Create RAG-ready knowledge bases from websites using Apify, Gemini & Supabase
Convert any website into a searchable vector database for AI chatbots. Submit a URL, choose scraping scope, and this workflow handles everything: scraping, cleaning, chunking, embedding, and storing in Supabase. What it does - Scrapes websites using Apify (3 modes: full site unlimited, full site limited, single URL) - Cleans content (removes navigation, footer, ads, cookie banners, etc) - Chunks text (800 chars, markdown-aware) - Generates embeddings (Google Gemini, 768 dimensions
At a glance
Create RAG-ready knowledge bases from websites using Apify, Gemini & Supabase is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects Gemini. It's free to download. Follow the 5-step import below to go live in minutes.
- Platform
- n8n
- Connects
- Gemini
- Modules
- 13
- Price
- Free
- Version
- v1.0

About this workflow
Convert any website into a searchable vector database for AI chatbots. Submit a URL, choose scraping scope, and this workflow handles everything: scraping, cleaning, chunking, embedding, and storing in Supabase. What it does - Scrapes websites using Apify (3 modes: full site unlimited, full site limited, single URL) - Cleans content (removes navigation, footer, ads, cookie banners, etc) - Chunks text (800 chars, markdown-aware) - Generates embeddings (Google Gemini, 768 dimensions) - Stores in Supabase vector database Requirements - Apify account + API token - Supabase database with pgvector extension - Google Gemini API key Setup 1. Create Supabase documents table with embedding column (vector 768). Run this SQL query in your Supabase project to enable the vector store setup 2. Add your Apify API token to all three "Run Apify Scraper" nodes 3. Add Supabase and Gemini credentials 4. Test with small site (5-10 pages) or single page/URL first Next steps Connect your vector store to an AI chatbot for RAG-powered Q&A, or build semantic search features into your apps. Tip: Start with page limits to test content quality before full-site scraping. Review chunks in Supabase and adjust Apify filters if needed for better vector embeddings. --- Sample Outputs Apify actor "runs" in Apify Dashboard from this workflow Supabase docuemnts table with scraped website content ingested in chunks with vector embeddings
How to import this n8n workflow
- 1
Download the workflow JSON file after purchase.
- 2
Open n8n → click the menu → Import from File.
- 3
Select the downloaded JSON and import.
- 4
Set up credentials for each node that requires them.
- 5
Click Execute Workflow to test, then activate.
Setup guide
Setup guide included
Purchase to unlock the full step-by-step guide
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- JSON blueprint — instant download
- Setup guide PDF included
- 5 downloads · valid 30 days
- Works with n8n
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