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LangChain for JavaScript Developers: Integrate LLMs into web applications - a beginner's guide
Get to grips with the LangChain framework from theory to production-ready applications. Code examples are regularly updated to keep you abreast of the latest LangChain and LangGraph changes.
Purchase of the print or Kindle book includes a free PDF eBook and all code samples.
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 get gain a good understanding of how all the components work together.
I’ve been doing JavaScript for almost 20 years, and this 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
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
models and prompt templates
output parsers,
streaming data
conversation memory
agents & tools
RAG - Retrieval Augmented Generation
debugging responses and more.
Purchase of the print or Kindle book includes a free PDF eBook and all code samples.
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 get gain a good understanding of how all the components work together.
I’ve been doing JavaScript for almost 20 years, and this 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
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
models and prompt templates
output parsers,
streaming data
conversation memory
agents & tools
RAG - Retrieval Augmented Generation
debugging responses and more.
147 pages, Kindle Edition
Published June 14, 2024
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