Docling simplifies document processing, parsing diverse formats — including advanced PDF understanding — and providing seamless integrations with the gen AI ecosystem.
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Signed-off-by: Abhishek Kumar <abhishekrocketeer@gmail.com> Testing: (.venv) mario@Abhisheks-MacBook-Air docling % docling https://arxiv.org/pdf/2206.01062 --document-timeout=10 --verbose INFO:docling.document_converter:Going to convert document batch... INFO:docling.pipeline.base_pipeline:Processing document 2206.01062v1.pdf WARNING:docling.pipeline.base_pipeline:Document processing time (24.555 seconds) exceeded the specified timeout of 10.000 seconds INFO:docling.document_converter:Finished converting document 2206.01062v1.pdf in 36.29 sec. WARNING:docling.cli.main:Document /var/folders/d7/dsfkllxs0xs8x2t4fcjknj4c0000gn/T/tmpl6p08u5i/2206.01062v1.pdf failed to convert. INFO:docling.cli.main:Processed 1 docs, of which 1 failed INFO:docling.cli.main:All documents were converted in 36.29 seconds. (.venv) mario@Abhisheks-MacBook-Air docling % docling https://arxiv.org/pdf/2206.01062 --document-timeout=100 --verbose INFO:docling.document_converter:Going to convert document batch... INFO:docling.pipeline.base_pipeline:Processing document 2206.01062v1.pdf INFO:docling.document_converter:Finished converting document 2206.01062v1.pdf in 58.36 sec. INFO:docling.cli.main:writing Markdown output to 2206.01062v1.md INFO:docling.cli.main:Processed 1 docs, of which 0 failed INFO:docling.cli.main:All documents were converted in 58.56 seconds. (.venv) mario@Abhisheks-MacBook-Air docling % docling https://arxiv.org/pdf/2206.01062 --verbose INFO:docling.document_converter:Going to convert document batch... INFO:docling.pipeline.base_pipeline:Processing document 2206.01062v1.pdf INFO:docling.document_converter:Finished converting document 2206.01062v1.pdf in 59.82 sec. INFO:docling.cli.main:writing Markdown output to 2206.01062v1.md INFO:docling.cli.main:Processed 1 docs, of which 0 failed INFO:docling.cli.main:All documents were converted in 59.88 seconds. (.venv) mario@Abhisheks-MacBook-Air docling % docling Usage: docling [OPTIONS] source ╭─ Arguments ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ * input_sources source PDF files to convert. Can be local file / directory paths or URL. [default: None] [required] │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ ╭─ Options ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮ │ --from [docx|pptx|html|image|pdf|asciido Specify input formats to convert │ │ c|md|xlsx] from. Defaults to all formats. │ │ [default: None] │ │ --to [md|json|html|text|doctags] Specify output formats. Defaults to │ │ Markdown. │ │ [default: None] │ │ --image-export-mode [placeholder|embedded|referenced] Image export mode for the document │ │ (only in case of JSON, Markdown or │ │ HTML). With `placeholder`, only the │ │ position of the image is marked in │ │ the output. In `embedded` mode, the │ │ image is embedded as base64 encoded │ │ string. In `referenced` mode, the │ │ image is exported in PNG format and │ │ referenced from the main exported │ │ document. │ │ [default: embedded] │ │ --ocr --no-ocr If enabled, the bitmap content will │ │ be processed using OCR. │ │ [default: ocr] │ │ --force-ocr --no-force-ocr Replace any existing text with OCR │ │ generated text over the full │ │ content. │ │ [default: no-force-ocr] │ │ --ocr-engine [easyocr|tesseract_cli|tesseract| The OCR engine to use. │ │ ocrmac|rapidocr] [default: easyocr] │ │ --ocr-lang TEXT Provide a comma-separated list of │ │ languages used by the OCR engine. │ │ Note that each OCR engine has │ │ different values for the language │ │ names. │ │ [default: None] │ │ --pdf-backend [pypdfium2|dlparse_v1|dlparse_v2] The PDF backend to use. │ │ [default: dlparse_v2] │ │ --table-mode [fast|accurate] The mode to use in the table │ │ structure model. │ │ [default: fast] │ │ --artifacts-path PATH If provided, the location of the │ │ model artifacts. │ │ [default: None] │ │ --abort-on-error --no-abort-on-error If enabled, the bitmap content will │ │ be processed using OCR. │ │ [default: no-abort-on-error] │ │ --output PATH Output directory where results are │ │ saved. │ │ [default: .] │ │ --verbose -v INTEGER Set the verbosity level. -v for │ │ info logging, -vv for debug │ │ logging. │ │ [default: 0] │ │ --debug-visualize-cells --no-debug-visualize-cells Enable debug output which │ │ visualizes the PDF cells │ │ [default: no-debug-visualize-cells] │ │ --debug-visualize-ocr --no-debug-visualize-ocr Enable debug output which │ │ visualizes the OCR cells │ │ [default: no-debug-visualize-ocr] │ │ --debug-visualize-layout --no-debug-visualize-layout Enable debug output which │ │ visualizes the layour clusters │ │ [default: │ │ no-debug-visualize-layout] │ │ --debug-visualize-tables --no-debug-visualize-tables Enable debug output which │ │ visualizes the table cells │ │ [default: │ │ no-debug-visualize-tables] │ │ --version Show version information. │ │ --document-timeout FLOAT The timeout for processing each │ │ document, in seconds. │ │ [default: None] │ │ --help Show this message and exit. │ ╰─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯ |
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Docling
Docling parses documents and exports them to the desired format with ease and speed.
Features
- 🗂️ Reads popular document formats (PDF, DOCX, PPTX, XLSX, Images, HTML, AsciiDoc & Markdown) and exports to HTML, Markdown and JSON (with embedded and referenced images)
- 📑 Advanced PDF document understanding including page layout, reading order & table structures
- 🧩 Unified, expressive DoclingDocument representation format
- 🤖 Easy integration with 🦙 LlamaIndex & 🦜🔗 LangChain for powerful RAG / QA applications
- 🔍 OCR support for scanned PDFs
- 💻 Simple and convenient CLI
Explore the documentation to discover plenty examples and unlock the full power of Docling!
Coming soon
- ♾️ Equation & code extraction
- 📝 Metadata extraction, including title, authors, references & language
- 🦜🔗 Native LangChain extension
Installation
To use Docling, simply install docling from your package manager, e.g. pip:
pip install docling
Works on macOS, Linux and Windows environments. Both x86_64 and arm64 architectures.
More detailed installation instructions are available in the docs.
Getting started
To convert individual documents, use convert(), for example:
from docling.document_converter import DocumentConverter
source = "https://arxiv.org/pdf/2408.09869" # document per local path or URL
converter = DocumentConverter()
result = converter.convert(source)
print(result.document.export_to_markdown()) # output: "## Docling Technical Report[...]"
More advanced usage options are available in the docs.
Documentation
Check out Docling's documentation, for details on installation, usage, concepts, recipes, extensions, and more.
Examples
Go hands-on with our examples, demonstrating how to address different application use cases with Docling.
Integrations
To further accelerate your AI application development, check out Docling's native integrations with popular frameworks and tools.
Get help and support
Please feel free to connect with us using the discussion section.
Technical report
For more details on Docling's inner workings, check out the Docling Technical Report.
Contributing
Please read Contributing to Docling for details.
References
If you use Docling in your projects, please consider citing the following:
@techreport{Docling,
author = {Deep Search Team},
month = {8},
title = {Docling Technical Report},
url = {https://arxiv.org/abs/2408.09869},
eprint = {2408.09869},
doi = {10.48550/arXiv.2408.09869},
version = {1.0.0},
year = {2024}
}
License
The Docling codebase is under MIT license. For individual model usage, please refer to the model licenses found in the original packages.
IBM ❤️ Open Source AI
Docling has been brought to you by IBM.