chore: add .gitignore

test_quality_tier_live.py

@@ -0,0 +1,146 @@
+#!/usr/bin/env python3
+"""Test live du quality_tier CPAM sur 3 dossiers existants.
+
+Force l'embedding SentenceTransformer sur CPU pour libérer la VRAM à Ollama Cloud.
+"""
+
+import os
+# Forcer CPU pour SentenceTransformer — la VRAM reste disponible pour Ollama
+os.environ["CUDA_VISIBLE_DEVICES"] = ""
+
+import json
+import sys
+import time
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent))
+
+from src.config import DossierMedical, ControleCPAM
+from src.control.cpam_parser import parse_cpam_excel
+from src.control.cpam_response import generate_cpam_response
+
+STRUCTURED_DIR = Path("output/structured")
+CPAM_EXCEL = Path("input/Control_cpam/SPHO-FINANC26020915121_ogc_structure.xlsx")
+
+# 3 dossiers avec contrôles CPAM connus
+DOSSIERS = [
+    "116_23065570",
+    "132_23080179",
+    "134_23050890",
+]
+
+# Délai entre les dossiers pour éviter les 429 sur Ollama Cloud
+INTER_DOSSIER_DELAY = 5  # secondes
+
+
+def load_dossier(subdir: str) -> DossierMedical | None:
+    fusionne = STRUCTURED_DIR / subdir / f"{subdir}_fusionne_cim10.json"
+    if not fusionne.exists():
+        # Fallback sur le premier JSON trouvé
+        jsons = list((STRUCTURED_DIR / subdir).glob("*_cim10.json"))
+        if not jsons:
+            return None
+        fusionne = jsons[0]
+    data = json.loads(fusionne.read_text(encoding="utf-8"))
+    return DossierMedical(**data)
+
+
+def main():
+    print("=" * 70)
+    print("TEST QUALITY_TIER CPAM — Mode Cloud (embedding CPU)")
+    print("=" * 70)
+    print()
+
+    # Charger les contrôles CPAM
+    if not CPAM_EXCEL.exists():
+        print(f"Fichier CPAM introuvable : {CPAM_EXCEL}")
+        return
+
+    cpam_data = parse_cpam_excel(str(CPAM_EXCEL))
+    print(f"Contrôles CPAM chargés : {len(cpam_data)} OGC\n")
+
+    results_summary = []
+
+    for i, subdir in enumerate(DOSSIERS):
+        if i > 0:
+            print(f"  [pause {INTER_DOSSIER_DELAY}s entre les dossiers...]\n")
+            time.sleep(INTER_DOSSIER_DELAY)
+
+        ogc_num = int(subdir.split("_")[0])
+        dossier = load_dossier(subdir)
+        if not dossier:
+            print(f"  [{subdir}] Dossier introuvable")
+            continue
+
+        # Trouver le contrôle CPAM correspondant (dict ogc → list[ControleCPAM])
+        ctrls = cpam_data.get(ogc_num)
+        if not ctrls:
+            print(f"  [{subdir}] Aucun contrôle OGC {ogc_num} trouvé")
+            continue
+
+        ctrl = ctrls[0]  # Premier contrôle pour cet OGC
+
+        dp_code = dossier.diagnostic_principal.cim10_suggestion if dossier.diagnostic_principal else "—"
+        n_das = len(dossier.diagnostics_associes)
+        n_bio = len(dossier.biologie_cle)
+        print(f"{'='*70}")
+        print(f"Dossier {subdir} — OGC {ogc_num}")
+        print(f"  DP: {dp_code}, DAS: {n_das}, Bio: {n_bio}")
+        print(f"  Titre: {ctrl.titre}")
+        print(f"  Décision UCR: {ctrl.decision_ucr}")
+        if ctrl.dp_ucr:
+            print(f"  DP UCR: {ctrl.dp_ucr}")
+        if ctrl.da_ucr:
+            print(f"  DA UCR: {ctrl.da_ucr}")
+        print()
+
+        t0 = time.time()
+        try:
+            text, result, sources = generate_cpam_response(dossier, ctrl)
+        except Exception as e:
+            print(f"  ERREUR: {e}")
+            results_summary.append((subdir, "ERREUR", str(e)))
+            continue
+        elapsed = time.time() - t0
+
+        print(f"  Temps: {elapsed:.1f}s")
+        print(f"  Sources RAG: {len(sources)}")
+        print(f"  Longueur texte: {len(text)} chars")
+        print()
+
+        # Quality tier (enrichi par generate_cpam_response)
+        print(f"  >>> QUALITY TIER: {ctrl.quality_tier}")
+        print(f"  >>> REQUIRES REVIEW: {ctrl.requires_review}")
+        if ctrl.quality_warnings:
+            print(f"  >>> WARNINGS ({len(ctrl.quality_warnings)}):")
+            for w in ctrl.quality_warnings:
+                print(f"      {w}")
+        else:
+            print(f"  >>> 0 warnings")
+
+        # Score adversarial si disponible
+        if result:
+            score_match = [
+                w for w in ctrl.quality_warnings
+                if "Score adversarial" in w
+            ]
+            if not score_match:
+                print(f"  >>> Score adversarial: non extrait des warnings (tier A implicite)")
+
+        print()
+        results_summary.append((subdir, ctrl.quality_tier, ctrl.requires_review))
+
+    # Résumé final
+    print("\n" + "=" * 70)
+    print("RÉSUMÉ")
+    print("=" * 70)
+    for subdir, tier, *rest in results_summary:
+        if tier == "ERREUR":
+            print(f"  {subdir}: ERREUR — {rest[0][:80]}")
+        else:
+            review = rest[0] if rest else "?"
+            print(f"  {subdir}: Tier {tier} | requires_review={review}")
+
+
+if __name__ == "__main__":
+    main()