RAG Day 10 –> Back in n8n and learning one step at a time
Today I stayed in n8n again. As I mentioned earlier, I need to understand the basics here before I switch to Claude Code with a full RAG setup. So my goal for today was simple.I wanted to load a PDF from Google Drive into a vector database in Supabase. I created a new project in Supabase. From what I can see, you can have two active projects before the paid version starts, which is perfect for experimenting. I added the API key and URL to the Supabase node in n8n. Next I needed a table. So I followed the docs under “quickstart for setting up your vector store,” copied the SQL snippet and pasted it into the SQL editor. Unfortunately I got an error. I copied the code and the error message into Google Gemini, added a short description of what I wanted to do and it immediately generated a corrected version. I ran it again and the table was created. Really impressive. After that I added the data loader in n8n for chunking the document. I kept the default settings for now. Chunk size 1000 and overlap 200. For embeddings I connected the OpenAI embeddings model. Apart from a small code issue, which Gemini also helped me fix very quickly, everything worked. Then I ran the full flow. And it was amazing to see how the document was split into 77 items and then stored in the vector database. One by one in the table. A really successful day. The data is now in the vector store and I can honestly say that I learned something valuable again today.