# Supabase
## Prerequisite
1. Register an account for [Supabase](https://supabase.com/)
2. Click **New project**\\
3. Input required fields\
**Name**, name of the project to be created. (e.g. LangFlux)\
**Database** Password, password to your postgres database. (e.g. click **Generate a password**)\\
4. Click **Create new project** and wait for the project to finish setting up
5. Click **SQL Editor**\\
6. Click **New query**\\
7. Copy & Paste [query ](https://js.langchain.com/docs/modules/indexes/vector_stores/integrations/supabase#create-a-table-and-search-function-in-your-database)and run it by `Ctrl + Enter` or click **RUN**\
**Table name**: documents\
**Query name**: match\_documents
```plsql
-- Enable the pgvector extension to work with embedding vectors
create extension vector;
-- Create a table to store your documents
create table documents (
id bigserial primary key,
content text, -- corresponds to Document.pageContent
metadata jsonb, -- corresponds to Document.metadata
embedding vector(1536) -- 1536 works for OpenAI embeddings, change if needed
);
-- Create a function to search for documents
create function match_documents (
query_embedding vector(1536),
match_count int DEFAULT null,
filter jsonb DEFAULT '{}'
) returns table (
id bigint,
content text,
metadata jsonb,
similarity float
)
language plpgsql
as $$
#variable_conflict use_column
begin
return query
select
id,
content,
metadata,
1 - (documents.embedding <=> query_embedding) as similarity
from documents
where metadata @> filter
order by documents.embedding <=> query_embedding
limit match_count;
end;
$$;
```
## Setup
1. Click **Project Settings**\\
2. Get your **Project URL & API Key**
3. Copy & Paste each details (*API Key, URL, Table Name, Query Name*) into **Supabase Upsert Document** node or **Supabase Load Existing** node\
4. **Document** can be connected with any node under [**Document Loader**](/integrations/document-loaders.md) category
5. **Embeddings** can be connected with any node under [**Embeddings** ](/integrations/embeddings.md)category
## Resources
* [LangChain JS Supabase](https://js.langchain.com/docs/modules/indexes/vector_stores/integrations/supabase)
* [Supabase Blog Post](https://supabase.com/blog/openai-embeddings-postgres-vector)
---
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