69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
"""
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Configuration settings for the inpainting server
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"""
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import os
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import platform
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from typing import Dict, Any
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from pydantic_settings import BaseSettings
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class Settings(BaseSettings):
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# System detection
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IS_JETSON: bool = platform.machine() == "aarch64" and "tegra" in platform.uname().release.lower()
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IS_X86: bool = platform.machine() in ["x86_64", "amd64"]
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# Server settings
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HOST: str = "0.0.0.0"
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PORT: int = 8008
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WORKERS: int = 1
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# GPU settings
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CUDA_DEVICE: int = 0
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FP16_ENABLED: bool = True
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# Jetson specific settings
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JETSON_MODE: bool = IS_JETSON
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JETSON_POWER_MODE: str = "MAXN" # MAXN, 5W, 10W, 15W
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JETSON_FAN_CONTROL: bool = True
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JETSON_TEMP_THRESHOLD: int = 75 # Celsius
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# Session pool settings
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SIMPLE_LAMA_SESSIONS: int = 2 if IS_JETSON else 4
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MIGAN_SESSIONS: int = 2 if IS_JETSON else 4
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REMBG_SESSIONS: int = 1 if IS_JETSON else 3
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# Worker settings (Jetson은 더 적은 워커 사용)
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MAX_WORKERS: int = 6 if IS_JETSON else 16
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MIN_WORKERS: int = 2 if IS_JETSON else 8
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WORKER_TIMEOUT: int = 120 # 2 minutes
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# VRAM management (Jetson은 더 보수적인 설정)
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VRAM_THRESHOLD_HIGH: float = 0.7 if IS_JETSON else 0.85 # 70% for Jetson, 85% for x86
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VRAM_THRESHOLD_LOW: float = 0.3 if IS_JETSON else 0.25 # 30% for Jetson, 25% for x86
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VRAM_CHECK_INTERVAL: int = 20 if IS_JETSON else 20 # More frequent for both
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# Model paths
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SIMPLE_LAMA_MODEL_PATH: str = "models/simple-lama"
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MIGAN_MODEL_PATH: str = "models/migan"
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REMBG_MODEL_PATH: str = "models/rembg"
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# Upload settings
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MAX_FILE_SIZE: int = 25 * 1024 * 1024 if IS_JETSON else 100 * 1024 * 1024 # 25MB for Jetson, 100MB for x86
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MAX_IMAGE_SIZE: int = 2048 if IS_JETSON else 8192 # Maximum image dimension for Jetson, 8K for x86
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ALLOWED_EXTENSIONS: set = {".jpg", ".jpeg", ".png", ".bmp", ".tiff"}
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# Monitoring
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ENABLE_MONITORING: bool = True
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MONITORING_PORT: int = 8888
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# Jetson performance settings
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JETSON_GPU_FREQ: int = 1200 # MHz
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JETSON_CPU_FREQ: int = 1900 # MHz
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JETSON_MEMORY_FREQ: int = 1600 # MHz
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class Config:
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env_file = ".env"
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settings = Settings()
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