immich/machine-learning/app/config.py
Mert 54b2779b79
chore(ml): improved logging (#3918)
* fixed `minScore` not being set correctly

* apply to init

* don't send `enabled`

* fix eslint warning

* added logger

* added logging

* refinements

* enable access log for info level

* formatting

* merged strings

---------

Co-authored-by: Alex <alex.tran1502@gmail.com>
2023-08-30 08:22:01 +00:00

67 lines
1.6 KiB
Python

import logging
import os
from pathlib import Path
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"
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
class LogSettings(BaseSettings):
log_level: str = "info"
no_color: bool = False
class Config:
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)
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()
console = Console(color_system="standard", no_color=log_settings.no_color)
logging.basicConfig(
format="%(message)s",
handlers=[
RichHandler(show_path=False, omit_repeated_times=False, console=console, tracebacks_suppress=[starlette])
],
)
log = logging.getLogger("uvicorn")
log.setLevel(LOG_LEVELS.get(log_settings.log_level.lower(), logging.INFO))