Upstash

import Icon from "@site/src/components/icon"; import PartialParams from '@site/docs/_partial-hidden-params.mdx'; import PartialConditionalParams from '@site/docs/_partial-conditional-params.mdx'; import PartialVectorSearchResults from '@site/docs/_partial-vector-search-results.mdx'; import PartialVectorStoreInstance from '@site/docs/_partial-vector-store-instance.mdx';

<Icon name="Blocks" aria-hidden="true" /> Bundles contain custom components that support specific third-party integrations with Langflow.

This page describes the components that are available in the Upstash bundle.

Upstash vector store

The Upstash component reads and writes to Upstash vector stores using an instance of UpstashVectorStore.

<details> <summary>About vector store instances</summary> <PartialVectorStoreInstance /> </details> <PartialVectorSearchResults />

:::tip For a tutorial using a vector database in a flow, see Create a vector RAG chatbot. :::

Upstash vector store parameters

You can inspect a vector store component's parameters to learn more about the inputs it accepts, the features it supports, and how to configure it.

<PartialParams /> <PartialConditionalParams />

For information about accepted values and functionality, see the Upstash documentation or inspect component code.

Name	Type	Description
index_url	String	Input parameter. The URL of the Upstash index.
index_token	SecretString	Input parameter. The token for the Upstash index.
text_key	String	Input parameter. The key in the record to use as text.
namespace	String	Input parameter. The namespace for the index.
search_query	String	Input parameter. The query for similarity search.
metadata_filter	String	Input parameter. Filter documents by metadata.
ingest_data	JSON	Input parameter. The data to be ingested into the vector store.
embedding	Embeddings	Input parameter. The embedding function to use.
number_of_results	Integer	Input parameter. The number of results to return in search.