#!/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()