From 81bdc02722d1d0559a0a2f6cd67b53a38185461c Mon Sep 17 00:00:00 2001
From: Nacim <nacim@biqoz.com>
Date: Mon, 23 Jun 2025 15:35:10 +0200
Subject: [PATCH] Update app.py

---
 app.py | 74 +++++++++++++++++++++++++++++++++++++++++++---------------
 1 file changed, 55 insertions(+), 19 deletions(-)

diff --git a/app.py b/app.py
index ad98aed..f0faeee 100644
--- a/app.py
+++ b/app.py
@@ -3,8 +3,8 @@ import logging
 import yaml
 from flask import Flask, request, jsonify, make_response
 
-# Import des classes nécessaires de Presidio
-from presidio_analyzer import AnalyzerEngine
+from presidio_analyzer import AnalyzerEngine, RecognizerRegistry, PatternRecognizer, Pattern
+from presidio_analyzer.nlp_engine import NlpEngineProvider
 
 # Configuration du logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
@@ -13,36 +13,70 @@ logger = logging.getLogger(__name__)
 # Initialisation de l'application Flask
 app = Flask(__name__)
 
-# --- LAISSER PRESIDIO GÉRER L'INITIALISATION ---
-# L'AnalyzerEngine, lorsqu'il est initialisé sans arguments, va automatiquement :
-# 1. Chercher la variable d'environnement PRESIDIO_ANALYZER_CONFIG_FILE.
-# 2. Lire le fichier de configuration (votre default.yaml).
-# 3. Créer et configurer tous les composants (moteur NLP, recognizers, etc.).
-
+# --- Initialisation Globale de l'Analyseur ---
 analyzer = None
 try:
-    logger.info("Initializing AnalyzerEngine using configuration from environment variable...")
-    analyzer = AnalyzerEngine()
-    logger.info("AnalyzerEngine initialized successfully.")
+    logger.info("--- Presidio Analyzer Service Starting ---")
+    
+    # 1. Charger la configuration depuis le fichier YAML
+    CONFIG_FILE_PATH = os.environ.get("PRESIDIO_ANALYZER_CONFIG_FILE", "conf/default.yaml")
+    logger.info(f"Loading configuration from: {CONFIG_FILE_PATH}")
+    with open(CONFIG_FILE_PATH, 'r', encoding='utf-8') as f:
+        config = yaml.safe_load(f)
+    logger.info("Configuration file loaded successfully.")
+
+    # 2. Créer le fournisseur de moteur NLP avec TOUTE la configuration
+    logger.info("Creating NLP engine provider...")
+    provider = NlpEngineProvider(nlp_configuration=config)
+    
+    # 3. Créer le registre de recognizers
+    logger.info("Creating and populating recognizer registry...")
+    registry = RecognizerRegistry()
+    # On charge les recognizers par défaut pour les langues supportées
+    registry.load_predefined_recognizers(languages=config.get("supported_languages"))
+    
+    # 4. Charger les recognizers personnalisés depuis la configuration
+    custom_recognizers_conf = config.get("recognizers", [])
+    for recognizer_conf in custom_recognizers_conf:
+        patterns = [Pattern(name=p['name'], regex=p['regex'], score=p['score']) for p in recognizer_conf['patterns']]
+        custom_recognizer = PatternRecognizer(
+            supported_entity=recognizer_conf['entity_name'],
+            name=recognizer_conf['name'],
+            supported_language=recognizer_conf['supported_language'],
+            patterns=patterns,
+            context=recognizer_conf.get('context')
+        )
+        registry.add_recognizer(custom_recognizer)
+        logger.info(f"Loaded custom recognizer: {custom_recognizer.name}")
+
+    # 5. Créer l'AnalyzerEngine avec tous les composants
+    logger.info("Initializing AnalyzerEngine with custom components...")
+    analyzer = AnalyzerEngine(
+        nlp_engine=provider.create_engine(),
+        registry=registry,
+        supported_languages=config.get("supported_languages")
+    )
+    logger.info("--- Presidio Analyzer Service Ready ---")
+
 except Exception as e:
-    logger.exception("FATAL: Error initializing AnalyzerEngine from configuration.")
-    # On s'assure que l'analyzer est None pour que les requêtes échouent proprement
-    analyzer = None
+    logger.exception("FATAL: Error during AnalyzerEngine initialization.")
+    analyzer = None # S'assurer que l'analyzer est None en cas d'échec
 
 @app.route('/analyze', methods=['POST'])
 def analyze_text():
     if not analyzer:
-        return jsonify({"error": "Analyzer engine not initialized. Check startup logs."}), 500
+        return jsonify({"error": "Analyzer engine is not available. Check startup logs for errors."}), 500
     
     try:
         data = request.get_json(force=True)
         text_to_analyze = data.get("text", "")
-        language = data.get("language", "en")
+        language = data.get("language", "fr") # Mettre 'fr' par défaut
 
         if not text_to_analyze:
              return jsonify({"error": "text field is missing or empty"}), 400
         
-        # L'allow list est chargée par l'AnalyzerEngine depuis le default.yaml
+        # L'allow list est chargée directement depuis la configuration de l'Analyzer
+        # car c'est une fonctionnalité intégrée.
         results = analyzer.analyze(
             text=text_to_analyze,
             language=language
@@ -51,9 +85,11 @@ def analyze_text():
         response_data = [res.to_dict() for res in results]
         return make_response(jsonify(response_data), 200)
     except Exception as e:
-        logger.exception("Error during analysis request.")
+        logger.exception(f"Error during analysis request for language '{language}'.")
+        # Renvoyer l'erreur spécifique de Presidio si elle est informative
+        if "No matching recognizers" in str(e):
+             return jsonify({"error": f"No recognizers available for language '{language}'. Please ensure the language model and recognizers are configured."}), 400
         return jsonify({"error": str(e)}), 500
 
 if __name__ == '__main__':
-    # Pour un test local sans gunicorn
     app.run(host='0.0.0.0', port=5001)