from __future__ import annotations

from dataclasses import dataclass
from pathlib import Path
import os


@dataclass(frozen=True)
class Settings:
    dataset_path: Path = Path(os.getenv("BITEWISE_DATASET_PATH", "data/united_master_database_corrected.csv"))
    ner_model_name: str = os.getenv("BITEWISE_NER_MODEL", "Dizex/InstaFoodRoBERTa-NER")
    qa_model_name: str = os.getenv(
        "BITEWISE_QA_MODEL",
        "bert-large-uncased-whole-word-masking-finetuned-squad",
    )
    semantic_model_name: str = os.getenv("BITEWISE_SEMANTIC_MODEL", "glove-wiki-gigaword-50")
    semantic_model_path: str = os.getenv("BITEWISE_SEMANTIC_PATH", "")
    enable_semantic_download: bool = os.getenv("BITEWISE_ENABLE_SEMANTIC_DOWNLOAD", "1") == "1"
    max_ingredients: int = int(os.getenv("BITEWISE_MAX_INGREDIENTS", "48"))
    similarity_threshold: float = float(os.getenv("BITEWISE_SIM_THRESHOLD", "0.52"))


settings = Settings()