---
title: Supabase
slug: /bundles-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**](/components-bundle-components) 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](/chat-with-rag).
:::

### 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](https://supabase.com/docs/guides/ai) or inspect [component code](/concepts-components#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         | 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.     |