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- import os
- from pathlib import Path
- from pydantic import BaseSettings
- from .schemas import ModelType
- class Settings(BaseSettings):
- cache_folder: str = "/cache"
- eager_startup: bool = False
- model_ttl: int = 0
- host: str = "0.0.0.0"
- port: int = 3003
- workers: int = 1
- test_full: bool = False
- request_threads: int = os.cpu_count() or 4
- model_inter_op_threads: int = 1
- model_intra_op_threads: int = 2
- class Config:
- env_prefix = "MACHINE_LEARNING_"
- case_sensitive = False
- _clean_name = str.maketrans(":\\/", "___", ".")
- def get_cache_dir(model_name: str, model_type: ModelType) -> Path:
- return Path(settings.cache_folder) / model_type.value / model_name.translate(_clean_name)
- settings = Settings()
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