79 lines
2.2 KiB
Python
79 lines
2.2 KiB
Python
"""Application configuration using Pydantic Settings."""
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from functools import lru_cache
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from pathlib import Path
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import torch
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from pydantic_settings import BaseSettings, SettingsConfigDict
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class Settings(BaseSettings):
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"""Application settings loaded from environment variables."""
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model_config = SettingsConfigDict(
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env_file=".env",
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env_file_encoding="utf-8",
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case_sensitive=False,
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)
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# API Settings
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api_prefix: str = "/doc_process/v1"
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debug: bool = False
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# Base Host Settings (can be overridden via .env file)
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# Default: 127.0.0.1 (production)
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# Dev: Set BASE_HOST=100.115.184.74 in .env file
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base_host: str = "127.0.0.1"
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# PaddleOCR-VL Settings
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@property
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def paddleocr_vl_url(self) -> str:
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"""Get PaddleOCR-VL URL based on base_host."""
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return f"http://{self.base_host}:8001/v1"
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# MinerOCR Settings
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@property
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def miner_ocr_api_url(self) -> str:
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"""Get MinerOCR API URL based on base_host."""
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return f"http://{self.base_host}:8000/file_parse"
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# GLM OCR Settings
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@property
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def glm_ocr_url(self) -> str:
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"""Get GLM OCR URL based on base_host."""
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return f"http://{self.base_host}:8002/v1"
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# padding ratio
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is_padding: bool = True
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padding_ratio: float = 0.1
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max_tokens: int = 4096
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# Model Paths
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pp_doclayout_model_dir: str | None = "/home/yoge/.cache/modelscope/hub/models/PaddlePaddle/PP-DocLayoutV3"
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# Image Processing
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max_image_size_mb: int = 10
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image_padding_ratio: float = 0.1 # 10% on each side = 20% total expansion
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device: torch.device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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# Server Settings
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host: str = "0.0.0.0"
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port: int = 8053
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# Logging Settings
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log_dir: str | None = None # Defaults to /app/logs in container or ./logs locally
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log_level: str = "INFO" # DEBUG, INFO, WARNING, ERROR, CRITICAL
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@property
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def pp_doclayout_dir(self) -> Path:
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"""Get the PP-DocLayout model directory path."""
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return Path(self.pp_doclayout_model_dir)
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@lru_cache
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def get_settings() -> Settings:
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"""Get cached settings instance."""
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return Settings()
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