Generative AI-Driven Application Development with Java

Build AI-powered API services and microservices that are both scalable and high-performing. Through detailed examples and best practices, this comprehensive guide will help you master LLM and AI integration using two popular Java frameworks—Spring Boot and Quarkus.

The book begins by introducing the core concepts of generative AI and LLMs, emphasizing their critical role in modern software development. Next, you’ll explore LangChain4j in depth, from installation to advanced usage. You will learn how to effortlessly connect to multiple LLMs, manage embeddings and vector stores (Pinecone and Milvus), and implement advanced AI patterns, all through a unified API that streamlines the development process. Beyond the basics, you’ll explore advanced patterns such as AI services, Retrieval-Augmented Generation (RAG), and managing complex chat memory states.

Ensuring that your AI-powered applications are reliable and production-ready is essential. With this book, you will learn how to effectively test, deploy, and maintain LLM-integrated services, with a focus on best practices for security, scalability, and continuous integration.

What You Will Learn

• Integrate generative AI and LLMs into Java for smarter, responsive apps
• Use LangChain4j to bridge complex LLMs with Java applications
• Create scalable AI services using Spring Boot and Quarkus with practical examples
• Apply Retrieval-Augmented Generation and other patterns to real-world AI apps
• Boost AI with vector-based search by integrating Pinecone or Milvus
• Prepare for future trends to remain competitive in the industry by learning emerging tools and techniques

Who This Book Is For

Java developers and software engineers in enterprise settings seeking to integrate AI into their applications; also valuable for AI enthusiasts, data scientists, educators, and architects looking to implement AI in Java