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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>
42 lines
1.5 KiB
HTML
Vendored
42 lines
1.5 KiB
HTML
Vendored
<!DOCTYPE html>
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<html>
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<head>
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<meta charset="UTF-8">
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<title>Code snippets in HTML</title>
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</head>
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<body>
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<h1>Code snippets</h1>
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<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>
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<p>To use Docling, simply install <code>docling</code>from your package manager, e.g. pip:
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<kbd>pip install docling</kbd>
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</p>
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<p>To convert individual documents with python, use <code>convert()</code>, for example:</p>
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<pre><code>
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from docling.document_converter import DocumentConverter
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source = "https://arxiv.org/pdf/2408.09869"
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converter = DocumentConverter()
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result = converter.convert(source)
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print(result.document.export_to_markdown())
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</code></pre>
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<p>The program will output:
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<samp>## Docling Technical Report[...]</samp>
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</p>
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<p>Prefetch the models:</p>
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<ul>
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<li>Use the <code>docling-tools models download</code> utility:</li>
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<li>Alternatively, models can be programmatically downloaded using <samp>docling.utils.model_downloader.download_models()</samp>.</li>
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<li>Also, you can use download-hf-repo parameter to download arbitrary models from HuggingFace by specifying repo id:
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<pre><code>
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$ docling-tools models download-hf-repo ds4sd/SmolDocling-256M-preview
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Downloading ds4sd/SmolDocling-256M-preview model from HuggingFace...
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</code></pre>
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<pre hidden><code>$ docling-tools</code></pre>
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</li>
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</ul>
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</body>
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</html>
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