langchain/templates/rag-supabase

RAG with Supabase

Supabase is an open-source Firebase alternative. It is built on top of PostgreSQL, a free and open-source relational database management system (RDBMS) and uses pgvector to store embeddings within your tables.

Use this package to host a retrieval augment generation (RAG) API using LangServe + Supabase.

Install Package

From within your langservehub project run:

poetry run poe add rag-supabase

Setup Supabase Database

Use these steps to setup your Supabase database if you haven't already.

1. Head over to https://database.new to provision your Supabase database.

2. In the studio, jump to the SQL editor and run the following script to enable pgvector and setup your database as a vector store:

   -- Enable the pgvector extension to work with embedding vectors
   create extension if not exists vector;
   
   -- Create a table to store your documents
   create table
     documents (
       id uuid primary key,
       content text, -- corresponds to Document.pageContent
       metadata jsonb, -- corresponds to Document.metadata
       embedding vector (1536) -- 1536 works for OpenAI embeddings, change as needed
     );
   
   -- Create a function to search for documents
   create function match_documents (
     query_embedding vector (1536),
     filter jsonb default '{}'
   ) returns table (
     id uuid,
     content text,
     metadata jsonb,
     similarity float
   ) language plpgsql as $$
   #variable_conflict use_column
   begin
     return query
     select
       id,
       content,
       metadata,
       1 - (documents.embedding <=> query_embedding) as similarity
     from documents
     where metadata @> filter
     order by documents.embedding <=> query_embedding;
   end;
   $$;
   

Setup Environment Variables

Since we are using SupabaseVectorStore and OpenAIEmbeddings, we need to load their API keys.

Create a .env file in the root of your project:

.env

SUPABASE_URL=
SUPABASE_SERVICE_KEY=
OPENAI_API_KEY=

To find your SUPABASE_URL and SUPABASE_SERVICE_KEY, head to your Supabase project's API settings.

• SUPABASE_URL corresponds to the Project URL
• SUPABASE_SERVICE_KEY corresponds to the service_role API key

To get your OPENAI_API_KEY, navigate to API keys on your OpenAI account and create a new secret key.

Add this file to your .gitignore if it isn't already there (so that we don't commit secrets):

.gitignore

.env

Install python-dotenv which we will use to load the environment variables into the app:

poetry add python-dotenv

Finally, call load_dotenv() in server.py.

app/server.py

from dotenv import load_dotenv

load_dotenv()