General information

Nastase D. LangChain for JavaScript developers. How to integrate LLMs...2024

Download this torrent!

To start this P2P download, you have to install a BitTorrent client like qBittorrent

Category: Other
Total size: 4.88 MB
Added: 2025-03-10 23:38:58

Share ratio: 5 seeders, 4 leechers
Info Hash: 9AC0C4B0E3C042B8993481ACEC57683A612F6DE3
Last updated: 4.6 hours ago

Description:

Textbook in PDF format LangChain for JavaScript developers – how to integrate LLMs into JavaScript apps by building 5 real examples using LangChain, Next.js and React. LangChain for JavaScript developers is a practical beginner’s workshop for integrating LLMs into JS applications. Learn by building 5 real LLM-powered apps with LangChain, Next.js, and React. The AI Engineer, responsible for integrating AI features into traditional software applications, will be one of the most in-demand roles in the coming years. In fact, there is a high chance that AI Engineers will outnumber ML Engineers in the near future. LangChain is a perfect gateway to starting your AI Engineering journey. LangChain serves as the orchestrator that connects nearly everything in the AI-Webapp integration system. Starting from this point, you can gain a good understanding of how all the components work together. Not yet ready to buy? Let’s keep in touch I’ve been doing JavaScript for almost 20 years, and this book emerged from my struggle to reconcile the undeniable wave of AI Technologies with classic web development. You can read the full story here. In this short course, we take a fun, hands-on, and pragmatic approach to learning how to build LLM-powered apps using LangChain. We will build the following five examples using LangChain, Next.js, and React: The Story Maker Tea Wikipedia app Geography Trivia game Documents Researcher app AI Agent chatbot The goal of this course is to teach you LangChain development in a manageable way without overwhelming you. Some of the topics we will cover include: models and prompt templates output parsers, streaming data conversation memory agents & tools RAG – Retrieval Augmented Generation debugging responses and more