"""Configuration globale et modèles de données pour le pipeline T2A."""

from __future__ import annotations

from pathlib import Path
from typing import Optional

from pydantic import BaseModel, Field


# --- Chemins ---

BASE_DIR = Path(__file__).resolve().parent.parent
INPUT_DIR = BASE_DIR / "input"
OUTPUT_DIR = BASE_DIR / "output"
ANONYMIZED_DIR = OUTPUT_DIR / "anonymized"
STRUCTURED_DIR = OUTPUT_DIR / "structured"
REPORTS_DIR = OUTPUT_DIR / "reports"

for d in (INPUT_DIR, ANONYMIZED_DIR, STRUCTURED_DIR, REPORTS_DIR):
    d.mkdir(parents=True, exist_ok=True)


# --- Configuration anonymisation ---

KEEP_ESTABLISHMENT_NAME = True
NER_MODEL = "Jean-Baptiste/camembert-ner"
NER_CONFIDENCE_THRESHOLD = 0.80


# --- Configuration Ollama ---

OLLAMA_URL = "http://localhost:11434"
OLLAMA_MODEL = "mistral-large-3:675b-cloud"
OLLAMA_TIMEOUT = 120


# --- Configuration RAG ---

RAG_INDEX_DIR = BASE_DIR / "data" / "rag_index"
CIM10_DICT_PATH = BASE_DIR / "data" / "cim10_dict.json"
CCAM_DICT_PATH = BASE_DIR / "data" / "ccam_dict.json"
CIM10_PDF = Path("/home/dom/ai/aivanov_CIM/cim-10-fr_2026_a_usage_pmsi_version_provisoire_111225.pdf")
GUIDE_METHODO_PDF = Path("/home/dom/ai/aivanov_CIM/guide_methodo_mco_2026_version_provisoire.pdf")
CCAM_PDF = Path("/home/dom/ai/aivanov_CIM/actualisation_ccam_descriptive_a_usage_pmsi_v4_2025.pdf")


# --- Modèles de données CIM-10 ---


class RAGSource(BaseModel):
    document: str
    page: Optional[int] = None
    code: Optional[str] = None
    extrait: Optional[str] = None


class Sejour(BaseModel):
    sexe: Optional[str] = None
    age: Optional[int] = None
    date_entree: Optional[str] = None
    date_sortie: Optional[str] = None
    duree_sejour: Optional[int] = None
    mode_entree: Optional[str] = None
    mode_sortie: Optional[str] = None
    imc: Optional[float] = None
    poids: Optional[float] = None
    taille: Optional[float] = None


class Diagnostic(BaseModel):
    texte: str
    cim10_suggestion: Optional[str] = None
    cim10_confidence: Optional[str] = None
    justification: Optional[str] = None
    raisonnement: Optional[str] = None
    sources_rag: list[RAGSource] = Field(default_factory=list)
    est_cma: Optional[bool] = None
    est_cms: Optional[bool] = None
    niveau_severite: Optional[str] = None  # "leger" | "modere" | "severe" | "non_evalue"


class ActeCCAM(BaseModel):
    texte: str
    code_ccam_suggestion: Optional[str] = None
    date: Optional[str] = None
    validite: Optional[str] = None  # "valide" | "obsolete" | "non_verifie"
    alertes: list[str] = Field(default_factory=list)


class Traitement(BaseModel):
    medicament: str
    posologie: Optional[str] = None
    code_atc: Optional[str] = None


class BiologieCle(BaseModel):
    test: str
    valeur: Optional[str] = None
    anomalie: Optional[bool] = None


class Imagerie(BaseModel):
    type: str
    conclusion: Optional[str] = None
    score: Optional[str] = None


class DossierMedical(BaseModel):
    source_file: str = ""
    document_type: str = ""
    sejour: Sejour = Field(default_factory=Sejour)
    diagnostic_principal: Optional[Diagnostic] = None
    diagnostics_associes: list[Diagnostic] = Field(default_factory=list)
    actes_ccam: list[ActeCCAM] = Field(default_factory=list)
    antecedents: list[str] = Field(default_factory=list)
    traitements_sortie: list[Traitement] = Field(default_factory=list)
    biologie_cle: list[BiologieCle] = Field(default_factory=list)
    imagerie: list[Imagerie] = Field(default_factory=list)
    complications: list[str] = Field(default_factory=list)
    alertes_codage: list[str] = Field(default_factory=list)
    source_files: list[str] = Field(default_factory=list)
    processing_time_s: float | None = None


# --- Rapport d'anonymisation ---


class AnonymizationReport(BaseModel):
    source_file: str
    total_replacements: int = 0
    regex_replacements: int = 0
    ner_replacements: int = 0
    sweep_replacements: int = 0
    entities_found: list[dict] = Field(default_factory=list)