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Docling can convert PDFs to readable Markdown or structured JSON, with options for table reconstruction, OCR, and reading-order handling. Use Markdown when people will read the result; choose JSON when software needs to inspect document elements and their sequence. Table and reading-order results depend on the PDF’s layout, so validate representative pages against the original.
Convert a PDF with Docling
Docling’s PDF support includes layout, reading order, and table understanding. The quickest way to try it is the command-line interface:
docling convert report.pdf --to mdThis writes Markdown output. To request structured JSON instead, use:
docling convert report.pdf --to jsonBoth formats come from Docling’s document representation; they differ in how you consume the result. See the Docling homepage for the command examples and supported formats.
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Choose Markdown or JSON
| Output | Best suited to | What it gives you |
|---|---|---|
| Markdown | Human-readable results, documentation, or review | Readable text with tables rendered in Markdown form. |
| JSON | Programmatic processing or inspection of document structure | Structured elements, including text, tables, pictures, key-value items, and a body tree. |
For downstream code, JSON is useful because DoclingDocument represents more than a flat text string. Its body tree preserves hierarchy and sequence: the concept documentation says, “The reading order of the document is encapsulated through the body tree and the order of children in each item in the tree.” See DoclingDocument concepts.
Extract tables and choose a table mode
Table structure extraction is controlled by the PDF pipeline option do_table_structure. In Python, configure a converter with DocumentConverter, PdfFormatOption, and PdfPipelineOptions; the official examples show enabling table extraction and exporting Markdown:
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from docling.document_converter import DocumentConverter, PdfFormatOption
from docling.datamodel.base_models import InputFormat
from docling.datamodel.pipeline_options import PdfPipelineOptions
pipeline_options = PdfPipelineOptions()
pipeline_options.do_table_structure = True
converter = DocumentConverter(
format_options={
InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)
}
)
result = converter.convert("report.pdf")
markdown = result.document.export_to_markdown()
print(markdown)Docling’s examples describe a faster approximate table mode and an accurate mode using TableFormer for complex tables, including merged cells. The choice is a trade-off between processing needs and table complexity, not a universal guarantee about the result. Check the official examples and PDF pipeline options for the current configuration details.
Validate reconstructed tables
Compare extracted output with the source page, especially when a table has:
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- Headers that span columns or rows
- Merged cells or irregular row boundaries
- Captions or explanatory text positioned close to the table
Confirm that rows and columns retain their intended relationships and that captions have not been absorbed into table content or detached from it. Treat this as a document-specific check; the documentation does not establish a general extraction-accuracy rate.
Preserve and inspect reading order
In JSON, inspect the body tree and the order of its child items to understand Docling’s represented reading sequence. The model also distinguishes page furniture, such as headers and footers, from the main body. Markdown can be useful for a quick visual review, while JSON exposes the hierarchy directly.
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For PDFs with visible horizontal or vertical rules, the reading-order stage can use those rules as structural signals when the PDF backend exposes their geometry. This behavior is enabled by default. Advanced options document how to disable it in Python or through the CLI flag --no-reading-order-separators. See advanced options and the pipeline options reference.
Review pages where order is ambiguous
- Multi-column layouts, where lines from adjacent columns can be interleaved.
- Ruled sections, where visible lines may affect how content is grouped.
- Headers and footers, which should be distinguished from the main text.
- Transitions between tables and surrounding paragraphs or captions.
Inspect representative pages in the JSON hierarchy or rendered Markdown and compare them with the PDF. Docling documents the representation and controls, but does not claim that every layout will be read in the intended order without review.
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Use OCR for image-only PDFs
OCR is relevant when a PDF contains scanned pages or images without a usable text layer. The documented full-page example is:
docling convert scan.pdf --ocr-mode full_page --to mdOCR adds processing time. If a PDF was generated digitally and already has an embedded text layer, check whether OCR is needed rather than enabling it automatically. The pipeline options reference describes OCR for scanned or image-based documents; the homepage shows the full-page command example.
Quick Recap
Choose settings based on the PDF
- Output purpose: Markdown for a readable deliverable; JSON when downstream software needs structured elements and reading order.
- Table complexity: Use the faster approximate mode where suitable; consider the accurate TableFormer mode for complex or merged-cell tables, then verify the output.
- Source condition: Use OCR for scanned or image-based pages; first check digital PDFs for an existing text layer.
- Page structure: Keep reading-order separators enabled when visible rules may help, or disable them if your workflow requires that behavior.
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