Docling/examples/batch_convert.py
Christoph Auer a8c6b29a67
feat: Upgrade docling-parse PDF backend and interface to use page-by-page parsing (#44)
* Use docling-parse page-by-page

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Propagate document_hash to PDF backends, use docling-parse 1.0.0

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Upgrade lockfile

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* repin after more packages on pypi

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

---------

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>
Signed-off-by: Michele Dolfi <dol@zurich.ibm.com>
Co-authored-by: Michele Dolfi <dol@zurich.ibm.com>
2024-08-22 13:49:37 +02:00

80 lines
2.2 KiB
Python

import json
import logging
import time
from io import BytesIO
from pathlib import Path
from typing import Iterable
from docling.datamodel.base_models import (
ConversionStatus,
DocumentStream,
PipelineOptions,
)
from docling.datamodel.document import ConvertedDocument, DocumentConversionInput
from docling.document_converter import DocumentConverter
_log = logging.getLogger(__name__)
def export_documents(
converted_docs: Iterable[ConvertedDocument],
output_dir: Path,
):
output_dir.mkdir(parents=True, exist_ok=True)
success_count = 0
failure_count = 0
for doc in converted_docs:
if doc.status == ConversionStatus.SUCCESS:
success_count += 1
doc_filename = doc.input.file.stem
# Export Deep Search document JSON format:
with (output_dir / f"{doc_filename}.json").open("w") as fp:
fp.write(json.dumps(doc.render_as_dict()))
# Export Markdown format:
with (output_dir / f"{doc_filename}.md").open("w") as fp:
fp.write(doc.render_as_markdown())
else:
_log.info(f"Document {doc.input.file} failed to convert.")
failure_count += 1
_log.info(
f"Processed {success_count + failure_count} docs, of which {failure_count} failed"
)
def main():
logging.basicConfig(level=logging.INFO)
input_doc_paths = [
Path("./test/data/2206.01062.pdf"),
Path("./test/data/2203.01017v2.pdf"),
Path("./test/data/2305.03393v1.pdf"),
Path("./test/data/redp5110.pdf"),
Path("./test/data/redp5695.pdf"),
]
# buf = BytesIO(Path("./test/data/2206.01062.pdf").open("rb").read())
# docs = [DocumentStream(filename="my_doc.pdf", stream=buf)]
# input = DocumentConversionInput.from_streams(docs)
doc_converter = DocumentConverter(pipeline_options=PipelineOptions(do_ocr=False))
input = DocumentConversionInput.from_paths(input_doc_paths)
start_time = time.time()
converted_docs = doc_converter.convert(input)
export_documents(converted_docs, output_dir=Path("./scratch"))
end_time = time.time() - start_time
_log.info(f"All documents were converted in {end_time:.2f} seconds.")
if __name__ == "__main__":
main()