9d07894c6f
- Viewer : badges compteurs (DAS, actes, alertes, CMA), raisonnement LLM pliable, regroupement CCAM, navigation patient, alertes NON-CUMUL en rouge - Non-cumul CCAM : 3 règles heuristiques (même base, même regroupement/jour, paires incompatibles) - Fusion multi-PDFs : merge_dossiers() avec priorité Trackare, spécificité CIM-10, déduplication, champ source_files - Index FAISS reconstruit : 21 141 vecteurs (CCAM dict 8 257 + CIM-10 alpha 306) - 192 tests unitaires passent Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
136 lines
3.9 KiB
Python
136 lines
3.9 KiB
Python
"""Configuration globale et modèles de données pour le pipeline T2A."""
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from __future__ import annotations
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from pathlib import Path
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from typing import Optional
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from pydantic import BaseModel, Field
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# --- Chemins ---
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BASE_DIR = Path(__file__).resolve().parent.parent
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INPUT_DIR = BASE_DIR / "input"
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OUTPUT_DIR = BASE_DIR / "output"
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ANONYMIZED_DIR = OUTPUT_DIR / "anonymized"
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STRUCTURED_DIR = OUTPUT_DIR / "structured"
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REPORTS_DIR = OUTPUT_DIR / "reports"
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for d in (INPUT_DIR, ANONYMIZED_DIR, STRUCTURED_DIR, REPORTS_DIR):
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d.mkdir(parents=True, exist_ok=True)
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# --- Configuration anonymisation ---
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KEEP_ESTABLISHMENT_NAME = True
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NER_MODEL = "Jean-Baptiste/camembert-ner"
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NER_CONFIDENCE_THRESHOLD = 0.80
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# --- Configuration Ollama ---
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OLLAMA_URL = "http://localhost:11434"
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OLLAMA_MODEL = "mistral-large-3:675b-cloud"
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OLLAMA_TIMEOUT = 120
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# --- Configuration RAG ---
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RAG_INDEX_DIR = BASE_DIR / "data" / "rag_index"
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CIM10_DICT_PATH = BASE_DIR / "data" / "cim10_dict.json"
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CCAM_DICT_PATH = BASE_DIR / "data" / "ccam_dict.json"
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CIM10_PDF = Path("/home/dom/ai/aivanov_CIM/cim-10-fr_2026_a_usage_pmsi_version_provisoire_111225.pdf")
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GUIDE_METHODO_PDF = Path("/home/dom/ai/aivanov_CIM/guide_methodo_mco_2026_version_provisoire.pdf")
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CCAM_PDF = Path("/home/dom/ai/aivanov_CIM/actualisation_ccam_descriptive_a_usage_pmsi_v4_2025.pdf")
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# --- Modèles de données CIM-10 ---
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class RAGSource(BaseModel):
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document: str
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page: Optional[int] = None
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code: Optional[str] = None
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extrait: Optional[str] = None
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class Sejour(BaseModel):
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sexe: Optional[str] = None
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age: Optional[int] = None
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date_entree: Optional[str] = None
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date_sortie: Optional[str] = None
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duree_sejour: Optional[int] = None
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mode_entree: Optional[str] = None
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mode_sortie: Optional[str] = None
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imc: Optional[float] = None
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poids: Optional[float] = None
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taille: Optional[float] = None
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class Diagnostic(BaseModel):
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texte: str
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cim10_suggestion: Optional[str] = None
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cim10_confidence: Optional[str] = None
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justification: Optional[str] = None
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raisonnement: Optional[str] = None
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sources_rag: list[RAGSource] = Field(default_factory=list)
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est_cma: Optional[bool] = None
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est_cms: Optional[bool] = None
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niveau_severite: Optional[str] = None # "leger" | "modere" | "severe" | "non_evalue"
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class ActeCCAM(BaseModel):
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texte: str
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code_ccam_suggestion: Optional[str] = None
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date: Optional[str] = None
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validite: Optional[str] = None # "valide" | "obsolete" | "non_verifie"
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alertes: list[str] = Field(default_factory=list)
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class Traitement(BaseModel):
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medicament: str
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posologie: Optional[str] = None
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code_atc: Optional[str] = None
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class BiologieCle(BaseModel):
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test: str
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valeur: Optional[str] = None
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anomalie: Optional[bool] = None
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class Imagerie(BaseModel):
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type: str
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conclusion: Optional[str] = None
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score: Optional[str] = None
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class DossierMedical(BaseModel):
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source_file: str = ""
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document_type: str = ""
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sejour: Sejour = Field(default_factory=Sejour)
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diagnostic_principal: Optional[Diagnostic] = None
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diagnostics_associes: list[Diagnostic] = Field(default_factory=list)
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actes_ccam: list[ActeCCAM] = Field(default_factory=list)
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antecedents: list[str] = Field(default_factory=list)
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traitements_sortie: list[Traitement] = Field(default_factory=list)
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biologie_cle: list[BiologieCle] = Field(default_factory=list)
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imagerie: list[Imagerie] = Field(default_factory=list)
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complications: list[str] = Field(default_factory=list)
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alertes_codage: list[str] = Field(default_factory=list)
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source_files: list[str] = Field(default_factory=list)
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processing_time_s: float | None = None
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# --- Rapport d'anonymisation ---
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class AnonymizationReport(BaseModel):
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source_file: str
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total_replacements: int = 0
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regex_replacements: int = 0
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ner_replacements: int = 0
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sweep_replacements: int = 0
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entities_found: list[dict] = Field(default_factory=list)
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