docling-project/docling

Background JATS (Journal Article Tag Suite) is a standardized XML format used to encode, publish, and archive academic and scientific literature. It provides a common set of tags to structure article text, metadata (like authors and affiliations), figures, and citations, allowing research to be shared seamlessly across platforms like PubMed, CrossRef, and SciELO. Docling supports the parsing of JATS through the declarative backend JatsDocumentBackend. The first version was released with version 2.23.0 on Feb 17, 2025. Since then, the DoclingDocument data model has evolved and it now supports features that rich JATS document contain but had to be ignored in the first version. Goal The goal of this issue is to review the JATS backend and implement the parsing of features in JATS documents that can currently be support with DoclingDocument. Some of these features were marked as TODO in the code and thus they should be easy to locate and implement. They include: Footnotes @aaarif796 #3

Requested feature Currently, footnotes are serialized as part of MarkdownDocSerializer more or less as-is: Serialized as: 5 https://github.com/tesseract-ocr/tesseract 6 https://github.com/VikParuchuri/surya 7 https://github.com/lukas-blecher/LaTeX-OCR Alternatives For downstream LLM-based applications it would be helpful if footnotes were serialized as actual footnotes in Markdown Syntax for the LLM to indentify them as footnotes (and not as a numbered list, for example). ^[5 https://github.com/tesseract-ocr/tesseract] ^[6 https://github.com/VikParuchuri/surya] ^[7 https://github.com/lukas-blecher/LaTeX-OCR]

Problem When using ImageRefMode.REFERENCED, users must manually: Iterate through all picture elements Save each image to disk Update the URI for each element Then call export_to_markdown() Proposed Solution Add optional image_dir and image_path_prefix parameters to export methods: markdown = doc.export_to_markdown( image_mode=ImageRefMode.REFERENCED, image_dir=Path("./output/images"), image_path_prefix="images/" # relative path in markdown output ) When image_dir is provided: Automatically save images to that directory Generate sequential filenames (e.g. image_001.png) Use image_path_prefix in the markdown output Affected Methods DoclingDocument.export_to_markdown() PictureItem.export_to_markdown() Potentially HTML export methods too Would this be an interesting feature to have? Happy to submit a PR. (PS: Keep up the great work!!)

all work fine so fare but image count like i mentiont and same(similar) for tables yes you can convert tables in markdown directly but if you make a json <b<much better for embedding you have trouble to find the right place copy back to markdown. i made out of the json tables in json format tables_data = [] for table_ix, table in enumerate(conv_res.document.tables): if not hasattr(table, 'export_to_dataframe'): _log.warning(f"Table {table_ix} has no export method.") continue try: # Assuming clean_text is defined globally or passed in. # If missing, you must define it or use str(val).replace('\n', ' ') table_df = table.export_to_dataframe() num_rows = len(table_df) if hasattr(table_df, 'columns'): columns_list = list(table_df.columns) records = [ {col: clea

Bug In docling-core, the MarkdownTableSerializer transforms DoclingDocument headings and titles into markdown headings (i.e., text with preceding # symbols). According to the markdown specs, you can’t use headings, blockquotes, lists, horizontal rules, images, or most HTML tags when formatting text within tables and most applications will not render those headings properly. Steps to reproduce Convert Docling's test file table_with_heading_02.html to markdown or check its ground truth file table_with_heading_02.html.md Docling version Docling version: 2.64.0 Docling Core version: 2.51.1 Docling IBM Models version: 3.10.2 Docling Parse version: 4.7.1 Python: cpython-313 (3.13.5) Platform: macOS-14.7.1-arm64-arm-64bit-Mach-O Python version Python 3.13.5