"""
Pipeline d'extraction d'entités
"""

import os
import logging
import re
from typing import Dict, Any, List

logger = logging.getLogger(__name__)

def run(doc_id: str, ctx: Dict[str, Any]) -> None:
    """Pipeline d'extraction d'entités"""
    logger.info(f"🔍 Extraction d'entités pour le document {doc_id}")
    
    try:
        ocr_text = ctx.get("ocr_text", "")
        document_type = ctx.get("document_type", "autre")
        
        # Extraction basique
        entities = _extract_basic_entities(ocr_text, document_type)
        
        ctx.update({
            "extracted_entities": entities,
            "entities_count": len(entities)
        })
        logger.info(f"✅ Extraction terminée pour {doc_id}: {len(entities)} entités")
    except Exception as e:
        logger.error(f"❌ Erreur extraction {doc_id}: {e}")
        ctx["extraction_error"] = str(e)

def _extract_basic_entities(text: str, doc_type: str) -> List[Dict[str, Any]]:
    """Extraction basique d'entités"""
    entities = []
    
    # Emails
    emails = re.findall(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b', text)
    for email in emails:
        entities.append({
            "type": "contact",
            "subtype": "email",
            "value": email,
            "confidence": 0.95
        })
    
    # Téléphones
    phones = re.findall(r'\b0[1-9](?:[.\-\s]?\d{2}){4}\b', text)
    for phone in phones:
        entities.append({
            "type": "contact",
            "subtype": "phone",
            "value": phone,
            "confidence": 0.9
        })
    
    # Dates
    dates = re.findall(r'\b\d{1,2}[\/\-\.]\d{1,2}[\/\-\.]\d{4}\b', text)
    for date in dates:
        entities.append({
            "type": "date",
            "subtype": "generic",
            "value": date,
            "confidence": 0.8
        })
    
    return entities