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immich/machine-learning/app/config.py

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import logging
import os
from pathlib import Path
import gunicorn
import starlette
from pydantic import BaseSettings
from rich.console import Console
from rich.logging import RichHandler
from .schemas import ModelType
class Settings(BaseSettings):
cache_folder: str = "/cache"
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
class LogSettings(BaseSettings):
log_level: str = "info"
no_color: bool = False
class Config:
case_sensitive = False
_clean_name = str.maketrans(":\\/", "___", ".")
def clean_name(model_name: str) -> str:
return model_name.split("/")[-1].translate(_clean_name)
def get_cache_dir(model_name: str, model_type: ModelType) -> Path:
return Path(settings.cache_folder) / model_type.value / clean_name(model_name)
def get_hf_model_name(model_name: str) -> str:
return f"immich-app/{clean_name(model_name)}"
LOG_LEVELS: dict[str, int] = {
"critical": logging.ERROR,
"error": logging.ERROR,
"warning": logging.WARNING,
"warn": logging.WARNING,
"info": logging.INFO,
"log": logging.INFO,
"debug": logging.DEBUG,
"verbose": logging.DEBUG,
}
settings = Settings()
log_settings = LogSettings()
class CustomRichHandler(RichHandler):
def __init__(self) -> None:
console = Console(color_system="standard", no_color=log_settings.no_color)
super().__init__(
show_path=False, omit_repeated_times=False, console=console, tracebacks_suppress=[gunicorn, starlette]
)
log = logging.getLogger("gunicorn.access")
log.setLevel(LOG_LEVELS.get(log_settings.log_level.lower(), logging.INFO))