2023-08-25 06:28:51 +02:00
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import os
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2023-06-25 05:18:09 +02:00
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from pathlib import Path
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2023-06-18 05:49:19 +02:00
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from pydantic import BaseSettings
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2023-06-25 05:18:09 +02:00
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from .schemas import ModelType
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2023-06-18 05:49:19 +02:00
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class Settings(BaseSettings):
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cache_folder: str = "/cache"
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2023-08-21 01:24:14 +02:00
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eager_startup: bool = False
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model_ttl: int = 0
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2023-06-18 05:49:19 +02:00
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host: str = "0.0.0.0"
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port: int = 3003
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workers: int = 1
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2023-06-28 01:21:33 +02:00
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test_full: bool = False
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2023-08-25 06:28:51 +02:00
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request_threads: int = os.cpu_count() or 4
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model_inter_op_threads: int = 1
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model_intra_op_threads: int = 2
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2023-06-18 05:49:19 +02:00
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2023-08-06 04:45:13 +02:00
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class Config:
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env_prefix = "MACHINE_LEARNING_"
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2023-06-18 05:49:19 +02:00
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case_sensitive = False
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2023-08-25 06:28:51 +02:00
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_clean_name = str.maketrans(":\\/", "___", ".")
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2023-06-25 05:18:09 +02:00
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def get_cache_dir(model_name: str, model_type: ModelType) -> Path:
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2023-08-25 06:28:51 +02:00
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return Path(settings.cache_folder) / model_type.value / model_name.translate(_clean_name)
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2023-06-25 05:18:09 +02:00
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2023-06-18 05:49:19 +02:00
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settings = Settings()
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