Supabase

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 Supabase bundle.

Supabase vector store

The Supabase component reads and writes to Supabase vector stores using an instance of SupabaseVectorStore.

<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. :::

Supabase 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 Supabase documentation or inspect component code.

Name	Type	Description
supabase_url	String	Input parameter. The URL of the Supabase instance.
supabase_service_key	SecretString	Input parameter. The service key for Supabase authentication.
table_name	String	Input parameter. The name of the table in Supabase.
query_name	String	Input parameter. The name of the query to use.
search_query	String	Input parameter. The query for similarity search.
ingest_data	Data	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.