LangChain for JavaScript developers: How to integrate LLMs into Javascript web appsКНИГИ » ПРОГРАММИНГ
Название: LangChain for javascript developers: How to integrate LLMs into javascript web apps Автор: Daniel Nastase Издательство: Leanpub Год: 2024-07-28 Страниц: 120 Язык: английский Формат: pdf (true) epub Размер: 10.1 MB
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 is a framework designed to simplify the creation of applications that integrate Large Language Models (LLMs). LangChain provides all the AI integration building blocks in one framework. It offers a modular, flexible, and scalable architecture that is easy to maintain. 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. 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.
What prerequisites do I need to have before taking this course? The examples are using Next.js and React. You don't need to be an expert but you will need a very basic understanding of how React works.
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