perf: prevent temp file leftovers, reuse core type (#487)
* chore: reuse DocumentStream from docling-core Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com> * update docling-core version Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com> * [skip ci] document import line Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com> * fix: use new resolve_source_to_x functions to avoid tempfile leftovers (#490) use new resolve_source_to_x functions Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> --------- Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com> Signed-off-by: Michele Dolfi <dol@zurich.ibm.com> Co-authored-by: Michele Dolfi <97102151+dolfim-ibm@users.noreply.github.com>
This commit is contained in:
Panos Vagenas
GitHub
parent
d3f84b2457
commit
051789d017
@ -2,6 +2,7 @@ import importlib
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import json
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import logging
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import re
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import tempfile
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import time
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import warnings
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from enum import Enum
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@ -9,7 +10,7 @@ from pathlib import Path
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from typing import Annotated, Dict, Iterable, List, Optional, Type
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import typer
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from docling_core.utils.file import resolve_file_source
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from docling_core.utils.file import resolve_source_to_path
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from docling.backend.docling_parse_backend import DoclingParseDocumentBackend
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from docling.backend.docling_parse_v2_backend import DoclingParseV2DocumentBackend
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@ -256,95 +257,98 @@ def convert(
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if from_formats is None:
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from_formats = [e for e in InputFormat]
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input_doc_paths: List[Path] = []
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for src in input_sources:
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source = resolve_file_source(source=src)
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if not source.exists():
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err_console.print(
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f"[red]Error: The input file {source} does not exist.[/red]"
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)
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raise typer.Abort()
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elif source.is_dir():
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for fmt in from_formats:
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for ext in FormatToExtensions[fmt]:
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input_doc_paths.extend(list(source.glob(f"**/*.{ext}")))
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input_doc_paths.extend(list(source.glob(f"**/*.{ext.upper()}")))
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with tempfile.TemporaryDirectory() as tempdir:
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input_doc_paths: List[Path] = []
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for src in input_sources:
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source = resolve_source_to_path(source=src, workdir=Path(tempdir))
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if not source.exists():
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err_console.print(
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f"[red]Error: The input file {source} does not exist.[/red]"
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)
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raise typer.Abort()
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elif source.is_dir():
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for fmt in from_formats:
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for ext in FormatToExtensions[fmt]:
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input_doc_paths.extend(list(source.glob(f"**/*.{ext}")))
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input_doc_paths.extend(list(source.glob(f"**/*.{ext.upper()}")))
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else:
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input_doc_paths.append(source)
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if to_formats is None:
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to_formats = [OutputFormat.MARKDOWN]
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export_json = OutputFormat.JSON in to_formats
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export_md = OutputFormat.MARKDOWN in to_formats
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export_txt = OutputFormat.TEXT in to_formats
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export_doctags = OutputFormat.DOCTAGS in to_formats
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if ocr_engine == OcrEngine.EASYOCR:
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ocr_options: OcrOptions = EasyOcrOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.TESSERACT_CLI:
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ocr_options = TesseractCliOcrOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.TESSERACT:
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ocr_options = TesseractOcrOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.OCRMAC:
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ocr_options = OcrMacOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.RAPIDOCR:
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ocr_options = RapidOcrOptions(force_full_page_ocr=force_ocr)
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else:
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input_doc_paths.append(source)
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raise RuntimeError(f"Unexpected OCR engine type {ocr_engine}")
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if to_formats is None:
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to_formats = [OutputFormat.MARKDOWN]
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ocr_lang_list = _split_list(ocr_lang)
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if ocr_lang_list is not None:
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ocr_options.lang = ocr_lang_list
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export_json = OutputFormat.JSON in to_formats
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export_md = OutputFormat.MARKDOWN in to_formats
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export_txt = OutputFormat.TEXT in to_formats
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export_doctags = OutputFormat.DOCTAGS in to_formats
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if ocr_engine == OcrEngine.EASYOCR:
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ocr_options: OcrOptions = EasyOcrOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.TESSERACT_CLI:
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ocr_options = TesseractCliOcrOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.TESSERACT:
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ocr_options = TesseractOcrOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.OCRMAC:
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ocr_options = OcrMacOptions(force_full_page_ocr=force_ocr)
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elif ocr_engine == OcrEngine.RAPIDOCR:
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ocr_options = RapidOcrOptions(force_full_page_ocr=force_ocr)
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else:
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raise RuntimeError(f"Unexpected OCR engine type {ocr_engine}")
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ocr_lang_list = _split_list(ocr_lang)
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if ocr_lang_list is not None:
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ocr_options.lang = ocr_lang_list
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pipeline_options = PdfPipelineOptions(
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do_ocr=ocr,
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ocr_options=ocr_options,
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do_table_structure=True,
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)
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pipeline_options.table_structure_options.do_cell_matching = True # do_cell_matching
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pipeline_options.table_structure_options.mode = table_mode
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if artifacts_path is not None:
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pipeline_options.artifacts_path = artifacts_path
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if pdf_backend == PdfBackend.DLPARSE_V1:
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backend: Type[PdfDocumentBackend] = DoclingParseDocumentBackend
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elif pdf_backend == PdfBackend.DLPARSE_V2:
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backend = DoclingParseV2DocumentBackend
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elif pdf_backend == PdfBackend.PYPDFIUM2:
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backend = PyPdfiumDocumentBackend
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else:
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raise RuntimeError(f"Unexpected PDF backend type {pdf_backend}")
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format_options: Dict[InputFormat, FormatOption] = {
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InputFormat.PDF: PdfFormatOption(
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pipeline_options=pipeline_options,
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backend=backend, # pdf_backend
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pipeline_options = PdfPipelineOptions(
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do_ocr=ocr,
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ocr_options=ocr_options,
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do_table_structure=True,
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)
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}
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doc_converter = DocumentConverter(
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allowed_formats=from_formats,
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format_options=format_options,
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)
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pipeline_options.table_structure_options.do_cell_matching = (
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True # do_cell_matching
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)
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pipeline_options.table_structure_options.mode = table_mode
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start_time = time.time()
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if artifacts_path is not None:
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pipeline_options.artifacts_path = artifacts_path
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conv_results = doc_converter.convert_all(
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input_doc_paths, raises_on_error=abort_on_error
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)
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if pdf_backend == PdfBackend.DLPARSE_V1:
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backend: Type[PdfDocumentBackend] = DoclingParseDocumentBackend
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elif pdf_backend == PdfBackend.DLPARSE_V2:
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backend = DoclingParseV2DocumentBackend
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elif pdf_backend == PdfBackend.PYPDFIUM2:
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backend = PyPdfiumDocumentBackend
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else:
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raise RuntimeError(f"Unexpected PDF backend type {pdf_backend}")
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output.mkdir(parents=True, exist_ok=True)
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export_documents(
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conv_results,
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output_dir=output,
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export_json=export_json,
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export_md=export_md,
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export_txt=export_txt,
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export_doctags=export_doctags,
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)
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format_options: Dict[InputFormat, FormatOption] = {
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InputFormat.PDF: PdfFormatOption(
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pipeline_options=pipeline_options,
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backend=backend, # pdf_backend
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)
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}
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doc_converter = DocumentConverter(
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allowed_formats=from_formats,
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format_options=format_options,
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)
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end_time = time.time() - start_time
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start_time = time.time()
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conv_results = doc_converter.convert_all(
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input_doc_paths, raises_on_error=abort_on_error
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)
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output.mkdir(parents=True, exist_ok=True)
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export_documents(
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conv_results,
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output_dir=output,
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export_json=export_json,
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export_md=export_md,
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export_txt=export_txt,
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export_doctags=export_doctags,
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)
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end_time = time.time() - start_time
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_log.info(f"All documents were converted in {end_time:.2f} seconds.")
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@ -1,5 +1,4 @@
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from enum import Enum, auto
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from io import BytesIO
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from typing import TYPE_CHECKING, Dict, List, Optional, Union
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from docling_core.types.doc import (
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@ -9,6 +8,9 @@ from docling_core.types.doc import (
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Size,
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TableCell,
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)
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from docling_core.types.io import ( # DO ΝΟΤ REMOVE; explicitly exposed from this location
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DocumentStream,
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)
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from PIL.Image import Image
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from pydantic import BaseModel, ConfigDict
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@ -207,10 +209,3 @@ class Page(BaseModel):
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@property
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def image(self) -> Optional[Image]:
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return self.get_image(scale=self._default_image_scale)
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class DocumentStream(BaseModel):
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model_config = ConfigDict(arbitrary_types_allowed=True)
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name: str
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stream: BytesIO
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@ -32,7 +32,7 @@ from docling_core.types.legacy_doc.document import (
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)
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from docling_core.types.legacy_doc.document import CCSFileInfoObject as DsFileInfoObject
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from docling_core.types.legacy_doc.document import ExportedCCSDocument as DsDocument
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from docling_core.utils.file import resolve_file_source
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from docling_core.utils.file import resolve_source_to_stream
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from pydantic import BaseModel
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from typing_extensions import deprecated
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@ -459,7 +459,7 @@ class _DocumentConversionInput(BaseModel):
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self, format_options: Dict[InputFormat, "FormatOption"]
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) -> Iterable[InputDocument]:
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for item in self.path_or_stream_iterator:
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obj = resolve_file_source(item) if isinstance(item, str) else item
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obj = resolve_source_to_stream(item) if isinstance(item, str) else item
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format = self._guess_format(obj)
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if format not in format_options.keys():
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_log.info(
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15
poetry.lock
generated
15
poetry.lock
generated
@ -896,13 +896,13 @@ files = [
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[[package]]
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name = "docling-core"
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version = "2.5.1"
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version = "2.6.1"
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description = "A python library to define and validate data types in Docling."
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optional = false
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python-versions = "<4.0,>=3.9"
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files = [
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{file = "docling_core-2.5.1-py3-none-any.whl", hash = "sha256:e4a5626520714c25a5ec2f9f7495407e730485257c2272e8467faae7357435bf"},
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{file = "docling_core-2.5.1.tar.gz", hash = "sha256:e9a7c7c46f869b13747436a2ce42df3632af655e1a3af574dfcd114e71dcbb75"},
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{file = "docling_core-2.6.1-py3-none-any.whl", hash = "sha256:8e7a5bc0ce13289567738481949fed3ab580f2d8cea7525b246159233d81b26b"},
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{file = "docling_core-2.6.1.tar.gz", hash = "sha256:c8af45e0873611120cc24757d567d37e053a54e2ce060b7b5b44efd0d73f75e5"},
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]
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[package.dependencies]
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@ -913,6 +913,7 @@ pillow = ">=10.3.0,<11.0.0"
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pydantic = ">=2.6.0,<2.10"
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pyyaml = ">=5.1,<7.0.0"
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tabulate = ">=0.9.0,<0.10.0"
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typing-extensions = ">=4.12.2,<5.0.0"
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[[package]]
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name = "docling-ibm-models"
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@ -3200,6 +3201,7 @@ files = [
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{file = "nh3-0.2.19-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:00810cd5275f5c3f44b9eb0e521d1a841ee2f8023622de39ffc7d88bd533d8e0"},
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{file = "nh3-0.2.19-cp38-abi3-win32.whl", hash = "sha256:7e98621856b0a911c21faa5eef8f8ea3e691526c2433f9afc2be713cb6fbdb48"},
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{file = "nh3-0.2.19-cp38-abi3-win_amd64.whl", hash = "sha256:75c7cafb840f24430b009f7368945cb5ca88b2b54bb384ebfba495f16bc9c121"},
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{file = "nh3-0.2.19.tar.gz", hash = "sha256:790056b54c068ff8dceb443eaefb696b84beff58cca6c07afd754d17692a4804"},
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]
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[[package]]
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@ -6028,6 +6030,11 @@ files = [
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{file = "scikit_learn-1.5.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f60021ec1574e56632be2a36b946f8143bf4e5e6af4a06d85281adc22938e0dd"},
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{file = "scikit_learn-1.5.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:394397841449853c2290a32050382edaec3da89e35b3e03d6cc966aebc6a8ae6"},
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{file = "scikit_learn-1.5.2-cp312-cp312-win_amd64.whl", hash = "sha256:57cc1786cfd6bd118220a92ede80270132aa353647684efa385a74244a41e3b1"},
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{file = "scikit_learn-1.5.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:e9a702e2de732bbb20d3bad29ebd77fc05a6b427dc49964300340e4c9328b3f5"},
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{file = "scikit_learn-1.5.2-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:b0768ad641981f5d3a198430a1d31c3e044ed2e8a6f22166b4d546a5116d7908"},
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{file = "scikit_learn-1.5.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:178ddd0a5cb0044464fc1bfc4cca5b1833bfc7bb022d70b05db8530da4bb3dd3"},
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{file = "scikit_learn-1.5.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f7284ade780084d94505632241bf78c44ab3b6f1e8ccab3d2af58e0e950f9c12"},
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{file = "scikit_learn-1.5.2-cp313-cp313-win_amd64.whl", hash = "sha256:b7b0f9a0b1040830d38c39b91b3a44e1b643f4b36e36567b80b7c6bd2202a27f"},
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{file = "scikit_learn-1.5.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:757c7d514ddb00ae249832fe87100d9c73c6ea91423802872d9e74970a0e40b9"},
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{file = "scikit_learn-1.5.2-cp39-cp39-macosx_12_0_arm64.whl", hash = "sha256:52788f48b5d8bca5c0736c175fa6bdaab2ef00a8f536cda698db61bd89c551c1"},
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{file = "scikit_learn-1.5.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:643964678f4b5fbdc95cbf8aec638acc7aa70f5f79ee2cdad1eec3df4ba6ead8"},
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@ -7646,4 +7653,4 @@ tesserocr = ["tesserocr"]
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[metadata]
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lock-version = "2.0"
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python-versions = "^3.9"
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content-hash = "2e7c27ffe32d556a66cc1008a7147a90c17f63b01d2a6cde3e7b941ba7e268d7"
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content-hash = "ee3b3d938295f0057567c10fb808a0d95ed2fe9a32f459d489b4b29aacf710c8"
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@ -26,7 +26,7 @@ packages = [{include = "docling"}]
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######################
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python = "^3.9"
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pydantic = ">=2.0.0,<2.10"
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docling-core = "^2.5.1"
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docling-core = "^2.6.1"
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docling-ibm-models = "^2.0.6"
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deepsearch-glm = "^0.26.1"
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filetype = "^1.2.0"
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