#!/usr/bin/env python3
"""
Exemple d'utilisation du RPA Vision V3

Ce script montre comment :
1. Charger un workflow existant
2. Démarrer l'exécution en mode supervisé
3. Observer la progression
4. Arrêter proprement

Usage:
    python examples/run_rpa.py --workflow <workflow_id> --mode supervised
"""

import argparse
import logging
import time
import sys
from pathlib import Path

# Ajouter le répertoire racine au path
sys.path.insert(0, str(Path(__file__).parent.parent))

from core.pipeline import WorkflowPipeline, create_pipeline
from core.execution import ExecutionLoop, ExecutionMode, ExecutionState, create_execution_loop

logging.basicConfig(
    level=logging.INFO,
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)


def on_step_complete(result):
    """Callback appelé après chaque étape."""
    status = "✓" if result.success else "✗"
    logger.info(
        f"{status} Step: node={result.node_id}, "
        f"confidence={result.match_confidence:.2f}, "
        f"duration={result.duration_ms:.0f}ms"
    )


def on_state_change(new_state):
    """Callback appelé lors des changements d'état."""
    logger.info(f"State changed to: {new_state.value}")


def on_error(error_type, exception):
    """Callback appelé en cas d'erreur."""
    logger.error(f"Error [{error_type}]: {exception}")


def confirmation_callback(message, action_info):
    """Callback pour demander confirmation (mode supervisé)."""
    print(f"\n{'='*60}")
    print(f"ACTION REQUIRED: {message}")
    print(f"Details: {action_info}")
    print(f"{'='*60}")
    
    response = input("Execute? [y/N]: ").strip().lower()
    return response == 'y'


def main():
    parser = argparse.ArgumentParser(description="RPA Vision V3 Runner")
    parser.add_argument("--workflow", "-w", required=True, help="Workflow ID to execute")
    parser.add_argument(
        "--mode", "-m",
        choices=["observation", "coaching", "supervised", "automatic"],
        default="supervised",
        help="Execution mode"
    )
    parser.add_argument("--data-dir", "-d", default="data", help="Data directory")
    parser.add_argument("--list", "-l", action="store_true", help="List available workflows")
    
    args = parser.parse_args()
    
    # Créer le pipeline
    logger.info("Initializing RPA Vision V3...")
    pipeline = create_pipeline(
        data_dir=args.data_dir,
        use_gpu=False,
        enable_ui_detection=True
    )
    
    # Lister les workflows si demandé
    if args.list:
        workflows = pipeline.list_workflows()
        if not workflows:
            print("No workflows found.")
        else:
            print("\nAvailable workflows:")
            for wf in workflows:
                print(f"  - {wf['workflow_id']}: {wf['name']} ({wf['learning_state']})")
        return
    
    # Créer la boucle d'exécution
    loop = create_execution_loop(pipeline, capture_interval_ms=500)
    
    # Enregistrer les callbacks
    loop.on_step_complete(on_step_complete)
    loop.on_state_change(on_state_change)
    loop.on_error(on_error)
    
    # Déterminer le mode
    mode_map = {
        "observation": ExecutionMode.OBSERVATION,
        "coaching": ExecutionMode.COACHING,
        "supervised": ExecutionMode.SUPERVISED,
        "automatic": ExecutionMode.AUTOMATIC
    }
    mode = mode_map[args.mode]
    
    # Démarrer l'exécution
    logger.info(f"Starting workflow '{args.workflow}' in {args.mode} mode...")
    
    if mode == ExecutionMode.SUPERVISED:
        # En mode supervisé, utiliser le callback de confirmation
        loop.confirmation_callback = confirmation_callback
    
    success = loop.start(args.workflow, mode=mode)
    
    if not success:
        logger.error("Failed to start execution")
        return
    
    # Boucle principale - afficher la progression
    try:
        while loop.get_state() in [ExecutionState.RUNNING, ExecutionState.PAUSED, ExecutionState.WAITING_CONFIRMATION]:
            progress = loop.get_progress()
            
            # Afficher la progression
            print(
                f"\rProgress: {progress['steps_executed']} steps, "
                f"{progress['steps_succeeded']} succeeded, "
                f"{progress['steps_failed']} failed, "
                f"node: {progress['current_node'] or 'N/A'}",
                end="", flush=True
            )
            
            time.sleep(1)
    
    except KeyboardInterrupt:
        logger.info("\nStopping execution...")
        loop.stop()
    
    finally:
        # Afficher le résumé
        print("\n")
        final_progress = loop.get_progress()
        logger.info(f"Execution finished: {final_progress['status']}")
        logger.info(f"  Steps executed: {final_progress['steps_executed']}")
        logger.info(f"  Steps succeeded: {final_progress['steps_succeeded']}")
        logger.info(f"  Steps failed: {final_progress['steps_failed']}")
        logger.info(f"  Duration: {final_progress['duration_seconds']:.1f}s")
        
        # Nettoyer
        loop.cleanup()


if __name__ == "__main__":
    main()