Spaces:
Running
on
Zero
Running
on
Zero
remove docling and pypdfium because of independencies
Browse files- README.md +1 -1
- requirements.txt +12 -10
- src/core/converter.py +1 -1
- src/parsers/__init__.py +0 -2
- src/parsers/docling_parser.py +0 -161
- src/parsers/pypdfium_parser.py +0 -78
README.md
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@@ -1,5 +1,5 @@
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---
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title: Markit
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emoji: π
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colorFrom: blue
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colorTo: indigo
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---
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title: Markit GOT OCR
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emoji: π
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colorFrom: blue
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colorTo: indigo
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requirements.txt
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gradio==5.14.0
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grpcio-status==1.70.0
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markdown==3.7
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multiprocess==0.70.16
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pipdeptree==2.25.0
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pytesseract==0.3.13
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semchunk==2.2.2
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Pillow>=9.0.0,<11.0.0
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numpy>=1.21.0
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tesseract==0.1.3
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tesserocr>=2.5.0; platform_system != "Windows" # Only install on non-Windows systems
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# Additional dependencies for image processing
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opencv-python-headless>=4.5.0 # Headless version for server environments
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dill==0.3.8 # Downgraded to be compatible with datasets
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# Gemini API client
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google-genai>=0.1.0
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# Environment variables
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python-dotenv>=1.0.0
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# Pin pydantic to resolve compatibility issues with gradio
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pydantic==2.7.1
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# GOT-OCR dependencies
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torch>=2.0.1
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torchvision>=0.15.2
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# Core dependencies
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gradio==5.14.0
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grpcio-status==1.70.0
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markdown==3.7
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multiprocess==0.70.16
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pipdeptree==2.25.0
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Pillow>=9.0.0,<11.0.0
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numpy>=1.21.0
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# PDF processing
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pdf2image>=1.16.0
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# OCR dependencies (for GOT-OCR)
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pytesseract==0.3.13
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tesseract==0.1.3
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tesserocr>=2.5.0; platform_system != "Windows" # Only install on non-Windows systems
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opencv-python-headless>=4.5.0 # Headless version for server environments
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# Utility dependencies
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dill==0.3.8 # Downgraded to be compatible with datasets
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python-dotenv>=1.0.0
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pydantic==2.7.1
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# Gemini API client
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google-genai>=0.1.0
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# GOT-OCR dependencies
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torch>=2.0.1
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torchvision>=0.15.2
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src/core/converter.py
CHANGED
@@ -8,7 +8,7 @@ from pathlib import Path
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from src.core.parser_factory import ParserFactory
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# Import all parsers to ensure they're registered
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import parsers
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# Reference to the cancellation flag from ui.py
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# This will be set by the UI when the cancel button is clicked
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from src.core.parser_factory import ParserFactory
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# Import all parsers to ensure they're registered
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from src import parsers
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# Reference to the cancellation flag from ui.py
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# This will be set by the UI when the cancel button is clicked
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src/parsers/__init__.py
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"""Parser implementations for document conversion."""
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# Import all parsers to ensure they're registered
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from src.parsers.docling_parser import DoclingParser
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from src.parsers.pypdfium_parser import PyPdfiumParser
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from src.parsers.gemini_flash_parser import GeminiFlashParser
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from src.parsers.got_ocr_parser import GotOcrParser
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"""Parser implementations for document conversion."""
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# Import all parsers to ensure they're registered
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from src.parsers.gemini_flash_parser import GeminiFlashParser
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from src.parsers.got_ocr_parser import GotOcrParser
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src/parsers/docling_parser.py
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from pathlib import Path
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from typing import Dict, List, Optional, Any, Union
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import json
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import os
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import shutil
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from src.parsers.parser_interface import DocumentParser
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from src.parsers.parser_registry import ParserRegistry
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from docling.document_converter import DocumentConverter, PdfFormatOption
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.pipeline_options import (
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AcceleratorDevice,
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AcceleratorOptions,
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PdfPipelineOptions,
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)
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from docling.models.tesseract_ocr_model import TesseractOcrOptions
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from docling.models.tesseract_ocr_cli_model import TesseractCliOcrOptions
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class DoclingParser(DocumentParser):
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"""Parser implementation using Docling."""
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@classmethod
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def get_name(cls) -> str:
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return "Docling"
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@classmethod
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def get_supported_ocr_methods(cls) -> List[Dict[str, Any]]:
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return [
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{
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"id": "no_ocr",
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"name": "No OCR",
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"default_params": {}
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},
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{
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"id": "easyocr",
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"name": "EasyOCR",
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"default_params": {"languages": ["en"]}
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},
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{
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"id": "easyocr_cpu",
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"name": "EasyOCR (CPU only)",
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"default_params": {"languages": ["en"], "use_gpu": False}
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},
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{
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"id": "tesseract",
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"name": "Tesseract",
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"default_params": {}
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},
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{
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"id": "tesseract_cli",
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"name": "Tesseract CLI",
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"default_params": {}
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},
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{
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"id": "full_force_ocr",
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"name": "Full Force OCR",
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"default_params": {}
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}
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]
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def parse(self, file_path: Union[str, Path], ocr_method: Optional[str] = None, **kwargs) -> str:
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"""Parse a document using Docling."""
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# Special case for full force OCR
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if ocr_method == "full_force_ocr":
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return self._apply_full_force_ocr(file_path)
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# Regular Docling parsing
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pipeline_options = PdfPipelineOptions()
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pipeline_options.do_table_structure = True
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pipeline_options.table_structure_options.do_cell_matching = True
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# Configure OCR based on the method
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if ocr_method == "no_ocr":
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pipeline_options.do_ocr = False
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elif ocr_method == "easyocr":
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pipeline_options.do_ocr = True
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pipeline_options.ocr_options.lang = kwargs.get("languages", ["en"])
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pipeline_options.accelerator_options = AcceleratorOptions(
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num_threads=4, device=AcceleratorDevice.AUTO
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)
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elif ocr_method == "easyocr_cpu":
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pipeline_options.do_ocr = True
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pipeline_options.ocr_options.lang = kwargs.get("languages", ["en"])
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pipeline_options.ocr_options.use_gpu = False
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elif ocr_method == "tesseract":
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pipeline_options.do_ocr = True
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pipeline_options.ocr_options = TesseractOcrOptions()
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elif ocr_method == "tesseract_cli":
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pipeline_options.do_ocr = True
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pipeline_options.ocr_options = TesseractCliOcrOptions()
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# Create the converter
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converter = DocumentConverter(
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format_options={
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InputFormat.PDF: PdfFormatOption(
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pipeline_options=pipeline_options
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)
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}
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)
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# Convert the document
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result = converter.convert(Path(file_path))
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doc = result.document
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# Return the content in the requested format
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output_format = kwargs.get("output_format", "markdown")
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if output_format.lower() == "json":
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return json.dumps(doc.export_to_dict(), ensure_ascii=False, indent=2)
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elif output_format.lower() == "text":
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return doc.export_to_text()
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elif output_format.lower() == "document_tags":
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return doc.export_to_document_tokens()
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else:
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return doc.export_to_markdown()
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def _apply_full_force_ocr(self, file_path: Union[str, Path]) -> str:
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"""Apply full force OCR to a document."""
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input_doc = Path(file_path)
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file_extension = input_doc.suffix.lower()
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# Debug information
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print(f"Applying full force OCR to file: {input_doc} (type: {file_extension})")
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# Basic pipeline setup
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pipeline_options = PdfPipelineOptions()
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pipeline_options.do_ocr = True
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pipeline_options.do_table_structure = True
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pipeline_options.table_structure_options.do_cell_matching = True
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# Find tesseract executable
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tesseract_path = shutil.which("tesseract") or "/usr/bin/tesseract"
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print(f"Using tesseract at: {tesseract_path}")
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# Configure OCR options
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ocr_options = TesseractCliOcrOptions(force_full_page_ocr=True) # Using standard options instead of CLI
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pipeline_options.ocr_options = ocr_options
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# Set up format options based on file type
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format_options = {
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InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
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}
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# Handle image files
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if file_extension in ['.jpg', '.jpeg', '.png', '.tiff', '.tif', '.bmp']:
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print(f"Processing as image file: {file_extension}")
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format_options[InputFormat.IMAGE] = PdfFormatOption(pipeline_options=pipeline_options)
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# Try full force OCR with standard options
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try:
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converter = DocumentConverter(format_options=format_options)
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result = converter.convert(input_doc)
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return result.document.export_to_markdown()
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except Exception as e:
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print(f"Error with standard OCR: {e}")
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print(f"Attempting fallback to tesseract_cli OCR...")
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return self.parse(file_path, ocr_method="tesseract_cli")
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# Register the parser with the registry
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ParserRegistry.register(DoclingParser)
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src/parsers/pypdfium_parser.py
DELETED
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from pathlib import Path
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from typing import Dict, List, Optional, Any, Union
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import json
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import pypdfium2 as pdfium
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from src.parsers.parser_interface import DocumentParser
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from src.parsers.parser_registry import ParserRegistry
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from docling.document_converter import DocumentConverter, PdfFormatOption
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from docling.datamodel.base_models import InputFormat
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from docling.datamodel.pipeline_options import PdfPipelineOptions
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from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
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class PyPdfiumParser(DocumentParser):
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"""Parser implementation using PyPdfium."""
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@classmethod
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def get_name(cls) -> str:
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return "PyPdfium"
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@classmethod
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def get_supported_ocr_methods(cls) -> List[Dict[str, Any]]:
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return [
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{
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"id": "no_ocr",
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"name": "No OCR",
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"default_params": {}
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},
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{
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"id": "easyocr",
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"name": "EasyOCR",
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"default_params": {"languages": ["en"]}
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}
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]
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def parse(self, file_path: Union[str, Path], ocr_method: Optional[str] = None, **kwargs) -> str:
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"""Parse a document using PyPdfium."""
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pipeline_options = PdfPipelineOptions()
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pipeline_options.do_table_structure = True
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pipeline_options.table_structure_options.do_cell_matching = True
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-
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# Configure OCR based on the method
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if ocr_method == "easyocr":
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pipeline_options.do_ocr = True
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# Apply any custom parameters from kwargs
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if "languages" in kwargs:
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pipeline_options.ocr_options.lang = kwargs["languages"]
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else:
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pipeline_options.do_ocr = False
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# Create the converter
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converter = DocumentConverter(
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format_options={
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InputFormat.PDF: PdfFormatOption(
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pipeline_options=pipeline_options,
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backend=PyPdfiumDocumentBackend
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)
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}
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)
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# Convert the document
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result = converter.convert(Path(file_path))
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doc = result.document
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# Return the content in the requested format
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output_format = kwargs.get("output_format", "markdown")
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if output_format.lower() == "json":
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return json.dumps(doc.export_to_dict(), ensure_ascii=False, indent=2)
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elif output_format.lower() == "text":
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return doc.export_to_text()
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elif output_format.lower() == "document_tags":
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return doc.export_to_document_tokens()
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else:
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return doc.export_to_markdown()
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# Register the parser with the registry
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ParserRegistry.register(PyPdfiumParser)
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