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</li></ul></nav></div></div></aside><main class="docMainContainer_TBSr"><div class="container padding-top--md padding-bottom--lg"><div class="row"><div class="col docItemCol_VOVn"><div class="docItemContainer_Djhp"><article><nav class="theme-doc-breadcrumbs breadcrumbsContainer_Z_bl" aria-label="Breadcrumbs"><ul class="breadcrumbs"><li class="breadcrumbs__item"><a aria-label="Home page" class="breadcrumbs__link" href="/"><svg viewBox="0 0 24 24" class="breadcrumbHomeIcon_YNFT"><path d="M10 19v-5h4v5c0 .55.45 1 1 1h3c.55 0 1-.45 1-1v-7h1.7c.46 0 .68-.57.33-.87L12.67 3.6c-.38-.34-.96-.34-1.34 0l-8.36 7.53c-.34.3-.13.87.33.87H5v7c0 .55.45 1 1 1h3c.55 0 1-.45 1-1z" fill="currentColor"></path></svg></a></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">Integrations</span></li><li class="breadcrumbs__item"><span class="breadcrumbs__link">NVIDIA</span></li><li class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link">NVIDIA Ingest</span></li></ul></nav><div class="tocCollapsible_ETCw theme-doc-toc-mobile tocMobile_ITEo"><button type="button" class="clean-btn tocCollapsibleButton_TO0P">On this page</button></div><div class="theme-doc-markdown markdown"><header><h1>Integrate NVIDIA Retriever Extraction with Langflow</h1></header><style>[data-ch-theme="github-dark"] { --ch-t-colorScheme: dark;--ch-t-foreground: #c9d1d9;--ch-t-background: #0d1117;--ch-t-lighter-inlineBackground: #0d1117e6;--ch-t-editor-background: #0d1117;--ch-t-editor-foreground: #c9d1d9;--ch-t-editor-lineHighlightBackground: #6e76811a;--ch-t-editor-rangeHighlightBackground: #ffffff0b;--ch-t-editor-infoForeground: #3794FF;--ch-t-editor-selectionBackground: #264F78;--ch-t-focusBorder: #1f6feb;--ch-t-tab-activeBackground: #0d1117;--ch-t-tab-activeForeground: #c9d1d9;--ch-t-tab-inactiveBackground: #010409;--ch-t-tab-inactiveForeground: #8b949e;--ch-t-tab-border: #30363d;--ch-t-tab-activeBorder: #0d1117;--ch-t-editorGroup-border: #30363d;--ch-t-editorGroupHeader-tabsBackground: #010409;--ch-t-editorLineNumber-foreground: #6e7681;--ch-t-input-background: #0d1117;--ch-t-input-foreground: #c9d1d9;--ch-t-input-border: #30363d;--ch-t-icon-foreground: #8b949e;--ch-t-sideBar-background: #010409;--ch-t-sideBar-foreground: #c9d1d9;--ch-t-sideBar-border: #30363d;--ch-t-list-activeSelectionBackground: #6e768166;--ch-t-list-activeSelectionForeground: #c9d1d9;--ch-t-list-hoverBackground: #6e76811a;--ch-t-list-hoverForeground: #c9d1d9; }</style>
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<div class="theme-admonition theme-admonition-note admonition_xJq3 alert alert--secondary"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 14 16"><path fill-rule="evenodd" d="M6.3 5.69a.942.942 0 0 1-.28-.7c0-.28.09-.52.28-.7.19-.18.42-.28.7-.28.28 0 .52.09.7.28.18.19.28.42.28.7 0 .28-.09.52-.28.7a1 1 0 0 1-.7.3c-.28 0-.52-.11-.7-.3zM8 7.99c-.02-.25-.11-.48-.31-.69-.2-.19-.42-.3-.69-.31H6c-.27.02-.48.13-.69.31-.2.2-.3.44-.31.69h1v3c.02.27.11.5.31.69.2.2.42.31.69.31h1c.27 0 .48-.11.69-.31.2-.19.3-.42.31-.69H8V7.98v.01zM7 2.3c-3.14 0-5.7 2.54-5.7 5.68 0 3.14 2.56 5.7 5.7 5.7s5.7-2.55 5.7-5.7c0-3.15-2.56-5.69-5.7-5.69v.01zM7 .98c3.86 0 7 3.14 7 7s-3.14 7-7 7-7-3.12-7-7 3.14-7 7-7z"></path></svg></span>note</div><div class="admonitionContent_BuS1"><p>NVIDIA Retriever Extraction is also known as NV-Ingest and NeMo Retriever Extraction.</p></div></div>
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<p>The <strong>NVIDIA Retriever Extraction</strong> component integrates with the <a href="https://github.com/NVIDIA/nv-ingest" target="_blank" rel="noopener noreferrer">NVIDIA nv-ingest</a> microservice for data ingestion, processing, and extraction of text files.</p>
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<p>The <code>nv-ingest</code> service supports multiple extraction methods for PDF, DOCX, and PPTX file types, and includes pre- and post-processing services like splitting, chunking, and embedding generation. The extractor service's High Resolution mode uses the <code>nemoretriever-parse</code> extraction method for better quality extraction from scanned PDF documents. This feature is only available for PDF files.</p>
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<p>The <strong>NVIDIA Retriever Extraction</strong> component imports the NVIDIA <code>Ingestor</code> client, ingests files with requests to the NVIDIA ingest endpoint, and outputs the processed content as a list of <a href="/concepts-objects#data-object">Data</a> objects. <code>Ingestor</code> accepts additional configuration options for data extraction from other text formats. To configure these options, see the <a href="/integrations-nvidia-ingest#parameters">component parameters</a>.</p>
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<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="prerequisites">Prerequisites<a href="#prerequisites" class="hash-link" aria-label="Direct link to Prerequisites" title="Direct link to Prerequisites"></a></h2>
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<ul>
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<li>
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<p>An NVIDIA Ingest endpoint. For more information on setting up an NVIDIA Ingest endpoint, see the <a href="https://github.com/NVIDIA/nv-ingest?tab=readme-ov-file#quickstart" target="_blank" rel="noopener noreferrer">NVIDIA Ingest quickstart</a>.</p>
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</li>
|
||
<li>
|
||
<p>The <strong>NVIDIA Retriever Extraction</strong> component requires the installation of additional dependencies to your Langflow environment. To install the dependencies in a virtual environment, run the following commands.</p>
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<ul>
|
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<li>If you have the Langflow repository cloned and installed from source:</li>
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</ul>
|
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<div class="ch-codeblock not-prose" data-ch-theme="github-dark"><div class="ch-code-wrapper ch-code" data-ch-measured="false"><code class="ch-code-scroll-parent"><br><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>source **YOUR_LANGFLOW_VENV**/bin/activate</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>uv sync --extra nv-ingest</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>uv run langflow run</span></div></div><br></code></div></div>
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<ul>
|
||
<li>If you are installing Langflow from the Python Package Index:</li>
|
||
</ul>
|
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<div class="ch-codeblock not-prose" data-ch-theme="github-dark"><div class="ch-code-wrapper ch-code" data-ch-measured="false"><code class="ch-code-scroll-parent"><br><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>source **YOUR_LANGFLOW_VENV**/bin/activate</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>uv pip install --prerelease=allow 'langflow[nv-ingest]'</span></div></div><div><span class="ch-code-line-number">_<!-- -->10</span><div style="display:inline-block;margin-left:16px"><span>uv run langflow run</span></div></div><br></code></div></div>
|
||
</li>
|
||
</ul>
|
||
<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="use-the-nvidia-retriever-extraction-component-in-a-flow">Use the NVIDIA Retriever Extraction component in a flow<a href="#use-the-nvidia-retriever-extraction-component-in-a-flow" class="hash-link" aria-label="Direct link to Use the NVIDIA Retriever Extraction component in a flow" title="Direct link to Use the NVIDIA Retriever Extraction component in a flow"></a></h2>
|
||
<p>The <strong>NVIDIA Retriever Extraction</strong> component accepts <strong>Message</strong> inputs and outputs <strong>Data</strong>. The component calls an NVIDIA Ingest microservice's endpoint to ingest a local file and extract the text.</p>
|
||
<p>To use the NVIDIA Retriever Extraction component in your flow, follow these steps:</p>
|
||
<ol>
|
||
<li>In the component library, click the <strong>NVIDIA Retriever Extraction</strong> component, and then drag it onto the canvas.</li>
|
||
<li>In the <strong>Base URL</strong> field, enter the URL of the NVIDIA Ingest endpoint.
|
||
Optionally, add the endpoint URL as a <strong>Global variable</strong>:<!-- -->
|
||
<ol>
|
||
<li>Click <strong>Settings</strong>, and then click <strong>Global Variables</strong>.</li>
|
||
<li>Click <strong>Add New</strong>.</li>
|
||
<li>Name your variable. Paste your endpoint in the <strong>Value</strong> field.</li>
|
||
<li>In the <strong>Apply To Fields</strong> field, select the field you want to globally apply this variable to. In this case, select <strong>NVIDIA Base URL</strong>.</li>
|
||
<li>Click <strong>Save Variable</strong>.</li>
|
||
</ol>
|
||
</li>
|
||
<li>Click the <strong>Select files</strong> button to select which file you want to ingest.</li>
|
||
<li>Select which text type to extract from the file.
|
||
The component supports text, charts, tables, images, and infographics.
|
||
Optionally, for PDF files, enable High Resolution mode for better quality extraction from scanned documents.</li>
|
||
<li>Select whether to split the text into chunks.
|
||
Modify the splitting parameters in the component's <strong>Configuration</strong> tab.</li>
|
||
<li>Click <strong>Run</strong> to ingest the file.</li>
|
||
<li>To confirm the component is ingesting the file, open the <strong>Logs</strong> pane to view the output of the flow.</li>
|
||
<li>To store the processed data in a vector database, add an <strong>AstraDB Vector</strong> component to your flow, and connect the <strong>NVIDIA Retriever Extraction</strong> component to the <strong>AstraDB Vector</strong> component with a <strong>Data</strong> output.</li>
|
||
</ol>
|
||
<p><img decoding="async" loading="lazy" alt="NVIDIA Retriever Extraction component flow" src="/assets/images/nvidia-component-ingest-astra-c6f0107751252206ab0d500a25ba3f9c.png" width="1722" height="1548" class="img_ev3q"></p>
|
||
<ol start="9">
|
||
<li>Run the flow.
|
||
Inspect your Astra DB vector database to view the processed data.</li>
|
||
</ol>
|
||
<h2 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="parameters">NVIDIA Retriever Extraction component parameters<a href="#parameters" class="hash-link" aria-label="Direct link to NVIDIA Retriever Extraction component parameters" title="Direct link to NVIDIA Retriever Extraction component parameters"></a></h2>
|
||
<p>The <strong>NVIDIA Retriever Extraction</strong> component has the following parameters.</p>
|
||
<p>For more information, see the <a href="https://nvidia.github.io/nv-ingest/user-guide/" target="_blank" rel="noopener noreferrer">NV-Ingest documentation</a>.</p>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="inputs">Inputs<a href="#inputs" class="hash-link" aria-label="Direct link to Inputs" title="Direct link to Inputs"></a></h3>
|
||
<table><thead><tr><th>Name</th><th>Display Name</th><th>Info</th></tr></thead><tbody><tr><td>base_url</td><td>NVIDIA Ingestion URL</td><td>The URL of the NVIDIA Ingestion API.</td></tr><tr><td>path</td><td>Path</td><td>File path to process.</td></tr><tr><td>extract_text</td><td>Extract Text</td><td>Extract text from documents. Default: <code>True</code>.</td></tr><tr><td>extract_charts</td><td>Extract Charts</td><td>Extract text from charts. Default: <code>False</code>.</td></tr><tr><td>extract_tables</td><td>Extract Tables</td><td>Extract text from tables. Default: <code>True</code>.</td></tr><tr><td>extract_images</td><td>Extract Images</td><td>Extract images from document. Default: <code>True</code>.</td></tr><tr><td>extract_infographics</td><td>Extract Infographics</td><td>Extract infographics from document. Default: <code>False</code>.</td></tr><tr><td>text_depth</td><td>Text Depth</td><td>The level at which text is extracted. Options: 'document', 'page', 'block', 'line', 'span'. Default: <code>page</code>.</td></tr><tr><td>split_text</td><td>Split Text</td><td>Split text into smaller chunks. Default: <code>True</code>.</td></tr><tr><td>chunk_size</td><td>Chunk Size</td><td>The number of tokens per chunk. Default: <code>500</code>.</td></tr><tr><td>chunk_overlap</td><td>Chunk Overlap</td><td>Number of tokens to overlap from previous chunk. Default: <code>150</code>.</td></tr><tr><td>filter_images</td><td>Filter Images</td><td>Filter images (see advanced options for filtering criteria). Default: <code>False</code>.</td></tr><tr><td>min_image_size</td><td>Minimum Image Size Filter</td><td>Minimum image width/length in pixels. Default: <code>128</code>.</td></tr><tr><td>min_aspect_ratio</td><td>Minimum Aspect Ratio Filter</td><td>Minimum allowed aspect ratio (width / height). Default: <code>0.2</code>.</td></tr><tr><td>max_aspect_ratio</td><td>Maximum Aspect Ratio Filter</td><td>Maximum allowed aspect ratio (width / height). Default: <code>5.0</code>.</td></tr><tr><td>dedup_images</td><td>Deduplicate Images</td><td>Filter duplicated images. Default: <code>True</code>.</td></tr><tr><td>caption_images</td><td>Caption Images</td><td>Generate captions for images using the NVIDIA captioning model. Default: <code>True</code>.</td></tr><tr><td>high_resolution</td><td>High Resolution (PDF only)</td><td>Process PDF in high-resolution mode for better quality extraction from scanned PDF. Default: <code>False</code>.</td></tr></tbody></table>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="outputs">Outputs<a href="#outputs" class="hash-link" aria-label="Direct link to Outputs" title="Direct link to Outputs"></a></h3>
|
||
<p>The <strong>NVIDIA Retriever Extraction</strong> component outputs a list of <a href="/concepts-objects#data-object">Data</a> objects where each object contains:</p>
|
||
<ul>
|
||
<li><code>text</code>: The extracted content.<!-- -->
|
||
<ul>
|
||
<li>For text documents: The extracted text content.</li>
|
||
<li>For tables and charts: The extracted table/chart content.</li>
|
||
<li>For images: The image caption.</li>
|
||
<li>For infographics: The extracted infographic content.</li>
|
||
</ul>
|
||
</li>
|
||
<li><code>file_path</code>: The source file name and path.</li>
|
||
<li><code>document_type</code>: The type of the document, which can be <code>text</code>, <code>structured</code>, or <code>image</code>.</li>
|
||
<li><code>description</code>: Additional description of the content.</li>
|
||
</ul>
|
||
<p>The output varies based on the <code>document_type</code>:</p>
|
||
<ul>
|
||
<li>
|
||
<p>Documents with <code>document_type: "text"</code> contain:</p>
|
||
<ul>
|
||
<li>Raw text content extracted from documents, for example, paragraphs from PDFs or DOCX files.</li>
|
||
<li>Content stored directly in the <code>text</code> field.</li>
|
||
<li>Content extracted using the <code>extract_text</code> parameter.</li>
|
||
</ul>
|
||
</li>
|
||
<li>
|
||
<p>Documents with <code>document_type: "structured"</code> contain:</p>
|
||
<ul>
|
||
<li>Text extracted from tables, charts, and infographics and processed to preserve structural information.</li>
|
||
<li>Content extracted using the <code>extract_tables</code>, <code>extract_charts</code>, and <code>extract_infographics</code> parameters.</li>
|
||
<li>Content stored in the <code>text</code> field after being processed from the <code>table_content</code> metadata.</li>
|
||
</ul>
|
||
</li>
|
||
<li>
|
||
<p>Documents with <code>document_type: "image"</code> contain:</p>
|
||
<ul>
|
||
<li>Image content extracted from documents.</li>
|
||
<li>Caption text stored in the <code>text</code> field when <code>caption_images</code> is enabled.</li>
|
||
<li>Content extracted using the <code>extract_images</code> parameter.</li>
|
||
</ul>
|
||
</li>
|
||
</ul></div></article><nav class="docusaurus-mt-lg pagination-nav" aria-label="Docs pages"><a class="pagination-nav__link pagination-nav__link--prev" href="/integrations/notion/notion-agent-meeting-notes"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Notion Meeting Notes Agent</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/integrations-nvidia-ingest-wsl2"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">NVIDIA NIM on WSL2</div></a></nav></div></div><div class="col col--3"><div class="tableOfContents_bqdL thin-scrollbar theme-doc-toc-desktop"><ul class="table-of-contents table-of-contents__left-border"><li><a href="#prerequisites" class="table-of-contents__link toc-highlight">Prerequisites</a></li><li><a href="#use-the-nvidia-retriever-extraction-component-in-a-flow" class="table-of-contents__link toc-highlight">Use the NVIDIA Retriever Extraction component in a flow</a></li><li><a href="#parameters" class="table-of-contents__link toc-highlight">NVIDIA Retriever Extraction component parameters</a><ul><li><a href="#inputs" class="table-of-contents__link toc-highlight">Inputs</a></li><li><a href="#outputs" class="table-of-contents__link toc-highlight">Outputs</a></li></ul></li></ul></div></div></div></div></main></div></div></div><footer class="theme-layout-footer footer"><div class="container container-fluid"><div class="row footer__links"><div class="theme-layout-footer-column col footer__col"><div class="footer__title"></div><ul class="footer__items clean-list"><li class="footer__item"><div class="footer-links">
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