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This book shows you step-by-step and example-by-example how to build sites and applications that take advantage of large language models (LLMs) like GPT, Claude, and Llama. Written especially for web developers comfortable with React or Next.js, this book introduces the tools and techniques you need to add sophisticated AI features like Retrieval Augmented Generation (RAG), document summarization, chatbots, and more to your web-based projects.
It guides you through AI development using only JavaScript and other common web dev skills–no Python or Machine Learning experience required. You’ll learn by working with full-scale AI projects that solve actual business problems. You’ll soon be delivering user-friendly, efficient interfaces that make the absolute best use of AI tech.
In Build AI-Enhanced Web Apps you'll learn how to:
• Integrate AI models into React and Next.js applications
• Implement streaming responses and real-time AI interactions
• Manage conversation history and context in chat applications
• Implement LangChain.js for complex AI workflows and reasoning
• Build a web application for summarizing documents using LangChain.js
• Utilize Retrieval-Augmented Generation (RAG) systems for knowledge management
• Develop an AI-powered interview preparation system with voice feedback
About the technology
The users have spoken! Agents, personalized responses, and other LLM-powered features are required in modern web applications. Build AI-Enhanced Web Apps presents the end-to-end architecture of AI web apps, including UI, backend infrastructure, data processing, API integration, deployment, and scaling, with examples and language perfect for professional web developers.
About the book
This accessible book shows you how to ship real AI features—not just toy demos—using a JavaScript stack you already know: React for UI, Next.js for backend integration, and the Vercel AI SDK to connect to LLMs like Gemini and GPT. In it, you’ll acquire the skills you need to complete two portfolio-ready projects: a voice-based interview assistant and a RAG-powered corporate knowledge system. You’ll also learn how to design workflows that balance latency, cost, and UX and implement responsible guardrails for security, quality control, hallucinations, and bias.
What's inside
• Build AI features using a professional stack
• Ship production-ready features
• Learn from concrete projects
About the reader
For web developers familiar with JavaScript and React.
About the author
Theo Despoudis is a Senior Engineer at WP Engine specializing in AI-powered search and headless WordPress. He is an expert in integrating LLMs, RAG, and Vercel AI SDK into React and Next.js apps.
Table of Contents
Part 1
1 Using generative AI in web apps
2 Building your first generative AI web application
3 Connecting AI models with the Vercel AI SDK
4 Managing conversation and state in your application
Part 2
5 Prompt engineering in web applications
6 Building AI workflows with LangChain.js
7 Document summarization and RAG with LangChain.js
8 Testing and debugging techniques
9 Deployment and security
Part 3
10 Building an AI interview assistant: Project walk-through
11 Building an AI RAG agent: Project walk-through
Part 4
12 Integrating web apps with the Model Context Protocol
A Running the examples
