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fix(html): preserve code blocks in list items (#2131)

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* chore(html): refactor parser to leverage context managers

Signed-off-by: Cesar Berrospi Ramis <ceb@zurich.ibm.com>

* fix(html): parse inline code snippets, also from list items

Signed-off-by: Cesar Berrospi Ramis <ceb@zurich.ibm.com>

* chore(html): remove hidden tags

Remove tags that are not meant to be displayed.
Add regression tests for code blocks, inline code, and hidden tags.

Signed-off-by: Cesar Berrospi Ramis <ceb@zurich.ibm.com>

---------

Signed-off-by: Cesar Berrospi Ramis <ceb@zurich.ibm.com>
This commit is contained in:
Cesar Berrospi Ramis
2025-08-26 06:43:48 +02:00
committed by GitHub
parent c0268416cf
commit fa3327e1a6
5 changed files with 950 additions and 76 deletions
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41
tests/data/html/html_code_snippets.html vendored Normal file
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<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8">
<title>Code snippets in HTML</title>
</head>
<body>
<h1>Code snippets</h1>
<p>The Pythagorean theorem can be written as an equation relating the lengths of the sides <var>a</var>, <var>b</var> and the hypotenuse <var>c</var>.</p>
<p>To use Docling, simply install <code>docling</code>from your package manager, e.g. pip:
<kbd>pip install docling</kbd>
</p>
<p>To convert individual documents with python, use <code>convert()</code>, for example:</p>
<pre><code>
from docling.document_converter import DocumentConverter
source = "https://arxiv.org/pdf/2408.09869"
converter = DocumentConverter()
result = converter.convert(source)
print(result.document.export_to_markdown())
</code></pre>
<p>The program will output:
<samp>## Docling Technical Report[...]</samp>
</p>
<p>Prefetch the models:</p>
<ul>
<li>Use the <code>docling-tools models download</code> utility:</li>
<li>Alternatively, models can be programmatically downloaded using <samp>docling.utils.model_downloader.download_models()</samp>.</li>
<li>Also, you can use download-hf-repo parameter to download arbitrary models from HuggingFace by specifying repo id:
<pre><code>
$ docling-tools models download-hf-repo ds4sd/SmolDocling-256M-preview
Downloading ds4sd/SmolDocling-256M-preview model from HuggingFace...
</code></pre>
<pre hidden><code>$ docling-tools</code></pre>
</li>
</ul>
</body>
</html>