Turn ANY File into LLM Knowledge in SECONDS
One of the biggest challenges we face with LLMs is their knowledge is too general and limited for anything new. That’s why RAG is so popular - it’s a method for providing an LLM with external knowledge you curate so it can become an expert on your data. The problem is, that “curate” step can be very difficult if you have data in a lot of different formats. That is where Docling comes in! Docling is an open source data pipeline and chunking framework specifically designed to handle all your data formats and prepare them for LLMs. In this video, I show you how to use Docling to extract text from virtually ANY file type and chunk it perfectly for a RAG system. Plus at the end, I even show you a RAG AI agent I built that uses Docling for the RAG engine which you can use as a template right now (link below)! ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - If you want to see Docling in action in a production ready RAG pipeline and AI agent, check out Dynamous (Docling workshop this Friday!): https://dynamous.ai ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - Docling RAG Agent and examples: https://github.com/coleam00/ottomator-agents/tree/main/docling-rag-agent - Docling GitHub repository: https://github.com/docling-project/docling - Docling documentation: https://docling-project.github.io/docling/ ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 00:00 - Introducing Docling - RAG Made Easy 01:36 - Getting Started with Docling 03:33 - Dynamous Event - Full RAG Pipeline with Docling 04:04 - Example #1 - PDF Parsing 06:26 - Example #2 - Working with Different File Types 08:24 - Example #3 - Extract Text from Audio Files 10:30 - Example #4 - Hybrid Chunking 14:26 - More Docling Resources (So Many Examples!) 15:41 - Grand Finale - Docling RAG AI Agent 20:36 - Final Thoughts ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Join me as I push the limits of what is possible with AI. I'll be uploading videos every week - Wednesdays at 7:00 PM CDT!
