docling/docs/examples/develop_formula_understanding.py
Michele Dolfi 5458a88464
ci: add coverage and ruff (#1383)
* add coverage calculation and push

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* new codecov version and usage of token

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* enable ruff formatter instead of black and isort

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* apply ruff lint fixes

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* apply ruff unsafe fixes

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* add removed imports

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* runs 1 on linter issues

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* finalize linter fixes

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>

* Update pyproject.toml

Co-authored-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com>
Signed-off-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>

---------

Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Signed-off-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>
Co-authored-by: Cesar Berrospi Ramis <75900930+ceberam@users.noreply.github.com>
2025-04-14 18:01:26 +02:00

92 lines
3.0 KiB
Python

# 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()