This tutorial outlines how to build a Python script for RAG-Anything, enabling multi-modal RAG across PDFs containing text, images, tables, and equations to answer natural language questions. It details the setup and use of a multimodal knowledge-graph pipeline, including installation instructions and OpenAI API usage.
This content analyzes different approaches—Regex, Template Matching, and AI—for structured data extraction from PDFs, specifically focusing on the complexities of invoice processing. It discusses how Regex works for controlled formats but quickly fails with layout changes or diverse vendor documents.
The title "My Agent Can't Read a PDF?" by Jerry Liu at AI Dev 26 x SF addresses a common and frustrating challenge in AI agent development: the difficulty in processing and extracting information from PDF documents. This highlights a gap in current AI capabilities to effectively handle complex data formats.
