125 lines
3.9 KiB
Python
125 lines
3.9 KiB
Python
"""
|
|
文档处理器工厂
|
|
|
|
提供统一的文档处理器创建和管理接口
|
|
"""
|
|
|
|
from typing import Any
|
|
|
|
from src.plugins.document_processor_base import BaseDocumentProcessor
|
|
from src.plugins.mineru_official_parser import MinerUOfficialParser
|
|
from src.plugins.mineru_parser import MinerUParser
|
|
from src.plugins.paddlex_parser import PaddleXDocumentParser
|
|
from src.plugins.rapid_ocr_processor import RapidOCRProcessor
|
|
from src.utils import logger
|
|
|
|
# 处理器实例缓存
|
|
_PROCESSOR_CACHE: dict[str, BaseDocumentProcessor] = {}
|
|
|
|
|
|
class DocumentProcessorFactory:
|
|
"""文档处理器工厂"""
|
|
|
|
# 处理器类型映射
|
|
PROCESSOR_TYPES = {
|
|
"onnx_rapid_ocr": RapidOCRProcessor,
|
|
"mineru_ocr": MinerUParser,
|
|
"mineru_official": MinerUOfficialParser,
|
|
"paddlex_ocr": PaddleXDocumentParser,
|
|
}
|
|
|
|
@classmethod
|
|
def get_processor(cls, processor_type: str, **kwargs) -> BaseDocumentProcessor:
|
|
"""
|
|
获取文档处理器实例 (单例模式)
|
|
|
|
Args:
|
|
processor_type: 处理器类型
|
|
- "onnx_rapid_ocr": RapidOCR 本地 OCR
|
|
- "mineru_ocr": MinerU HTTP API 文档解析
|
|
- "mineru_official": MinerU 官方云服务 API 文档解析
|
|
- "paddlex_ocr": PaddleX 版面解析
|
|
**kwargs: 处理器初始化参数
|
|
|
|
Returns:
|
|
BaseDocumentProcessor: 处理器实例
|
|
|
|
Raises:
|
|
ValueError: 不支持的处理器类型
|
|
"""
|
|
if processor_type not in cls.PROCESSOR_TYPES:
|
|
raise ValueError(f"不支持的处理器类型: {processor_type}. 支持的类型: {list(cls.PROCESSOR_TYPES.keys())}")
|
|
|
|
# 使用缓存避免重复创建
|
|
cache_key = f"{processor_type}_{hash(frozenset(kwargs.items()))}"
|
|
if cache_key not in _PROCESSOR_CACHE:
|
|
processor_class = cls.PROCESSOR_TYPES[processor_type]
|
|
_PROCESSOR_CACHE[cache_key] = processor_class(**kwargs)
|
|
logger.debug(f"创建文档处理器: {processor_type}")
|
|
|
|
return _PROCESSOR_CACHE[cache_key]
|
|
|
|
@classmethod
|
|
def process_file(cls, processor_type: str, file_path: str, params: dict | None = None) -> str:
|
|
"""
|
|
使用指定处理器处理文件 (便捷方法)
|
|
|
|
Args:
|
|
processor_type: 处理器类型
|
|
file_path: 文件路径
|
|
params: 处理参数
|
|
|
|
Returns:
|
|
str: 提取的文本
|
|
|
|
Raises:
|
|
DocumentProcessorException: 处理失败
|
|
"""
|
|
processor = cls.get_processor(processor_type)
|
|
return processor.process_file(file_path, params)
|
|
|
|
@classmethod
|
|
def check_health(cls, processor_type: str) -> dict[str, Any]:
|
|
"""
|
|
检查指定处理器的健康状态
|
|
|
|
Args:
|
|
processor_type: 处理器类型
|
|
|
|
Returns:
|
|
dict: 健康状态信息
|
|
"""
|
|
try:
|
|
processor = cls.get_processor(processor_type)
|
|
return processor.check_health()
|
|
except Exception as e:
|
|
return {
|
|
"status": "error",
|
|
"message": f"健康检查失败: {str(e)}",
|
|
"details": {"error": str(e)},
|
|
}
|
|
|
|
@classmethod
|
|
def check_all_health(cls) -> dict[str, dict[str, Any]]:
|
|
"""
|
|
检查所有处理器的健康状态
|
|
|
|
Returns:
|
|
dict: 各处理器的健康状态
|
|
"""
|
|
health_status = {}
|
|
for processor_type in cls.PROCESSOR_TYPES:
|
|
health_status[processor_type] = cls.check_health(processor_type)
|
|
return health_status
|
|
|
|
@classmethod
|
|
def get_available_processors(cls) -> list[str]:
|
|
"""返回所有可用的处理器类型"""
|
|
return list(cls.PROCESSOR_TYPES.keys())
|
|
|
|
@classmethod
|
|
def clear_cache(cls):
|
|
"""清除处理器缓存"""
|
|
_PROCESSOR_CACHE.clear()
|
|
logger.debug("文档处理器缓存已清除")
|