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Formula understanding
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<div class="md-content" data-md-component="content">
<article class="md-content__inner md-typeset">
<h1>Enrichment features</h1>
<p>Docling allows to enrich the conversion pipeline with additional steps which process specific document components,
e.g. code blocks, pictures, etc. The extra steps usually require extra models executions which may increase
the processing time consistently. For this reason most enrichment models are disabled by default.</p>
<p>The following table provides an overview of the default enrichment models available in Docling.</p>
<table>
<thead>
<tr>
<th>Feature</th>
<th>Parameter</th>
<th>Processed item</th>
<th>Description</th>
</tr>
</thead>
<tbody>
<tr>
<td>Code understanding</td>
<td><code>do_code_enrichment</code></td>
<td><code>CodeItem</code></td>
<td>See <a href="#code-understanding">docs below</a>.</td>
</tr>
<tr>
<td>Formula understanding</td>
<td><code>do_formula_enrichment</code></td>
<td><code>TextItem</code> with label <code>FORMULA</code></td>
<td>See <a href="#formula-understanding">docs below</a>.</td>
</tr>
<tr>
<td>Picture classification</td>
<td><code>do_picture_classification</code></td>
<td><code>PictureItem</code></td>
<td>See <a href="#picture-classification">docs below</a>.</td>
</tr>
<tr>
<td>Picture description</td>
<td><code>do_picture_description</code></td>
<td><code>PictureItem</code></td>
<td>See <a href="#picture-description">docs below</a>.</td>
</tr>
</tbody>
</table>
<h2 id="enrichments-details">Enrichments details</h2>
<h3 id="code-understanding">Code understanding</h3>
<p>The code understanding step allows to use advance parsing for code blocks found in the document.
This enrichment model also set the <code>code_language</code> property of the <code>CodeItem</code>.</p>
<p>Model specs: see the <a href="https://huggingface.co/ds4sd/CodeFormula"><code>CodeFormula</code> model card</a>.</p>
<p>Example command line:</p>
<div class="highlight"><pre><span></span><code>docling<span class="w"> </span>--enrich-code<span class="w"> </span>FILE
</code></pre></div>
<p>Example code:</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.document_converter</span><span class="w"> </span><span class="kn">import</span> <span class="n">DocumentConverter</span><span class="p">,</span> <span class="n">PdfFormatOption</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">PdfPipelineOptions</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.base_models</span><span class="w"> </span><span class="kn">import</span> <span class="n">InputFormat</span>
<span class="n">pipeline_options</span> <span class="o">=</span> <span class="n">PdfPipelineOptions</span><span class="p">()</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">do_code_enrichment</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">converter</span> <span class="o">=</span> <span class="n">DocumentConverter</span><span class="p">(</span><span class="n">format_options</span><span class="o">=</span><span class="p">{</span>
<span class="n">InputFormat</span><span class="o">.</span><span class="n">PDF</span><span class="p">:</span> <span class="n">PdfFormatOption</span><span class="p">(</span><span class="n">pipeline_options</span><span class="o">=</span><span class="n">pipeline_options</span><span class="p">)</span>
<span class="p">})</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">converter</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s2">&quot;https://arxiv.org/pdf/2501.17887&quot;</span><span class="p">)</span>
<span class="n">doc</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">document</span>
</code></pre></div>
<h3 id="formula-understanding">Formula understanding</h3>
<p>The formula understanding step will analize the equation formulas in documents and extract their LaTeX representation.
The HTML export functions in the DoclingDocument will leverage the formula and visualize the result using the mathml html syntax.</p>
<p>Model specs: see the <a href="https://huggingface.co/ds4sd/CodeFormula"><code>CodeFormula</code> model card</a>.</p>
<p>Example command line:</p>
<div class="highlight"><pre><span></span><code>docling<span class="w"> </span>--enrich-formula<span class="w"> </span>FILE
</code></pre></div>
<p>Example code:</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.document_converter</span><span class="w"> </span><span class="kn">import</span> <span class="n">DocumentConverter</span><span class="p">,</span> <span class="n">PdfFormatOption</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">PdfPipelineOptions</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.base_models</span><span class="w"> </span><span class="kn">import</span> <span class="n">InputFormat</span>
<span class="n">pipeline_options</span> <span class="o">=</span> <span class="n">PdfPipelineOptions</span><span class="p">()</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">do_formula_enrichment</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">converter</span> <span class="o">=</span> <span class="n">DocumentConverter</span><span class="p">(</span><span class="n">format_options</span><span class="o">=</span><span class="p">{</span>
<span class="n">InputFormat</span><span class="o">.</span><span class="n">PDF</span><span class="p">:</span> <span class="n">PdfFormatOption</span><span class="p">(</span><span class="n">pipeline_options</span><span class="o">=</span><span class="n">pipeline_options</span><span class="p">)</span>
<span class="p">})</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">converter</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s2">&quot;https://arxiv.org/pdf/2501.17887&quot;</span><span class="p">)</span>
<span class="n">doc</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">document</span>
</code></pre></div>
<h3 id="picture-classification">Picture classification</h3>
<p>The picture classification step classifies the <code>PictureItem</code> elements in the document with the <code>DocumentFigureClassifier</code> model.
This model is specialized to understand the classes of pictures found in documents, e.g. different chart types, flow diagrams,
logos, signatures, etc.</p>
<p>Model specs: see the <a href="https://huggingface.co/ds4sd/DocumentFigureClassifier"><code>DocumentFigureClassifier</code> model card</a>.</p>
<p>Example command line:</p>
<div class="highlight"><pre><span></span><code>docling<span class="w"> </span>--enrich-picture-classes<span class="w"> </span>FILE
</code></pre></div>
<p>Example code:</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.document_converter</span><span class="w"> </span><span class="kn">import</span> <span class="n">DocumentConverter</span><span class="p">,</span> <span class="n">PdfFormatOption</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">PdfPipelineOptions</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.base_models</span><span class="w"> </span><span class="kn">import</span> <span class="n">InputFormat</span>
<span class="n">pipeline_options</span> <span class="o">=</span> <span class="n">PdfPipelineOptions</span><span class="p">()</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">generate_picture_images</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">images_scale</span> <span class="o">=</span> <span class="mi">2</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">do_picture_classification</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">converter</span> <span class="o">=</span> <span class="n">DocumentConverter</span><span class="p">(</span><span class="n">format_options</span><span class="o">=</span><span class="p">{</span>
<span class="n">InputFormat</span><span class="o">.</span><span class="n">PDF</span><span class="p">:</span> <span class="n">PdfFormatOption</span><span class="p">(</span><span class="n">pipeline_options</span><span class="o">=</span><span class="n">pipeline_options</span><span class="p">)</span>
<span class="p">})</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">converter</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s2">&quot;https://arxiv.org/pdf/2501.17887&quot;</span><span class="p">)</span>
<span class="n">doc</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">document</span>
</code></pre></div>
<h3 id="picture-description">Picture description</h3>
<p>The picture description step allows to annotate a picture with a vision model. This is also known as a "captioning" task.
The Docling pipeline allows to load and run models completely locally as well as connecting to remote API which support the chat template.
Below follow a few examples on how to use some common vision model and remote services.</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.document_converter</span><span class="w"> </span><span class="kn">import</span> <span class="n">DocumentConverter</span><span class="p">,</span> <span class="n">PdfFormatOption</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">PdfPipelineOptions</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.base_models</span><span class="w"> </span><span class="kn">import</span> <span class="n">InputFormat</span>
<span class="n">pipeline_options</span> <span class="o">=</span> <span class="n">PdfPipelineOptions</span><span class="p">()</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">do_picture_description</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">converter</span> <span class="o">=</span> <span class="n">DocumentConverter</span><span class="p">(</span><span class="n">format_options</span><span class="o">=</span><span class="p">{</span>
<span class="n">InputFormat</span><span class="o">.</span><span class="n">PDF</span><span class="p">:</span> <span class="n">PdfFormatOption</span><span class="p">(</span><span class="n">pipeline_options</span><span class="o">=</span><span class="n">pipeline_options</span><span class="p">)</span>
<span class="p">})</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">converter</span><span class="o">.</span><span class="n">convert</span><span class="p">(</span><span class="s2">&quot;https://arxiv.org/pdf/2501.17887&quot;</span><span class="p">)</span>
<span class="n">doc</span> <span class="o">=</span> <span class="n">result</span><span class="o">.</span><span class="n">document</span>
</code></pre></div>
<h4 id="granite-vision-model">Granite Vision model</h4>
<p>Model specs: see the <a href="https://huggingface.co/ibm-granite/granite-vision-3.1-2b-preview"><code>ibm-granite/granite-vision-3.1-2b-preview</code> model card</a>.</p>
<p>Usage in Docling:</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">granite_picture_description</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">picture_description_options</span> <span class="o">=</span> <span class="n">granite_picture_description</span>
</code></pre></div>
<h4 id="smolvlm-model">SmolVLM model</h4>
<p>Model specs: see the <a href="https://huggingface.co/HuggingFaceTB/SmolVLM-256M-Instruct"><code>HuggingFaceTB/SmolVLM-256M-Instruct</code> model card</a>.</p>
<p>Usage in Docling:</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">smolvlm_picture_description</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">picture_description_options</span> <span class="o">=</span> <span class="n">smolvlm_picture_description</span>
</code></pre></div>
<h4 id="other-vision-models">Other vision models</h4>
<p>The option class <code>PictureDescriptionVlmOptions</code> allows to use any another model from the Hugging Face Hub.</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">PictureDescriptionVlmOptions</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">picture_description_options</span> <span class="o">=</span> <span class="n">PictureDescriptionVlmOptions</span><span class="p">(</span>
<span class="n">repo_id</span><span class="o">=</span><span class="s2">&quot;&quot;</span><span class="p">,</span> <span class="c1"># &lt;-- add here the Hugging Face repo_id of your favorite VLM</span>
<span class="n">prompt</span><span class="o">=</span><span class="s2">&quot;Describe the image in three sentences. Be consise and accurate.&quot;</span><span class="p">,</span>
<span class="p">)</span>
</code></pre></div>
<h4 id="remote-vision-model">Remote vision model</h4>
<p>The option class <code>PictureDescriptionApiOptions</code> allows to use models hosted on remote platforms, e.g.
on local endpoints served by <a href="https://docs.vllm.ai">VLLM</a>, <a href="https://ollama.com/">Ollama</a> and others,
or cloud providers like <a href="https://www.ibm.com/products/watsonx-ai">IBM watsonx.ai</a>, etc.</p>
<p><em>Note: in most cases this option will send your data to the remote service provider.</em></p>
<p>Usage in Docling:</p>
<div class="highlight"><pre><span></span><code><span class="kn">from</span><span class="w"> </span><span class="nn">docling.datamodel.pipeline_options</span><span class="w"> </span><span class="kn">import</span> <span class="n">PictureDescriptionApiOptions</span>
<span class="c1"># Enable connections to remote services</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">enable_remote_services</span><span class="o">=</span><span class="kc">True</span> <span class="c1"># &lt;-- this is required!</span>
<span class="c1"># Example using a model running locally, e.g. via VLLM</span>
<span class="c1"># $ vllm serve MODEL_NAME</span>
<span class="n">pipeline_options</span><span class="o">.</span><span class="n">picture_description_options</span> <span class="o">=</span> <span class="n">PictureDescriptionApiOptions</span><span class="p">(</span>
<span class="n">url</span><span class="o">=</span><span class="s2">&quot;http://localhost:8000/v1/chat/completions&quot;</span><span class="p">,</span>
<span class="n">params</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span>
<span class="n">model</span><span class="o">=</span><span class="s2">&quot;MODEL NAME&quot;</span><span class="p">,</span>
<span class="n">seed</span><span class="o">=</span><span class="mi">42</span><span class="p">,</span>
<span class="n">max_completion_tokens</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span>
<span class="p">),</span>
<span class="n">prompt</span><span class="o">=</span><span class="s2">&quot;Describe the image in three sentences. Be consise and accurate.&quot;</span><span class="p">,</span>
<span class="n">timeout</span><span class="o">=</span><span class="mi">90</span><span class="p">,</span>
<span class="p">)</span>
</code></pre></div>
<p>End-to-end code snippets for cloud providers are available in the examples section:</p>
<ul>
<li><a href="../../examples/pictures_description_api/">IBM watsonx.ai</a></li>
</ul>
<h2 id="develop-new-enrichment-models">Develop new enrichment models</h2>
<p>Beside looking at the implementation of all the models listed above, the Docling documentation has a few examples
dedicated to the implementation of enrichment models.</p>
<ul>
<li><a href="../../examples/develop_picture_enrichment/">Develop picture enrichment</a></li>
<li><a href="../../examples/develop_formula_understanding/">Develop formula enrichment</a></li>
</ul>
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