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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">Components</span><meta itemprop="position" content="1"></li><li itemscope="" itemprop="itemListElement" itemtype="https://schema.org/ListItem" class="breadcrumbs__item breadcrumbs__item--active"><span class="breadcrumbs__link" itemprop="name">Vector Stores</span><meta itemprop="position" content="2"></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"><h1>Vector Stores</h1>
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<div class="theme-admonition theme-admonition-warning admonition_xJq3 alert alert--warning"><div class="admonitionHeading_Gvgb"><span class="admonitionIcon_Rf37"><svg viewBox="0 0 16 16"><path fill-rule="evenodd" d="M8.893 1.5c-.183-.31-.52-.5-.887-.5s-.703.19-.886.5L.138 13.499a.98.98 0 0 0 0 1.001c.193.31.53.501.886.501h13.964c.367 0 .704-.19.877-.5a1.03 1.03 0 0 0 .01-1.002L8.893 1.5zm.133 11.497H6.987v-2.003h2.039v2.003zm0-3.004H6.987V5.987h2.039v4.006z"></path></svg></span>warning</div><div class="admonitionContent_BuS1"><p>This page may contain outdated information. It will be updated as soon as possible.</p></div></div>
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<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="astra-db">Astra DB<a class="hash-link" aria-label="Direct link to Astra DB" title="Direct link to Astra DB" href="/components/vector-stores#astra-db"></a></h3>
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<p>The <code>Astra DB</code> initializes a vector store using Astra DB from Data. It creates Astra DB-based vector indexes to efficiently store and retrieve documents.</p>
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<p><strong>Parameters:</strong></p>
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<ul>
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<li><strong>Input:</strong> Documents or Data for input.</li>
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<li><strong>Embedding or Astra vectorize:</strong> External or server-side model Astra DB uses.</li>
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<li><strong>Collection Name:</strong> Name of the Astra DB collection.</li>
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<li><strong>Token:</strong> Authentication token for Astra DB.</li>
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<li><strong>API Endpoint:</strong> API endpoint for Astra DB.</li>
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<li><strong>Namespace:</strong> Astra DB namespace.</li>
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<li><strong>Metric:</strong> Metric used by Astra DB.</li>
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<li><strong>Batch Size:</strong> Batch size for operations.</li>
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<li><strong>Bulk Insert Batch Concurrency:</strong> Concurrency level for bulk inserts.</li>
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<li><strong>Bulk Insert Overwrite Concurrency:</strong> Concurrency level for overwriting during bulk inserts.</li>
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<li><strong>Bulk Delete Concurrency:</strong> Concurrency level for bulk deletions.</li>
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||
<li><strong>Setup Mode:</strong> Setup mode for the vector store.</li>
|
||
<li><strong>Pre Delete Collection:</strong> Option to delete the collection before setup.</li>
|
||
<li><strong>Metadata Indexing Include:</strong> Fields to include in metadata indexing.</li>
|
||
<li><strong>Metadata Indexing Exclude:</strong> Fields to exclude from metadata indexing.</li>
|
||
<li><strong>Collection Indexing Policy:</strong> Indexing policy for the collection.</li>
|
||
</ul>
|
||
<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>Ensure you configure the necessary Astra DB token and API endpoint before
|
||
starting.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="astra-db-search">Astra DB Search<a class="hash-link" aria-label="Direct link to Astra DB Search" title="Direct link to Astra DB Search" href="/components/vector-stores#astra-db-search"></a></h3>
|
||
<p><code>Astra DBSearch</code> searches an existing Astra DB vector store for documents similar to the input. It uses the <code>Astra DB</code> component's functionality for efficient retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as Similarity or MMR.</li>
|
||
<li><strong>Input Value:</strong> Value to search for.</li>
|
||
<li><strong>Embedding or Astra vectorize:</strong> External or server-side model Astra DB uses.</li>
|
||
<li><strong>Collection Name:</strong> Name of the Astra DB collection.</li>
|
||
<li><strong>Token:</strong> Authentication token for Astra DB.</li>
|
||
<li><strong>API Endpoint:</strong> API endpoint for Astra DB.</li>
|
||
<li><strong>Namespace:</strong> Astra DB namespace.</li>
|
||
<li><strong>Metric:</strong> Metric used by Astra DB.</li>
|
||
<li><strong>Batch Size:</strong> Batch size for operations.</li>
|
||
<li><strong>Bulk Insert Batch Concurrency:</strong> Concurrency level for bulk inserts.</li>
|
||
<li><strong>Bulk Insert Overwrite Concurrency:</strong> Concurrency level for overwriting during bulk inserts.</li>
|
||
<li><strong>Bulk Delete Concurrency:</strong> Concurrency level for bulk deletions.</li>
|
||
<li><strong>Setup Mode:</strong> Setup mode for the vector store.</li>
|
||
<li><strong>Pre Delete Collection:</strong> Option to delete the collection before setup.</li>
|
||
<li><strong>Metadata Indexing Include:</strong> Fields to include in metadata indexing.</li>
|
||
<li><strong>Metadata Indexing Exclude:</strong> Fields to exclude from metadata indexing.</li>
|
||
<li><strong>Collection Indexing Policy:</strong> Indexing policy for the collection.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="chroma">Chroma<a class="hash-link" aria-label="Direct link to Chroma" title="Direct link to Chroma" href="/components/vector-stores#chroma"></a></h3>
|
||
<p><code>Chroma</code> sets up a vector store using Chroma for efficient vector storage and retrieval within language processing workflows.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Collection Name:</strong> Name of the collection.</li>
|
||
<li><strong>Persist Directory:</strong> Directory to persist the Vector Store.</li>
|
||
<li><strong>Server CORS Allow Origins (Optional):</strong> CORS allow origins for the Chroma server.</li>
|
||
<li><strong>Server Host (Optional):</strong> Host for the Chroma server.</li>
|
||
<li><strong>Server Port (Optional):</strong> Port for the Chroma server.</li>
|
||
<li><strong>Server gRPC Port (Optional):</strong> gRPC port for the Chroma server.</li>
|
||
<li><strong>Server SSL Enabled (Optional):</strong> SSL configuration for the Chroma server.</li>
|
||
<li><strong>Input:</strong> Input data for creating the Vector Store.</li>
|
||
<li><strong>Embedding:</strong> Embeddings used for the Vector Store.</li>
|
||
</ul>
|
||
<p>For detailed documentation and integration guides, please refer to the <a href="https://python.langchain.com/docs/integrations/vectorstores/chroma" target="_blank" rel="noopener noreferrer">Chroma Component Documentation</a>.</p>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="chroma-search">Chroma Search<a class="hash-link" aria-label="Direct link to Chroma Search" title="Direct link to Chroma Search" href="/components/vector-stores#chroma-search"></a></h3>
|
||
<p><code>ChromaSearch</code> searches a Chroma collection for documents similar to the input text. It leverages Chroma to ensure efficient document retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Input:</strong> Input text for search.</li>
|
||
<li><strong>Search Type:</strong> Type of search, such as Similarity or MMR.</li>
|
||
<li><strong>Collection Name:</strong> Name of the Chroma collection.</li>
|
||
<li><strong>Index Directory:</strong> Directory where the Chroma index is stored.</li>
|
||
<li><strong>Embedding:</strong> Embedding model used for vectorization.</li>
|
||
<li><strong>Server CORS Allow Origins (Optional):</strong> CORS allow origins for the Chroma server.</li>
|
||
<li><strong>Server Host (Optional):</strong> Host for the Chroma server.</li>
|
||
<li><strong>Server Port (Optional):</strong> Port for the Chroma server.</li>
|
||
<li><strong>Server gRPC Port (Optional):</strong> gRPC port for the Chroma server.</li>
|
||
<li><strong>Server SSL Enabled (Optional):</strong> SSL configuration for the Chroma server.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="couchbase">Couchbase<a class="hash-link" aria-label="Direct link to Couchbase" title="Direct link to Couchbase" href="/components/vector-stores#couchbase"></a></h3>
|
||
<p><code>Couchbase</code> builds a Couchbase vector store from Data, streamlining the storage and retrieval of documents.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Embedding:</strong> Model used by Couchbase.</li>
|
||
<li><strong>Input:</strong> Documents or Data.</li>
|
||
<li><strong>Couchbase Cluster Connection String:</strong> Cluster Connection string.</li>
|
||
<li><strong>Couchbase Cluster Username:</strong> Cluster Username.</li>
|
||
<li><strong>Couchbase Cluster Password:</strong> Cluster Password.</li>
|
||
<li><strong>Bucket Name:</strong> Bucket identifier in Couchbase.</li>
|
||
<li><strong>Scope Name:</strong> Scope identifier in Couchbase.</li>
|
||
<li><strong>Collection Name:</strong> Collection identifier in Couchbase.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
</ul>
|
||
<p>For detailed documentation and integration guides, please refer to the <a href="https://python.langchain.com/docs/integrations/vectorstores/couchbase" target="_blank" rel="noopener noreferrer">Couchbase Component Documentation</a>.</p>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="couchbase-search">Couchbase Search<a class="hash-link" aria-label="Direct link to Couchbase Search" title="Direct link to Couchbase Search" href="/components/vector-stores#couchbase-search"></a></h3>
|
||
<p><code>CouchbaseSearch</code> leverages the Couchbase component to search for documents based on similarity metric.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Input:</strong> Search query.</li>
|
||
<li><strong>Embedding:</strong> Model used in the Vector Store.</li>
|
||
<li><strong>Couchbase Cluster Connection String:</strong> Cluster Connection string.</li>
|
||
<li><strong>Couchbase Cluster Username:</strong> Cluster Username.</li>
|
||
<li><strong>Couchbase Cluster Password:</strong> Cluster Password.</li>
|
||
<li><strong>Bucket Name:</strong> Bucket identifier.</li>
|
||
<li><strong>Scope Name:</strong> Scope identifier.</li>
|
||
<li><strong>Collection Name:</strong> Collection identifier in Couchbase.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="faiss">FAISS<a class="hash-link" aria-label="Direct link to FAISS" title="Direct link to FAISS" href="/components/vector-stores#faiss"></a></h3>
|
||
<p>The <code>FAISS</code> component manages document ingestion into a FAISS Vector Store, optimizing document indexing and retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Embedding:</strong> Model used for vectorizing inputs.</li>
|
||
<li><strong>Input:</strong> Documents to ingest.</li>
|
||
<li><strong>Folder Path:</strong> Save path for the FAISS index, relative to Langflow.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
</ul>
|
||
<p>For more details, see the <a href="https://faiss.ai/index.html" target="_blank" rel="noopener noreferrer">FAISS Component Documentation</a>.</p>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="faiss-search">FAISS Search<a class="hash-link" aria-label="Direct link to FAISS Search" title="Direct link to FAISS Search" href="/components/vector-stores#faiss-search"></a></h3>
|
||
<p><code>FAISSSearch</code> searches a FAISS Vector Store for documents similar to a given input, using similarity metrics for efficient retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Embedding:</strong> Model used in the FAISS Vector Store.</li>
|
||
<li><strong>Folder Path:</strong> Path to load the FAISS index from, relative to Langflow.</li>
|
||
<li><strong>Input:</strong> Search query.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="mongodb-atlas">MongoDB Atlas<a class="hash-link" aria-label="Direct link to MongoDB Atlas" title="Direct link to MongoDB Atlas" href="/components/vector-stores#mongodb-atlas"></a></h3>
|
||
<p><code>MongoDBAtlas</code> builds a MongoDB Atlas-based vector store from Data, streamlining the storage and retrieval of documents.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Embedding:</strong> Model used by MongoDB Atlas.</li>
|
||
<li><strong>Input:</strong> Documents or Data.</li>
|
||
<li><strong>Collection Name:</strong> Collection identifier in MongoDB Atlas.</li>
|
||
<li><strong>Database Name:</strong> Database identifier.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
<li><strong>MongoDB Atlas Cluster URI:</strong> Cluster URI.</li>
|
||
<li><strong>Search Kwargs:</strong> Additional search parameters.</li>
|
||
</ul>
|
||
<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>Ensure pymongo is installed for using MongoDB Atlas Vector Store.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="mongodb-atlas-search">MongoDB Atlas Search<a class="hash-link" aria-label="Direct link to MongoDB Atlas Search" title="Direct link to MongoDB Atlas Search" href="/components/vector-stores#mongodb-atlas-search"></a></h3>
|
||
<p><code>MongoDBAtlasSearch</code> leverages the MongoDBAtlas component to search for documents based on similarity metrics.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
<li><strong>Input:</strong> Search query.</li>
|
||
<li><strong>Embedding:</strong> Model used in the Vector Store.</li>
|
||
<li><strong>Collection Name:</strong> Collection identifier.</li>
|
||
<li><strong>Database Name:</strong> Database identifier.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
<li><strong>MongoDB Atlas Cluster URI:</strong> Cluster URI.</li>
|
||
<li><strong>Search Kwargs:</strong> Additional search parameters.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="pgvector">PGVector<a class="hash-link" aria-label="Direct link to PGVector" title="Direct link to PGVector" href="/components/vector-stores#pgvector"></a></h3>
|
||
<p><code>PGVector</code> integrates a Vector Store within a PostgreSQL database, allowing efficient storage and retrieval of vectors.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Input:</strong> Value for the Vector Store.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>PostgreSQL Server Connection String:</strong> Server URL.</li>
|
||
<li><strong>Table:</strong> Table name in the PostgreSQL database.</li>
|
||
</ul>
|
||
<p>For more details, see the <a href="https://python.langchain.com/docs/integrations/vectorstores/pgvector" target="_blank" rel="noopener noreferrer">PGVector Component Documentation</a>.</p>
|
||
<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>Ensure the PostgreSQL server is accessible and configured correctly.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="pgvector-search">PGVector Search<a class="hash-link" aria-label="Direct link to PGVector Search" title="Direct link to PGVector Search" href="/components/vector-stores#pgvector-search"></a></h3>
|
||
<p><code>PGVectorSearch</code> extends <code>PGVector</code> to search for documents based on similarity metrics.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Input:</strong> Search query.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>PostgreSQL Server Connection String:</strong> Server URL.</li>
|
||
<li><strong>Table:</strong> Table name.</li>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="pinecone">Pinecone<a class="hash-link" aria-label="Direct link to Pinecone" title="Direct link to Pinecone" href="/components/vector-stores#pinecone"></a></h3>
|
||
<p><code>Pinecone</code> constructs a Pinecone wrapper from Data, setting up Pinecone-based vector indexes for document storage and retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Input:</strong> Documents or Data.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
<li><strong>Namespace:</strong> Namespace used.</li>
|
||
<li><strong>Pinecone API Key:</strong> API key.</li>
|
||
<li><strong>Pinecone Environment:</strong> Environment settings.</li>
|
||
<li><strong>Search Kwargs:</strong> Additional search parameters.</li>
|
||
<li><strong>Pool Threads:</strong> Number of threads.</li>
|
||
</ul>
|
||
<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>Ensure the Pinecone API key and environment are correctly configured.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="pinecone-search">Pinecone Search<a class="hash-link" aria-label="Direct link to Pinecone Search" title="Direct link to Pinecone Search" href="/components/vector-stores#pinecone-search"></a></h3>
|
||
<p><code>PineconeSearch</code> searches a Pinecone Vector Store for documents similar to the input, using advanced similarity metrics.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
<li><strong>Input Value:</strong> Search query.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Index Name:</strong> Index identifier.</li>
|
||
<li><strong>Namespace:</strong> Namespace used.</li>
|
||
<li><strong>Pinecone API Key:</strong> API key.</li>
|
||
<li><strong>Pinecone Environment:</strong> Environment settings.</li>
|
||
<li><strong>Search Kwargs:</strong> Additional search parameters.</li>
|
||
<li><strong>Pool Threads:</strong> Number of threads.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="qdrant">Qdrant<a class="hash-link" aria-label="Direct link to Qdrant" title="Direct link to Qdrant" href="/components/vector-stores#qdrant"></a></h3>
|
||
<p><code>Qdrant</code> allows efficient similarity searches and retrieval operations, using a list of texts to construct a Qdrant wrapper.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Input:</strong> Documents or Data.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>API Key:</strong> Qdrant API key.</li>
|
||
<li><strong>Collection Name:</strong> Collection identifier.</li>
|
||
<li><strong>Advanced Settings:</strong> Includes content payload key, distance function, gRPC port, host, HTTPS, location, metadata payload key, path, port, prefer gRPC, prefix, search kwargs, timeout, URL.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="qdrant-search">Qdrant Search<a class="hash-link" aria-label="Direct link to Qdrant Search" title="Direct link to Qdrant Search" href="/components/vector-stores#qdrant-search"></a></h3>
|
||
<p><code>QdrantSearch</code> extends <code>Qdrant</code> to search for documents similar to the input based on advanced similarity metrics.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
<li><strong>Input Value:</strong> Search query.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>API Key:</strong> Qdrant API key.</li>
|
||
<li><strong>Collection Name:</strong> Collection identifier.</li>
|
||
<li><strong>Advanced Settings:</strong> Includes content payload key, distance function, gRPC port, host, HTTPS, location, metadata payload key, path, port, prefer gRPC, prefix, search kwargs, timeout, URL.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="redis">Redis<a class="hash-link" aria-label="Direct link to Redis" title="Direct link to Redis" href="/components/vector-stores#redis"></a></h3>
|
||
<p><code>Redis</code> manages a Vector Store in a Redis database, supporting efficient vector storage and retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Index Name:</strong> Default index name.</li>
|
||
<li><strong>Input:</strong> Data for building the Redis Vector Store.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Schema:</strong> Optional schema file (.yaml) for document structure.</li>
|
||
<li><strong>Redis Server Connection String:</strong> Server URL.</li>
|
||
<li><strong>Redis Index:</strong> Optional index name.</li>
|
||
</ul>
|
||
<p>For detailed documentation, refer to the <a href="https://python.langchain.com/docs/integrations/vectorstores/redis" target="_blank" rel="noopener noreferrer">Redis Documentation</a>.</p>
|
||
<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>Ensure the Redis server URL and index name are configured correctly. Provide a
|
||
schema if no documents are available.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="redis-search">Redis Search<a class="hash-link" aria-label="Direct link to Redis Search" title="Direct link to Redis Search" href="/components/vector-stores#redis-search"></a></h3>
|
||
<p><code>RedisSearch</code> searches a Redis Vector Store for documents similar to the input.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
<li><strong>Input Value:</strong> Search query.</li>
|
||
<li><strong>Index Name:</strong> Default index name.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Schema:</strong> Optional schema file (.yaml) for document structure.</li>
|
||
<li><strong>Redis Server Connection String:</strong> Server URL.</li>
|
||
<li><strong>Redis Index:</strong> Optional index name.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="supabase">Supabase<a class="hash-link" aria-label="Direct link to Supabase" title="Direct link to Supabase" href="/components/vector-stores#supabase"></a></h3>
|
||
<p><code>Supabase</code> initializes a Supabase Vector Store from texts and embeddings, setting up an environment for efficient document retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Input:</strong> Documents or data.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Query Name:</strong> Optional query name.</li>
|
||
<li><strong>Search Kwargs:</strong> Advanced search parameters.</li>
|
||
<li><strong>Supabase Service Key:</strong> Service key.</li>
|
||
<li><strong>Supabase URL:</strong> Instance URL.</li>
|
||
<li><strong>Table Name:</strong> Optional table name.</li>
|
||
</ul>
|
||
<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>Ensure the Supabase service key, URL, and table name are properly configured.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="supabase-search">Supabase Search<a class="hash-link" aria-label="Direct link to Supabase Search" title="Direct link to Supabase Search" href="/components/vector-stores#supabase-search"></a></h3>
|
||
<p><code>SupabaseSearch</code> searches a Supabase Vector Store for documents similar to the input.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
<li><strong>Input Value:</strong> Search query.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Query Name:</strong> Optional query name.</li>
|
||
<li><strong>Search Kwargs:</strong> Advanced search parameters.</li>
|
||
<li><strong>Supabase Service Key:</strong> Service key.</li>
|
||
<li><strong>Supabase URL:</strong> Instance URL.</li>
|
||
<li><strong>Table Name:</strong> Optional table name.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="vectara">Vectara<a class="hash-link" aria-label="Direct link to Vectara" title="Direct link to Vectara" href="/components/vector-stores#vectara"></a></h3>
|
||
<p><code>Vectara</code> sets up a Vectara Vector Store from files or upserted data, optimizing document retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Vectara Customer ID:</strong> Customer ID.</li>
|
||
<li><strong>Vectara Corpus ID:</strong> Corpus ID.</li>
|
||
<li><strong>Vectara API Key:</strong> API key.</li>
|
||
<li><strong>Files Url:</strong> Optional URLs for file initialization.</li>
|
||
<li><strong>Input:</strong> Optional data for corpus upsert.</li>
|
||
</ul>
|
||
<p>For more information, consult the <a href="https://python.langchain.com/docs/integrations/vectorstores/vectara" target="_blank" rel="noopener noreferrer">Vectara Component Documentation</a>.</p>
|
||
<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>If inputs or files_url are provided, they will be processed accordingly.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="vectara-search">Vectara Search<a class="hash-link" aria-label="Direct link to Vectara Search" title="Direct link to Vectara Search" href="/components/vector-stores#vectara-search"></a></h3>
|
||
<p><code>VectaraSearch</code> searches a Vectara Vector Store for documents based on the provided input.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
<li><strong>Input Value:</strong> Search query.</li>
|
||
<li><strong>Vectara Customer ID:</strong> Customer ID.</li>
|
||
<li><strong>Vectara Corpus ID:</strong> Corpus ID.</li>
|
||
<li><strong>Vectara API Key:</strong> API key.</li>
|
||
<li><strong>Files Url:</strong> Optional URLs for file initialization.</li>
|
||
</ul>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="weaviate">Weaviate<a class="hash-link" aria-label="Direct link to Weaviate" title="Direct link to Weaviate" href="/components/vector-stores#weaviate"></a></h3>
|
||
<p><code>Weaviate</code> facilitates a Weaviate Vector Store setup, optimizing text and document indexing and retrieval.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Weaviate URL:</strong> Default instance URL.</li>
|
||
<li><strong>Search By Text:</strong> Indicates whether to search by text.</li>
|
||
<li><strong>API Key:</strong> Optional API key for authentication.</li>
|
||
<li><strong>Index Name:</strong> Optional index name.</li>
|
||
<li><strong>Text Key:</strong> Default text extraction key.</li>
|
||
<li><strong>Input:</strong> Document or record.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Attributes:</strong> Optional additional attributes.</li>
|
||
</ul>
|
||
<p>For more details, see the <a href="https://python.langchain.com/docs/integrations/vectorstores/weaviate" target="_blank" rel="noopener noreferrer">Weaviate Component Documentation</a>.</p>
|
||
<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>Ensure Weaviate instance is running and accessible. Verify API key, index
|
||
name, text key, and attributes are set correctly.</p></div></div>
|
||
<hr>
|
||
<h3 class="anchor anchorWithHideOnScrollNavbar_WYt5" id="weaviate-search">Weaviate Search<a class="hash-link" aria-label="Direct link to Weaviate Search" title="Direct link to Weaviate Search" href="/components/vector-stores#weaviate-search"></a></h3>
|
||
<p><code>WeaviateSearch</code> searches a Weaviate Vector Store for documents similar to the input.</p>
|
||
<p><strong>Parameters:</strong></p>
|
||
<ul>
|
||
<li><strong>Search Type:</strong> Type of search, such as "Similarity" or "MMR".</li>
|
||
<li><strong>Input Value:</strong> Search query.</li>
|
||
<li><strong>Weaviate URL:</strong> Default instance URL.</li>
|
||
<li><strong>Search By Text:</strong> Indicates whether to search by text.</li>
|
||
<li><strong>API Key:</strong> Optional API key for authentication.</li>
|
||
<li><strong>Index Name:</strong> Optional index name.</li>
|
||
<li><strong>Text Key:</strong> Default text extraction key.</li>
|
||
<li><strong>Embedding:</strong> Model used.</li>
|
||
<li><strong>Attributes:</strong> Optional additional attributes.</li>
|
||
</ul>
|
||
<hr></div></article><nav class="pagination-nav docusaurus-mt-lg" aria-label="Docs pages"><a class="pagination-nav__link pagination-nav__link--prev" href="/components/helpers"><div class="pagination-nav__sublabel">Previous</div><div class="pagination-nav__label">Helpers</div></a><a class="pagination-nav__link pagination-nav__link--next" href="/components/embeddings"><div class="pagination-nav__sublabel">Next</div><div class="pagination-nav__label">Embeddings</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 class="table-of-contents__link toc-highlight" href="/components/vector-stores#astra-db">Astra DB</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#astra-db-search">Astra DB Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#chroma">Chroma</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#chroma-search">Chroma Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#couchbase">Couchbase</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#couchbase-search">Couchbase Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#faiss">FAISS</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#faiss-search">FAISS Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#mongodb-atlas">MongoDB Atlas</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#mongodb-atlas-search">MongoDB Atlas Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#pgvector">PGVector</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#pgvector-search">PGVector Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#pinecone">Pinecone</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#pinecone-search">Pinecone Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#qdrant">Qdrant</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#qdrant-search">Qdrant Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#redis">Redis</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#redis-search">Redis Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#supabase">Supabase</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#supabase-search">Supabase Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#vectara">Vectara</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#vectara-search">Vectara Search</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#weaviate">Weaviate</a></li><li><a class="table-of-contents__link toc-highlight" href="/components/vector-stores#weaviate-search">Weaviate Search</a></li></ul></div></div></div></div></main></div></div></div><div class="ms-fixed ms-bottom-4 ms-right-8 ms-z-[100] ms-flex ms-flex-col ms-items-end hover:ms-cursor-pointer"><div class="ms-relative ms-mb-4"><div style="background-color:#f6f6f6" class="ms-absolute -ms-bottom-1 ms-right-6 -ms-z-10 ms-h-4 ms-w-4 ms-rotate-45"></div><div style="background-color:#f6f6f6" class="ms-z-10 ms-flex ms-items-center ms-justify-center ms-rounded-lg ms-px-3 ms-py-2"><p style="color:#000000;margin:0" class="ms-text-sm">Hi, how can I help you?</p></div></div><div style="background-color:#f6f6f6" class="ms-flex ms-h-16 ms-w-16 ms-flex-col ms-items-center ms-justify-center ms-self-end ms-rounded-full ms-p-2 ms-transition"><div class="ms-rotate-0 ms-flex ms-h-full ms-w-full ms-transform ms-cursor-pointer ms-items-center ms-justify-center ms-rounded-full ms-transition-all ms-delay-75 ms-duration-100 ms-ease-in-out"><div style="color:#000000;font-size:22px;width:48px;height:48px;margin:0px;padding:0px;display:flex;align-items:center;justify-content:center;text-align:center"><img src="/img/chain.png" style="width:40px"></div></div></div><div></div></div></div>
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