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In this quick tutorial I show you how Google’s open-source LangExtract converts messy PDFs, HTML, and DOC files into clean knowledge graphs that plug straight into Retrieval-Augmented Generation (RAG) workflows. Watch me run entity- and relationship-extraction with a long-context LLM like Gemini, build custom schemas, and visualize everything in seconds. If you’re working on AI agents, vector databases, or search pipelines, this is the fastest way to make your data Graph-RAG ready.
Website: https://developers.googleblog.com/en/introducing-langextract-a-gemini-powered-information-extraction-library/
Github: https://github.com/google/langextract
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00:00 Introduction to Lang Extract
00:39 Overview of Lang Extract Capabilities
01:21 Setting Up Lang Extract
03:03 Basic Example: Entity Extraction
05:48 Advanced Example: Relationship Extraction
10:02 Creating Knowledge Graphs
11:29 Conclusion and Additional Resources Read More Prompt Engineering
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