The integration of Large Language Models (LLMs) into enterprise Java applications has historically been complex, requiring heavy boilerplate code and fragmented libraries. Spring AI solves this problem by providing a streamlined, idiomatic framework designed specifically for Java developers.
"Spring AI in Action" is the first authoritative guide to Spring's new AI extension, written by Craig Walls—a principal engineer on the Spring team and the bestselling author of Spring in Action . The book teaches you how to build AI applications natively using Spring AI and Spring Boot, without abandoning the Java ecosystem. No Python, no problem.
What are you building? (Chatbot, document search, automated data extractor?)
Spring Boot applications demonstrating AI integration. spring ai in action pdf github link
To get the most out of the book, hands-on code is essential. The author, , has provided the official code repository, which is a key resource for the "in action" part of the title. Official GitHub Link: habuma/spring-ai-in-action-samples . What to Expect in the Repository
Harnessing Enterprise AI: A Complete Guide to Spring AI (With GitHub Resources)
You can purchase the Spring AI in Action eBook on Manning to get the PDF, ePub, and Kindle versions. The integration of Large Language Models (LLMs) into
When searching for the , developers are usually looking for two things: the book's official code samples or the digital publication. The Official GitHub Repository
<repositories> <repository> <id>spring-milestones</id> <name>Spring Milestones</name> <url>https://repo.spring.io/milestone</url> <snapshots> <enabled>false</enabled> </snapshots> </repository> </repositories>
Write code once and switch LLM providers via simple configuration changes. The book teaches you how to build AI
Unified interface supporting OpenAI, Azure OpenAI, Amazon Bedrock, Google Vertex AI, and Hugging Face.
Another version, spring-ai-in-action-examples , hosts code as it appeared specifically at the time of printing. 🚀 Key Features of the Guide The book and its GitHub samples cover these features:
Once comfortable, dive into (7+ use cases), ThomasVitale/llm-apps-java-spring-ai (production-quality examples), and alibaba/spring-ai-alibaba (enterprise-grade agent framework).
Since Spring AI is evolving fast, always check the GitHub Issues on the main repo ( github.com/spring-projects/spring-ai ) if you run into dependency conflicts.
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