Chat With Your Images Using AI - Vectorize.io RAG Python Tutorial

Learn to build an AI-powered system that can analyze and chat with images, PDFs, and receipts using Vectorize.io and Python in this 15-minute tutorial. Discover how to leverage Vectorize.io's free AI platform to automatically extract and organize data from visual documents without manual parsing, then create a conversational interface using OpenAI's API. Master the process of setting up RAG (Retrieval-Augmented Generation) pipelines specifically designed for image-based data extraction, including receipt parsing with structured schemas. Build practical applications such as spending summarization tools, suspicious transaction detection systems, and automated data export functionality to CSV and JSON formats. Explore the complete workflow from initial platform setup and pipeline creation through advanced AI agent development, including OpenAI integration, tool definition, and Python implementation. Gain hands-on experience with real receipt datasets while learning to create sophisticated AI agents capable of analyzing financial documents, categorizing expenses, and identifying unusual purchasing patterns through natural language conversations.

Syllabus

00:00 Introducing Vectorize.io’s image‑based RAG feature
01:20 How to sign up and create your RAG pipeline on Vector.io
02:22 Choosing the image extractor and receipt schema for parsing
04:00 Chatting with uploaded receipts in the Vector.io sandbox
06:10 Connecting OpenAI, defining tools, and building the AI agent
08:53 Installing dependencies and launching the Python agent
09:41 Summarizing your spending by category from receipt data
12:04 Detecting unusual or suspicious transactions in history
13:15 Exporting analysis results to CSV and viewing the file