AI agent to chat with files in Supabase Storage

Video Guide

I prepared a detailed guide explaining how to set up and implement this scenario, enabling you to chat with your documents stored in Supabase using n8n.

[](https://www.youtube.com/watch?v=glWUkdZe3w)

[Youtube Link](https://www.youtube.com/watch?v=glWUkdZe3w)

Who is this for? This workflow is ideal for researchers, analysts, business owners, or anyone managing a large collection of documents. It's particularly beneficial for those who need quick contextual information retrieval from text-heavy files stored in Supabase, without needing additional services like Google Drive.

What problem does this workflow solve? Manually retrieving and analyzing specific information from large document repositories is time-consuming and inefficient. This workflow automates the process by vectorizing documents and enabling AI-powered interactions, making it easy to query and retrieve context-based information from uploaded files.

What this workflow does The workflow integrates Supabase with an AI-powered chatbot to process, store, and query text and PDF files. The steps include: - Fetching and comparing files to avoid duplicate processing. - Handling file downloads and extracting content based on the file type. - Converting documents into vectorized data for contextual information retrieval. - Storing and querying vectorized data from a Supabase vector store.

1. File Extraction and Processing: Automates handling of multiple file formats (e.g., PDFs, text files), and extracts document content. 2. Vectorized Embeddings Creation: Generates embeddings for processed data to enable AI-driven interactions. 3. Dynamic Data Querying: Allows users to query their document repository conversationally using a chatbot.