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| from typing import Optional, List | |
| from .base_parser import BaseParser | |
| class UnstructuredParser(BaseParser): | |
| def __init__(self, strategy: str = "auto", ocr_languages: Optional[List[str]] = None): | |
| """ | |
| Initialize the unstructured parser | |
| Args: | |
| strategy: Partitioning strategy ("auto", "fast", "hi_res", "ocr_only") | |
| ocr_languages: List of languages for OCR (e.g., ["eng", "spa"]) | |
| """ | |
| super().__init__() | |
| self.strategy = strategy | |
| self.ocr_languages = ocr_languages or ["eng"] | |
| self._unstructured_loaded = False | |
| def _load_unstructured(self): | |
| """Lazy load unstructured module""" | |
| if not self._unstructured_loaded: | |
| global partition_pdf | |
| from unstructured.partition.pdf import partition_pdf | |
| self._unstructured_loaded = True | |
| def parse(self, file_path: str) -> str: | |
| """ | |
| Parse a document using unstructured.io | |
| Args: | |
| file_path: Path to the document file | |
| Returns: | |
| str: Extracted text content | |
| """ | |
| try: | |
| if not self._unstructured_loaded: | |
| self._load_unstructured() | |
| # Convert list of languages to comma-separated string | |
| ocr_lang_str = ",".join(self.ocr_languages) | |
| # Partition the document | |
| elements = partition_pdf( | |
| filename=file_path, | |
| strategy=self.strategy, | |
| ocr_languages=ocr_lang_str, # Pass string instead of list | |
| ) | |
| # Join elements with double newlines for better readability | |
| return "\n\n".join([str(el) for el in elements]) | |
| except Exception as e: | |
| raise Exception(f"Failed to parse document {file_path}: {str(e)}") | |