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In this video, I show you how to use LangExtract to generate high-quality metadata for your Retrieval Augmented Generation (RAG) system. By extracting structured data from unstructured documents, we can filter results more effectively and drastically improve retrieval accuracy. I’ll walk you through a complete example, from setting up LangExtract to integrating metadata filtering into your RAG pipeline.
LangExtract Video: https://youtu.be/dPL2vRDunMw
Github: https://github.com/PromtEngineer/LangExtract-RAG.git
Website: https://engineerprompt.ai/
RAG Beyond Basics Course:
https://prompt-s-site.thinkific.com/courses/rag
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00:00 Metadata problem with RAG
00:45 Using Lang Extract for Metadata Extraction
01:46 Building the Retrieval Augmented Generation System
02:22 Setting Up the Environment and Sample Data
03:27 Creating the Metadata Extraction Pipeline
06:56 Implementing Metadata Filters in Vector Store
08:51 Running the Example and Viewing Results Read More Prompt Engineering
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