127 lines
4.8 KiB
Python
127 lines
4.8 KiB
Python
import os
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import re
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import logging
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from flask import Flask, request, jsonify, make_response
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from presidio_analyzer import AnalyzerEngineProvider
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logging.basicConfig(level=logging.INFO,
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format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
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logger = logging.getLogger(__name__)
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app = Flask(__name__)
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# Initialisation Presidio Analyzer via Provider
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analyzer = None
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try:
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logger.info("--- Presidio Analyzer Service Starting ---")
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CONFIG_FILE_PATH = os.environ.get("PRESIDIO_ANALYZER_CONFIG_FILE", "conf/default.yaml")
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provider = AnalyzerEngineProvider(analyzer_engine_conf_file=CONFIG_FILE_PATH)
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analyzer = provider.create_engine()
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logger.info(f"Analyzer ready. Supported languages: {analyzer.supported_languages}")
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except Exception as e:
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logger.exception("Error during AnalyzerEngine initialization.")
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analyzer = None
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# Regex pour recadrage strict
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IBAN_REGEX = re.compile(r"\b[A-Z]{2}[0-9]{2}(?:\s[A-Z0-9]{4}){4,7}\b", re.IGNORECASE)
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IPV4_REGEX = re.compile(r"\b(?:25[0-5]|2[0-4]\d|1\d{2}|[1-9]?\d)(?:\.(?:25[0-5]|2[0-4]\d|1\d{2}|[1-9]?\d)){3}\b")
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# Liste des labels/phrases à exclure de l'anonymisation (en minuscules)
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IGNORE_LABELS = {
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"témoins",
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"témoins clés",
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"coordonnées",
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"coordonnées bancaires",
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"contexte financier",
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"données sensibles",
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"contexte",
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"montrent",
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"montrent des",
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"montrent des irrégularités",
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"bénéficiaire",
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}
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def normalize_label(text: str) -> str:
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return text.strip().lower()
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@app.route("/analyze", methods=["POST"])
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def analyze_text():
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if not analyzer:
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return jsonify({"error": "Analyzer engine is not available. Check startup logs."}), 500
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try:
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data = request.get_json(force=True)
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text_to_analyze = data.get("text", "")
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language = data.get("language", "fr")
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if not text_to_analyze:
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return jsonify({"error": "text field is missing or empty"}), 400
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results = analyzer.analyze(text=text_to_analyze, language=language)
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filtered_results = []
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for res in results:
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ent_text = text_to_analyze[res.start:res.end].strip()
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ent_text_norm = normalize_label(ent_text)
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# Skip anonymization for labels to keep
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if ent_text_norm in IGNORE_LABELS:
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logger.debug(f"Skipping anonymization of label: '{ent_text}'")
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continue
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# Recadrage stricte IBAN
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if res.entity_type == "IBAN":
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match = IBAN_REGEX.search(ent_text)
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if match:
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true_iban = match.group(0)
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start_offset = ent_text.find(true_iban)
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if start_offset != -1:
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old_start, old_end = res.start, res.end
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res.start += start_offset
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res.end = res.start + len(true_iban)
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ent_text = true_iban
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logger.debug(f"Adjusted IBAN span from ({old_start}-{old_end}) to ({res.start}-{res.end}): '{ent_text}'")
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else:
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logger.warning(f"Cannot find exact IBAN substring inside entity: '{ent_text}'")
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else:
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# Pas un IBAN valide, ignorer cette entité
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logger.warning(f"Entity IBAN does not match strict IBAN regex: '{ent_text}'")
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continue
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# Recadrage stricte IP_ADDRESS
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if res.entity_type == "IP_ADDRESS":
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match = IPV4_REGEX.search(ent_text)
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if match:
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true_ip = match.group(0)
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start_offset = ent_text.find(true_ip)
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if start_offset != -1:
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old_start, old_end = res.start, res.end
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res.start += start_offset
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res.end = res.start + len(true_ip)
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ent_text = true_ip
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logger.debug(f"Adjusted IP_ADDRESS span from ({old_start}-{old_end}) to ({res.start}-{res.end}): '{ent_text}'")
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else:
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logger.warning(f"Cannot find exact IP substring inside entity: '{ent_text}'")
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else:
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logger.warning(f"Entity IP_ADDRESS does not match IPv4 regex: '{ent_text}'")
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continue
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filtered_results.append(res)
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# Option: filtrer les chevauchements
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response_data = [res.to_dict() for res in filtered_results]
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return make_response(jsonify(response_data), 200)
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except Exception as e:
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logger.exception(f"Error during analysis for language '{language}'.")
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if "No matching recognizers" in str(e):
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return jsonify({"error": f"No recognizers available for language '{language}'."}), 400
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return jsonify({"error": str(e)}), 500
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if __name__ == "__main__":
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app.run(host="0.0.0.0", port=5001)
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