Build a RAG Knowledge Chatbot with OpenAI, Google Drive, and Supabase

Description

🚀 Build Your Own Knowledge Chatbot Using Google Drive

Create a smart chatbot that answers questions using your Google Drive PDFs—perfect for support, internal docs, education, or research.

🛠️ Quick Setup Guide**
Step 1: Prerequisites

n8n instance (cloud or self-hosted)
Google Drive account (with PDFs)
Supabase account (vector database)
OpenAI API key
PostgreSQL database (for chat memory) else remove the node

Step 2: Supabase Setup
Create supabase account (its free)
Create a project
Copy the sql and paste it in supabase sql editor

-- 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 $$
#variable_conflict use_column
begin
return query
select
id,
content,
metadata,
1 - (documents.embedding <=> query_embedding) as similarity
from documents
where metadata @> filter
order by documents.embedding <=> query_embedding
limit match_count;
end;
$$;

Step 3: Import & Configure n8n Workflow

Import this template into n8n
Add credentials:
OpenAI API key
Google Drive OAuth2
Supabase URL & service key
PostgreSQL connection
Set your Google Drive folder ID in triggers

Step 4: Test & Use

Add a PDF to your Drive folder → check Supabase for new entries
Start the workflow and chat → ask questions about your documents. "What can you help me with?"
Multi-turn chat → context is maintained per user

⚡ Features

Auto-syncs new/updated PDFs from Google Drive
Extracts, chunks, and vectorizes text
Finds relevant info and answers questions
Maintains chat history per user

📝 Troubleshooting
Check folder permissions & IDs if no docs found
Verify API keys & Supabase setup for errors
Ensure PostgreSQL is connected for chat memory

Tags: RAG, Chatbot, Google Drive, Supabase, OpenAI, n8n
Setup Time: ~20 minutes