécution
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try:
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from core.models import ScreenState
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screen_state = ScreenState.from_screenshot(screenshot_path)
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except Exception as e:
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logger.warning(f"Création ScreenState échouée: {e}")
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# Créer un ScreenState minimal
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screen_state = type('ScreenState', (), {
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'screenshot_path': screenshot_path,
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'detected_elements': [],
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'timestamp': datetime.now()
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})()
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# Exécuter chaque edge avec ActionExecutor
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success_count = 0
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fail_count = 0
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for i, edge in enumerate(edges):
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if not execution_status["running"]:
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logger.info("⏹️ Exécution annulée par l'utilisateur")
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break
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action = edge.get("action", {})
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action_type = action.get("type", "unknown")
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progress = int(20 + (i + 1) / total_steps * 70)
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step_name = f"Étape {i+1}/{total_steps}: {action_type}"
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update_progress(progress, step_name, i + 3, total_steps + 2)
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logger.info(f"▶️ Exécution: {step_name}")
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try:
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# Créer un objet Edge compatible avec ActionExecutor
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workflow_edge = _create_workflow_edge(edge, params)
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# Exécuter l'action réelle
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result = action_executor.execute_edge(workflow_edge, screen_state)
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if result.status.value == "success":
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success_count += 1
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logger.info(f"✅ {step_name} - Succès")
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# Recapturer l'écran après chaque action réussie
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try:
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time.sleep(0.3) # Petit délai pour laisser l'UI se mettre à jour
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screenshot_path = screen_capturer.capture()
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screen_state = ScreenState.from_screenshot(screenshot_path)
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except:
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pass # Continuer même si la recapture échoue
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else:
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fail_count += 1
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logger.warning(f"⚠️ {step_name} - {result.status.value}: {result.message}")
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# Continuer malgré l'échec (mode best-effort)
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if fail_count >= 3:
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logger.error("❌ Trop d'échecs, arrêt de l'exécution")
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break
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except Exception as e:
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fail_count += 1
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logger.error(f"❌ Erreur lors de {step_name}: {e}")
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if fail_count >= 3:
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logger.error("❌ Trop d'erreurs, arrêt de l'exécution")
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break
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logger.info(f"📊 Résultat: {success_count} succès, {fail_count} échecs sur {total_steps} étapes")
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def _execute_workflow_simulated(edges, total_steps):
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"""Exécution simulée (fallback)."""
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import time
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for i, edge in enumerate(edges):
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if not execution_status["running"]:
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break
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action = edge.get("action", {})
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action_type = action.get("type", "unknown")
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progress = int(20 + (i + 1) / total_steps * 70)
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step_name = f"Étape {i+1}: {action_type} (simulé)"
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update_progress(progress, step_name, i + 3, total_steps + 2)
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# Simulation avec délai
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time.sleep(0.5)
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logger.info(f"🎭 Simulé: {step_name}")
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def _create_workflow_edge(edge_dict, params):
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"""Créer un objet WorkflowEdge depuis un dictionnaire."""
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from dataclasses import dataclass, field
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from typing import Optional, Dict, Any, List
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@dataclass
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class Action:
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type: str
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target: Optional[Dict] = None
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value: Optional[str] = None
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parameters: Dict[str, Any] = field(default_factory=dict)
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@dataclass
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class WorkflowEdge:
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id: str
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source: str
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target: str
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action: Action
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pre_conditions: List[Dict] = field(default_factory=list)
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post_conditions: List[Dict] = field(default_factory=list)
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action_dict = edge_dict.get("action", {})
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# Substituer les paramètres dans l'action
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action_value = action_dict.get("value", "")
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if action_value and isinstance(action_value, str):
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for key, val in params.items():
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action_value = action_value.replace(f"${{{key}}}", str(val))
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action_value = action_value.replace(f"${key}", str(val))
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action = Action(
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type=action_dict.get("type", "unknown"),
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target=action_dict.get("target"),
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value=action_value,
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parameters=action_dict.get("parameters", {})
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)
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return WorkflowEdge(
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id=edge_dict.get("id", f"edge_{id(edge_dict)}"),
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source=edge_dict.get("source", ""),
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target=edge_dict.get("target", ""),
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action=action,
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pre_conditions=edge_dict.get("pre_conditions", []),
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post_conditions=edge_dict.get("post_conditions", [])
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)
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def update_progress(progress: int, message: str, current: int, total: int):
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"""Mettre à jour la progression."""
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global execution_status
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