Presidio/app.py

import os
import re
import logging
import yaml

from flask import Flask, request, jsonify, make_response

# ### CORRECTION ### - Import des classes nécessaires. 'Replace' est nouveau et crucial.
from presidio_analyzer import AnalyzerEngine, RecognizerResult, AnalyzerEngineProvider
from presidio_anonymizer import AnonymizerEngine
from presidio_anonymizer.anonymizers import Replace # NOUVEL IMPORT

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

app = Flask(__name__)

# --- Initialisation ---
analyzer = None
anonymizer = None
anonymizer_config = {} # ### CORRECTION ### - On stocke la config pour l'utiliser plus tard

try:
    logger.info("--- Presidio Service Starting ---")
    CONFIG_FILE_PATH = os.environ.get("PRESIDIO_ANALYZER_CONFIG_FILE", "conf/default.yaml")

    if not os.path.exists(CONFIG_FILE_PATH):
        raise FileNotFoundError(f"Configuration file not found at: {CONFIG_FILE_PATH}")

    # 1. Initialiser l'AnalyzerEngine (cette partie est maintenant correcte).
    provider = AnalyzerEngineProvider(analyzer_engine_conf_file=CONFIG_FILE_PATH)
    analyzer = provider.create_engine()
    logger.info("AnalyzerEngine created successfully.")

    # 2. ### CORRECTION FONDAMENTALE ###
    # L'AnonymizerEngine est initialisé SANS argument.
    anonymizer = AnonymizerEngine()
    logger.info("AnonymizerEngine created successfully.")

    # 3. On charge la config d'anonymisation pour l'utiliser DANS l'endpoint.
    with open(CONFIG_FILE_PATH, 'r') as f:
        config_from_file = yaml.safe_load(f)
    anonymizer_config = config_from_file.get("anonymizer_config", {})
    logger.info("Anonymizer configuration loaded.")

    logger.info(f"Analyzer and Anonymizer are ready. Languages: {analyzer.supported_languages}")

except Exception as e:
    logger.exception("FATAL: Error during Presidio engines initialization.")
    analyzer = None
    anonymizer = None
# --- Fin de la section d'initialisation ---


# Le reste de votre logique de filtrage et de recadrage reste INCHANGÉ.
# ... (IBAN_REGEX, IPV4_REGEX, IGNORE_LABELS, normalize_label) ...
IBAN_REGEX = re.compile(r"\b[A-Z]{2}[0-9]{2}(?:\s[0-9]{4}){3}\b", re.IGNORECASE)
IPV4_REGEX = re.compile(
    r"\b(?:(?:25[0-5]|2[0-4][0-9]|1\d{2}|[1-9]?\d)\.){3}"
    r"(?:25[0-5]|2[0-4][0-9]|1\d{2}|[1-9]?\d)\b"
)
IGNORE_LABELS = {
    "témoins", "témoins clés", "coordonnées", "coordonnées bancaires",
    "contexte financier", "données sensibles", "contexte", "montrent",
    "montrent des", "montrent des irrégularités", "bénéficiaire",
}
def normalize_label(text: str) -> str:
    return text.strip().lower()


# =====================================================================
# VOTRE ENDPOINT /analyze ORIGINAL - SANS AUCUN CHANGEMENT
# =====================================================================
@app.route("/analyze", methods=["POST"])
def analyze_text():
    # ... (Votre code pour /analyze reste identique)
    if not analyzer:
        return jsonify({"error": "Analyzer engine is not available. Check startup logs."}), 500
    try:
        data = request.get_json(force=True)
        text_to_analyze = data.get("text", "")
        language = data.get("language", "fr")
        if not text_to_analyze:
            return jsonify({"error": "text field is missing or empty"}), 400
        results = analyzer.analyze(text=text_to_analyze, language=language)
        filtered_results = []
        for res in results:
            ent_text = text_to_analyze[res.start:res.end].strip()
            ent_text_norm = normalize_label(ent_text)
            if ent_text_norm in IGNORE_LABELS:
                continue
            if res.entity_type == "IBAN":
                if not IBAN_REGEX.search(ent_text): continue
            if res.entity_type == "IP_ADDRESS":
                if not IPV4_REGEX.search(ent_text): continue
            filtered_results.append(res)
        response_data = [res.to_dict() for res in filtered_results]
        return make_response(jsonify(response_data), 200)
    except Exception as e:
        logger.exception("Error processing analysis")
        return jsonify({"error": str(e)}), 500

# =====================================================================
# ### CORRECTION FONDAMENTALE ### NOUVEL ENDPOINT /anonymize
# =====================================================================
@app.route("/anonymize", methods=["POST"])
def anonymize_text():
    if not analyzer or not anonymizer:
        return jsonify({"error": "Presidio engines are not available. Check startup logs."}), 500

    try:
        data = request.get_json(force=True)
        text_to_process = data.get("text", "")
        language = data.get("language", "fr")

        if not text_to_process:
            return jsonify({"error": "text field is missing or empty"}), 400

        # Étape 1 : Analyser le texte (comme avant)
        analyzer_results = analyzer.analyze(text=text_to_process, language=language)

        # Étape 2 : ### NOUVELLE LOGIQUE ###
        # Construire le dictionnaire d'anonymiseurs à partir de notre configuration
        anonymizers_from_config = {}
        if "default_anonymizers" in anonymizer_config and "replacements" in anonymizer_config:
            default_anonymizers = anonymizer_config["default_anonymizers"]
            replacements = anonymizer_config["replacements"]
            for entity, method in default_anonymizers.items():
                if method.lower() == "replace":
                    # On cherche la valeur de remplacement pour cette entité
                    new_value = replacements.get(entity)
                    if new_value is not None:
                        anonymizers_from_config[entity] = Replace(new_value=new_value)

        # Étape 3 : Appeler .anonymize() en lui passant le dictionnaire que nous venons de créer
        anonymized_result = anonymizer.anonymize(
            text=text_to_process,
            analyzer_results=analyzer_results,
            anonymizers=anonymizers_from_config # On passe notre configuration ici
        )

        # Étape 4 : Renvoyer le texte anonymisé
        return jsonify({"text": anonymized_result.text}), 200

    except Exception as e:
        logger.exception("Error processing anonymization request")
        return jsonify({"error": str(e)}), 500

# =====================================================================
# DÉMARRAGE DE L'APPLICATION FLASK (INCHANGÉ)
# =====================================================================
if __name__ == "__main__":
    app.run(host="0.0.0.0", port=5001)