Spring AI Developer Guide: Building Intelligent Applications with Java, Spring Boot, and Large Language Models (Spring AI Developer Series) - J. Klat, Eric
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Spring AI Developer Guide: Building Intelligent Applications with Java, Spring Boot, and Large Language Models (Spring AI Developer Series)
J. Klat, Eric
Synopsis "Spring AI Developer Guide: Building Intelligent Applications with Java, Spring Boot, and Large Language Models (Spring AI Developer Series)"
Artificial intelligence is transforming software development, but Java developers do not need to leave the Spring ecosystem to build intelligent applications. Spring AI Developer Guide provides a practical, developer-focused introduction to building AI-powered applications with Java and Spring Boot. Rather than approaching AI from a research or data-science perspective, this book focuses on the engineering skills developers need to integrate modern AI capabilities into applications they already know how to build. Starting with the fundamentals of large language models, readers learn how tokens, context, embeddings, transformers, and model interactions affect application design. The book then moves into practical Spring AI development, covering model integration, the ChatClient API, prompt engineering, structured responses, embeddings, vector stores, and retrieval-augmented generation. Throughout the book, concepts are connected to real application-development scenarios, helping readers understand not only how to use AI APIs, but also why particular architectural and implementation choices matter. Inside the Book, You Will Explore:The foundations of large language models and modern AI applications How Spring AI fits into the Spring Boot development ecosystem Configuring and interacting with AI models from Java applications Building conversational applications with the ChatClient API Designing effective system, user, and reusable prompts Working with structured outputs and AI-generated responses Understanding embeddings and semantic similarity Building retrieval-augmented generation applications Processing, chunking, embedding, and retrieving documents Working with vector stores and persistent AI knowledge Connecting AI capabilities to real Spring Boot services Designing maintainable and extensible AI application architectures Testing and evaluating AI-powered application behavior Preparing AI applications for reliable real-world use By the end of the book, you will have a solid foundation for designing and implementing intelligent Spring Boot applications and the practical knowledge required to continue into more advanced AI engineering patterns. Spring AI Developer Guide is ideal for Java developers, Spring Boot engineers, backend developers, software architects, and experienced programmers who want a practical path into AI application development without abandoning the Java ecosystem.
