feat: dp_finalizer — arbitrage Trackare vs CRH-only avec traçabilité audit

Nouveau module src/medical/dp_finalizer.py :
- 5 règles d'arbitrage (R1-R5) : CRH CONFIRMED override, Trackare corroboré,
  symptôme R* override/review, ambigu REVIEW, Z-code/R-code interdits auto-confirm
- Traçabilité : dp_trackare, dp_crh_only, dp_final sur DossierMedical
- quality_flags dict (merge sans écraser) + alertes_codage (append)

Modèles config.py :
- DPCandidate, DPSelection (NUKE-3)
- get_dp_ranker_llm_enabled(), check_adversarial_model_config()
- Champs DossierMedical : dp_trackare, dp_crh_only, dp_final, quality_flags

Intégration :
- main.py : appel finalize_dp() après vetos/GHM (individuel + fusionné)
- benchmark : finalizer dans _rebuild_and_select(), dp_final dans output

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
dom
2026-02-24 17:50:07 +01:00
parent cad0dd22b1
commit c7317af447
4 changed files with 457 additions and 9 deletions

View File

@@ -68,6 +68,52 @@ def get_model(role: str) -> str:
return OLLAMA_MODELS.get(role, OLLAMA_MODEL)
# --- Flag LLM pour le sélecteur DP (NUKE-3) ---
# Nom canonique : T2A_DP_RANKER_LLM (0/1)
# Ancien nom accepté (compat) : DP_RANKER_LLM_ENABLED
DP_RANKER_LLM_ENABLED = os.environ.get("T2A_DP_RANKER_LLM", "1").lower() in ("1", "true", "yes")
def get_dp_ranker_llm_enabled() -> bool:
"""Retourne l'état du flag LLM pour NUKE-3 (lecture fraîche de l'env).
Nom canonique : T2A_DP_RANKER_LLM (0/1/true/false/yes/no).
Accepte aussi l'ancien nom DP_RANKER_LLM_ENABLED avec warning.
"""
canonical = os.environ.get("T2A_DP_RANKER_LLM")
legacy = os.environ.get("DP_RANKER_LLM_ENABLED")
if canonical is not None:
return canonical.lower() in ("1", "true", "yes")
if legacy is not None:
import logging as _logging
_logging.getLogger(__name__).warning(
"Env var DP_RANKER_LLM_ENABLED est dépréciée — utiliser T2A_DP_RANKER_LLM"
)
return legacy.lower() in ("1", "true", "yes")
# Défaut : activé
return True
def check_adversarial_model_config() -> tuple[bool, str]:
"""LOGIC-3 — Vérifie si les modèles CPAM et validation sont identiques.
Returns:
(same_model, warning_message)
"""
cpam = OLLAMA_MODELS.get("cpam", "")
validation = OLLAMA_MODELS.get("validation", "")
if cpam and validation and cpam == validation:
msg = (
f"Modèles CPAM et validation identiques ({cpam}) "
"— validation adversariale dégradée"
)
return True, msg
return False, ""
# --- Configuration RUM / établissement ---
FINESS = os.environ.get("T2A_FINESS", "000000000")
@@ -553,6 +599,37 @@ class CodeDecision(BaseModel):
applied_rules: list[str] = Field(default_factory=list)
class DPCandidate(BaseModel):
"""Candidat DP pour la sélection NUKE-3."""
index: int
term: str
code: Optional[str] = None
confidence: Optional[str] = None
source: Optional[str] = None
is_comorbidity_like: bool = False
is_symptom_like: bool = False
is_act_only: bool = False
section_strength: int = 0
num_occurrences: int = 1
score: float = 0.0
score_details: dict = Field(default_factory=dict)
class DPSelection(BaseModel):
"""Résultat de la sélection NUKE-3 du DP."""
chosen_index: Optional[int] = None
chosen_term: Optional[str] = None
chosen_code: Optional[str] = None
confidence: Optional[str] = None
verdict: str = "REVIEW" # CONFIRMED | REVIEW
evidence: list[str] = Field(default_factory=list)
reason: Optional[str] = None
candidates: list[DPCandidate] = Field(default_factory=list)
debug_scores: Optional[dict] = None
class Diagnostic(BaseModel):
texte: str
cim10_suggestion: Optional[str] = None
@@ -656,6 +733,12 @@ class DossierMedical(BaseModel):
document_type: str = ""
sejour: Sejour = Field(default_factory=Sejour)
diagnostic_principal: Optional[Diagnostic] = None
dp_selection: Optional[DPSelection] = None
# Traçabilité DP (finalizer) — audit DIM
dp_trackare: Optional[DPSelection] = None # DP issu du Trackare (si existant)
dp_crh_only: Optional[DPSelection] = None # DP issu du CRH-only pipeline
dp_final: Optional[DPSelection] = None # DP final après arbitrage finalizer
quality_flags: dict = Field(default_factory=dict)
diagnostics_associes: list[Diagnostic] = Field(default_factory=list)
actes_ccam: list[ActeCCAM] = Field(default_factory=list)
antecedents: list[Antecedent] = Field(default_factory=list)