# WARNING # This example demonstrates only how to develop a new enrichment model. # It does not run the actual formula understanding model. import logging from collections.abc import Iterable from pathlib import Path from docling_core.types.doc import DocItemLabel, DoclingDocument, NodeItem, TextItem from docling.datamodel.base_models import InputFormat, ItemAndImageEnrichmentElement from docling.datamodel.pipeline_options import PdfPipelineOptions from docling.document_converter import DocumentConverter, PdfFormatOption from docling.models.base_model import BaseItemAndImageEnrichmentModel from docling.pipeline.standard_pdf_pipeline import StandardPdfPipeline class ExampleFormulaUnderstandingPipelineOptions(PdfPipelineOptions): do_formula_understanding: bool = True # A new enrichment model using both the document element and its image as input class ExampleFormulaUnderstandingEnrichmentModel(BaseItemAndImageEnrichmentModel): images_scale = 2.6 def __init__(self, enabled: bool): self.enabled = enabled def is_processable(self, doc: DoclingDocument, element: NodeItem) -> bool: return ( self.enabled and isinstance(element, TextItem) and element.label == DocItemLabel.FORMULA ) def __call__( self, doc: DoclingDocument, element_batch: Iterable[ItemAndImageEnrichmentElement], ) -> Iterable[NodeItem]: if not self.enabled: return for enrich_element in element_batch: enrich_element.image.show() yield enrich_element.item # How the pipeline can be extended. class ExampleFormulaUnderstandingPipeline(StandardPdfPipeline): def __init__(self, pipeline_options: ExampleFormulaUnderstandingPipelineOptions): super().__init__(pipeline_options) self.pipeline_options: ExampleFormulaUnderstandingPipelineOptions self.enrichment_pipe = [ ExampleFormulaUnderstandingEnrichmentModel( enabled=self.pipeline_options.do_formula_understanding ) ] if self.pipeline_options.do_formula_understanding: self.keep_backend = True @classmethod def get_default_options(cls) -> ExampleFormulaUnderstandingPipelineOptions: return ExampleFormulaUnderstandingPipelineOptions() # Example main. In the final version, we simply have to set do_formula_understanding to true. def main(): logging.basicConfig(level=logging.INFO) input_doc_path = Path("./tests/data/pdf/2203.01017v2.pdf") pipeline_options = ExampleFormulaUnderstandingPipelineOptions() pipeline_options.do_formula_understanding = True doc_converter = DocumentConverter( format_options={ InputFormat.PDF: PdfFormatOption( pipeline_cls=ExampleFormulaUnderstandingPipeline, pipeline_options=pipeline_options, ) } ) doc_converter.convert(input_doc_path) if __name__ == "__main__": main()