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import os
from typing import Optional
class Config:
"""Application configuration for working with local GGUF models"""
# Model settings - using Hugging Face downloaded model
MODEL_REPO = "unsloth/gemma-3-270m-it-GGUF"
MODEL_FILENAME = "gemma-3-270m-it-Q8_0.gguf"
MODEL_PATH = f"/app/models/{MODEL_FILENAME}"
HUGGINGFACE_TOKEN: str = os.getenv("HUGGINGFACE_TOKEN", "")
# Model loading settings - optimized for Docker container
N_CTX: int = int(os.getenv("N_CTX", "1024")) # Reduced context window for Docker
N_GPU_LAYERS: int = int(os.getenv("N_GPU_LAYERS", "0")) # CPU-only for Docker by default
N_THREADS: int = int(os.getenv("N_THREADS", "2")) # Conservative thread count
N_BATCH: int = int(os.getenv("N_BATCH", "512")) # Smaller batch size for Docker
USE_MLOCK: bool = os.getenv("USE_MLOCK", "false").lower() == "true" # Disabled for Docker
USE_MMAP: bool = os.getenv("USE_MMAP", "true").lower() == "true" # Keep memory mapping
F16_KV: bool = os.getenv("F16_KV", "false").lower() == "true" # Use 16-bit keys and values
SEED: int = int(os.getenv("SEED", "42")) # Random seed for reproducibility
# Server settings - Docker compatible
HOST: str = os.getenv("HOST", "0.0.0.0")
GRADIO_PORT: int = int(os.getenv("GRADIO_PORT", "7860")) # Standard HuggingFace Spaces port
API_PORT: int = int(os.getenv("API_PORT", "8000"))
# Logging settings
LOG_LEVEL: str = os.getenv("LOG_LEVEL", "INFO") # INFO, WARNING, ERROR, DEBUG
# Generation settings - optimized for Docker
MAX_NEW_TOKENS: int = int(os.getenv("MAX_NEW_TOKENS", "256")) # Reduced for faster response
TEMPERATURE: float = 1.0
# File upload settings
MAX_FILE_SIZE: int = int(os.getenv("MAX_FILE_SIZE", "10485760")) # 10MB
ALLOWED_IMAGE_EXTENSIONS: set = {".jpg", ".jpeg", ".png", ".gif", ".bmp", ".webp"}
@classmethod
def is_model_available(cls) -> bool:
"""Check if local model file exists"""
return os.path.exists(cls.MODEL_PATH)
@classmethod
def get_model_path(cls) -> str:
"""Get absolute path to model file"""
return os.path.abspath(cls.MODEL_PATH)
@classmethod
def get_models_dir(cls) -> str:
"""Get models directory path"""
return os.path.dirname(cls.MODEL_PATH)
@classmethod
def load_from_env_file(cls, env_file: str = ".env") -> None:
"""Load configuration from .env file"""
if os.path.exists(env_file):
with open(env_file, 'r') as f:
for line in f:
line = line.strip()
if line and not line.startswith('#') and '=' in line:
key, value = line.split('=', 1)
os.environ[key.strip()] = value.strip()
# Automatically load from .env file on import
Config.load_from_env_file()
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