docling/docs/examples/minimal_smol_docling.py
2025-02-24 12:56:56 +01:00

54 lines
1.4 KiB
Python

from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
from docling.datamodel.base_models import InputFormat
from docling.datamodel.pipeline_options import PdfPipelineOptions
from docling.document_converter import DocumentConverter, PdfFormatOption
from docling.pipeline.vlm_pipeline import VlmPipeline
# source = "https://arxiv.org/pdf/2408.09869" # document per local path or URL
# source = "tests/data/2305.03393v1-pg9-img.png"
source = "tests/data/2305.03393v1-pg9.pdf"
pipeline_options = PdfPipelineOptions()
pipeline_options.artifacts_path = "model_artifacts"
converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(
pipeline_cls=VlmPipeline,
pipeline_options=pipeline_options,
backend=DoclingParseDocumentBackend,
),
InputFormat.IMAGE: PdfFormatOption(
pipeline_cls=VlmPipeline,
pipeline_options=pipeline_options,
backend=DoclingParseDocumentBackend,
),
}
)
print("============")
print("starting...")
print("============")
print("")
result = converter.convert(source)
print("------------")
print("result:")
print("------------")
print("")
print(result)
print("------------")
print("MD:")
print("------------")
print("")
print(result.document.export_to_markdown())
print("")
print("============")
print("done!")
print("============")
# output: ## Docling Technical Report [...]"