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- from pathlib import Path
- from pydantic import BaseSettings
- from .schemas import ModelType
- class Settings(BaseSettings):
- cache_folder: str = "/cache"
- classification_model: str = "microsoft/resnet-50"
- clip_image_model: str = "clip-ViT-B-32"
- clip_text_model: str = "clip-ViT-B-32"
- facial_recognition_model: str = "buffalo_l"
- min_tag_score: float = 0.9
- eager_startup: bool = True
- model_ttl: int = 0
- host: str = "0.0.0.0"
- port: int = 3003
- workers: int = 1
- min_face_score: float = 0.7
- test_full: bool = False
- class Config:
- env_prefix = "MACHINE_LEARNING_"
- case_sensitive = False
- def get_cache_dir(model_name: str, model_type: ModelType) -> Path:
- return Path(settings.cache_folder, model_type.value, model_name)
- settings = Settings()
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