app/utils/helpers.py

from cachetools import TTLCache
from typing import Any, Optional


cache = TTLCache(maxsize=512, ttl=60 * 10)


def cache_get(key: str) -> Any | None:
    return cache.get(key)


def cache_set(key: str, value: Any) -> None:
    cache[key] = value


def medical_disclaimer(language: str) -> str:
    if language.lower().startswith("fr"):
        return (
            "Avertissement: Je ne suis pas un médecin. Les conseils fournis par l'IA peuvent contenir des erreurs. "
            "En cas de symptômes graves, consultez un professionnel de santé ou appelez les services d'urgence."
        )
    return (
        "Disclaimer: I am not a medical professional. AI advice can be inaccurate. "
        "For serious symptoms, consult a healthcare professional or emergency services."
    )


def emergency_triage(text: str) -> bool:
    signals = ["chest pain", "poitrine", "hemorrag", "fainting", "inconscient", "stroke", "AVC", "difficulty breathing", "respire"]
    lower = text.lower()
    return any(s in lower for s in signals)


def normalize_gender(value: str) -> Optional[str]:
    if value is None:
        return None
    v = value.strip().lower()
    mapping = {
        "m": "male", "male": "male", "man": "male", "masculin": "male", "homme": "male",
        "f": "female", "female": "female", "woman": "female", "feminin": "female", "femme": "female"
    }
    return mapping.get(v, None)


def clean_diagnosis(value: str) -> Optional[str]:
    if not value:
        return None
    v = value.strip().nlower() if hasattr(value, 'nlower') else value.strip().lower()
    return v