LangExtract: Turn Messy Text into Graph-RAG Insights скачать в хорошем качестве

LangExtract: Turn Messy Text into Graph-RAG Insights

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/... Github: https://github.com/google/langextract Website: https://engineerprompt.ai/ RAG Beyond Basics Course: https://prompt-s-site.thinkific.com/c... Let's Connect: 🦾 Discord:   / discord   ☕ Buy me a Coffee: https://ko-fi.com/promptengineering |🔴 Patreon:   / promptengineering   💼Consulting: https://calendly.com/engineerprompt/c... 📧 Business Contact: engineerprompt@gmail.com Become Member: http://tinyurl.com/y5h28s6h 💻 Pre-configured localGPT VM: https://bit.ly/localGPT (use Code: PromptEngineering for 50% off). Signup for Newsletter, localgpt: https://tally.so/r/3y9bb0 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