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This commit is contained in:
Christoph Auer
351
docling/datamodel/document.py
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351
docling/datamodel/document.py
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import logging
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from io import BytesIO
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from pathlib import Path, PurePath
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from typing import ClassVar, Dict, Iterable, List, Optional, Type, Union
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from deepsearch.documents.core.export import export_to_markdown
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from docling_core.types import BaseCell, BaseText
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from docling_core.types import BoundingBox as DsBoundingBox
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from docling_core.types import Document as DsDocument
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from docling_core.types import DocumentDescription as DsDocumentDescription
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from docling_core.types import FileInfoObject as DsFileInfoObject
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from docling_core.types import PageDimensions, PageReference, Prov, Ref
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from docling_core.types import Table as DsSchemaTable
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from docling_core.types import TableCell
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from pydantic import BaseModel
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from docling.backend.abstract_backend import PdfDocumentBackend
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from docling.backend.pypdfium2_backend import PyPdfiumDocumentBackend
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from docling.datamodel.base_models import (
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AssembledUnit,
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ConversionStatus,
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DocumentStream,
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FigureElement,
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Page,
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TableElement,
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TextElement,
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)
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from docling.datamodel.settings import DocumentLimits
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from docling.utils.utils import create_file_hash
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_log = logging.getLogger(__name__)
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layout_label_to_ds_type = {
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"Title": "title",
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"Document Index": "table-of-path_or_stream",
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"Section-header": "subtitle-level-1",
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"Checkbox-Selected": "checkbox-selected",
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"Checkbox-Unselected": "checkbox-unselected",
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"Caption": "caption",
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"Page-header": "page-header",
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"Page-footer": "page-footer",
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"Footnote": "footnote",
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"Table": "table",
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"Formula": "equation",
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"List-item": "paragraph",
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"Code": "paragraph",
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"Picture": "figure",
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"Text": "paragraph",
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}
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class InputDocument(BaseModel):
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file: PurePath = None
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document_hash: Optional[str] = None
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valid: bool = False
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limits: DocumentLimits = DocumentLimits()
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filesize: Optional[int] = None
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page_count: Optional[int] = None
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_backend: PdfDocumentBackend = None # Internal PDF backend used
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def __init__(
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self,
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path_or_stream: Union[BytesIO, Path],
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filename: Optional[str] = None,
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limits: Optional[DocumentLimits] = None,
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pdf_backend=PyPdfiumDocumentBackend,
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):
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super().__init__()
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self.limits = limits or DocumentLimits()
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try:
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if isinstance(path_or_stream, Path):
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self.file = path_or_stream
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self.filesize = path_or_stream.stat().st_size
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if self.filesize > self.limits.max_file_size:
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self.valid = False
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else:
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self.document_hash = create_file_hash(path_or_stream)
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self._backend = pdf_backend(path_or_stream=path_or_stream)
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elif isinstance(path_or_stream, BytesIO):
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self.file = PurePath(filename)
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self.filesize = path_or_stream.getbuffer().nbytes
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if self.filesize > self.limits.max_file_size:
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self.valid = False
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else:
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self.document_hash = create_file_hash(path_or_stream)
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self._backend = pdf_backend(path_or_stream=path_or_stream)
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if self.document_hash and self._backend.page_count() > 0:
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self.page_count = self._backend.page_count()
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if self.page_count <= self.limits.max_num_pages:
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self.valid = True
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except (FileNotFoundError, OSError) as e:
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_log.exception(
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f"File {self.file.name} not found or cannot be opened.", exc_info=e
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)
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# raise
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except RuntimeError as e:
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_log.exception(
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f"An unexpected error occurred while opening the document {self.file.name}",
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exc_info=e,
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)
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# raise
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class ConvertedDocument(BaseModel):
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input: InputDocument
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status: ConversionStatus = ConversionStatus.PENDING # failure, success
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errors: List[Dict] = [] # structure to keep errors
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pages: List[Page] = []
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assembled: AssembledUnit = None
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output: DsDocument = None
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def to_ds_document(self) -> DsDocument:
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title = ""
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desc = DsDocumentDescription(logs=[])
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page_hashes = [
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PageReference(hash=p.page_hash, page=p.page_no, model="default")
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for p in self.pages
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]
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file_info = DsFileInfoObject(
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filename=self.input.file.name,
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document_hash=self.input.document_hash,
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num_pages=self.input.page_count,
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page_hashes=page_hashes,
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)
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main_text = []
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tables = []
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figures = []
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page_no_to_page = {p.page_no: p for p in self.pages}
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for element in self.assembled.elements:
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# Convert bboxes to lower-left origin.
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target_bbox = DsBoundingBox(
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element.cluster.bbox.to_bottom_left_origin(
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page_no_to_page[element.page_no].size.height
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).as_tuple()
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)
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if isinstance(element, TextElement):
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main_text.append(
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BaseText(
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text=element.text,
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obj_type=layout_label_to_ds_type.get(element.label),
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name=element.label,
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prov=[
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Prov(
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bbox=target_bbox,
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page=element.page_no,
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span=[0, len(element.text)],
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)
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],
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)
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)
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elif isinstance(element, TableElement):
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index = len(tables)
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ref_str = f"#/tables/{index}"
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main_text.append(
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Ref(
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name=element.label,
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obj_type=layout_label_to_ds_type.get(element.label),
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ref=ref_str,
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),
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)
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# Initialise empty table data grid (only empty cells)
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table_data = [
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[
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TableCell(
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text="",
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# bbox=[0,0,0,0],
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spans=[[i, j]],
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obj_type="body",
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)
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for j in range(element.num_cols)
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]
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for i in range(element.num_rows)
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]
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# Overwrite cells in table data for which there is actual cell content.
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for cell in element.table_cells:
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for i in range(
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min(cell.start_row_offset_idx, element.num_rows),
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min(cell.end_row_offset_idx, element.num_rows),
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):
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for j in range(
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min(cell.start_col_offset_idx, element.num_cols),
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min(cell.end_col_offset_idx, element.num_cols),
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):
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celltype = "body"
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if cell.column_header:
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celltype = "col_header"
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elif cell.row_header:
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celltype = "row_header"
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def make_spans(cell):
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for rspan in range(
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min(cell.start_row_offset_idx, element.num_rows),
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min(cell.end_row_offset_idx, element.num_rows),
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):
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for cspan in range(
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min(
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cell.start_col_offset_idx, element.num_cols
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),
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min(cell.end_col_offset_idx, element.num_cols),
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):
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yield [rspan, cspan]
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spans = list(make_spans(cell))
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table_data[i][j] = TableCell(
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text=cell.text,
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bbox=cell.bbox.to_bottom_left_origin(
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page_no_to_page[element.page_no].size.height
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).as_tuple(),
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# col=j,
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# row=i,
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spans=spans,
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obj_type=celltype,
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# col_span=[cell.start_col_offset_idx, cell.end_col_offset_idx],
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# row_span=[cell.start_row_offset_idx, cell.end_row_offset_idx]
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)
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tables.append(
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DsSchemaTable(
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num_cols=element.num_cols,
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num_rows=element.num_rows,
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obj_type=layout_label_to_ds_type.get(element.label),
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data=table_data,
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prov=[
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Prov(
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bbox=target_bbox,
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page=element.page_no,
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span=[0, 0],
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)
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],
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)
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)
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elif isinstance(element, FigureElement):
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index = len(figures)
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ref_str = f"#/figures/{index}"
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main_text.append(
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Ref(
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name=element.label,
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obj_type=layout_label_to_ds_type.get(element.label),
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ref=ref_str,
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),
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)
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figures.append(
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BaseCell(
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prov=[
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Prov(
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bbox=target_bbox,
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page=element.page_no,
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span=[0, 0],
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)
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],
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obj_type=layout_label_to_ds_type.get(element.label),
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# data=[[]],
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)
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)
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page_dimensions = [
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PageDimensions(page=p.page_no, height=p.size.height, width=p.size.width)
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for p in self.pages
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]
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ds_doc = DsDocument(
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name=title,
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description=desc,
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file_info=file_info,
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main_text=main_text,
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tables=tables,
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figures=figures,
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page_dimensions=page_dimensions,
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)
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return ds_doc
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def render_as_dict(self):
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if self.output:
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return self.output.model_dump(by_alias=True, exclude_none=True)
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else:
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return {}
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def render_as_markdown(self):
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if self.output:
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return export_to_markdown(
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self.output.model_dump(by_alias=True, exclude_none=True)
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)
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else:
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return ""
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class DocumentConversionInput(BaseModel):
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_path_or_stream_iterator: Iterable[Union[Path, DocumentStream]] = None
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limits: Optional[DocumentLimits] = DocumentLimits()
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DEFAULT_BACKEND: ClassVar = PyPdfiumDocumentBackend
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def docs(
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self, pdf_backend: Optional[Type[PdfDocumentBackend]] = None
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) -> Iterable[InputDocument]:
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pdf_backend = pdf_backend or DocumentConversionInput.DEFAULT_BACKEND
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for obj in self._path_or_stream_iterator:
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if isinstance(obj, Path):
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yield InputDocument(
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path_or_stream=obj, limits=self.limits, pdf_backend=pdf_backend
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)
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elif isinstance(obj, DocumentStream):
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yield InputDocument(
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path_or_stream=obj.stream,
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filename=obj.filename,
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limits=self.limits,
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pdf_backend=pdf_backend,
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)
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@classmethod
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def from_paths(cls, paths: Iterable[Path], limits: Optional[DocumentLimits] = None):
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paths = [Path(p) for p in paths]
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doc_input = cls(limits=limits)
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doc_input._path_or_stream_iterator = paths
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return doc_input
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@classmethod
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def from_streams(
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cls, streams: Iterable[DocumentStream], limits: Optional[DocumentLimits] = None
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):
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doc_input = cls(limits=limits)
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doc_input._path_or_stream_iterator = streams
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return doc_input
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