Satej Kumar Sahu

Generative Ai-Driven API Development with Java

Leveraging Generative AI with Spring Boot and Quarkus Frameworks

• Broschiertes Buch

Produktbeschreibung

This is the first hands-on guide that takes you from a simple “Hello, LLM” to production-ready microservices, all within the JVM. You’ll integrate hosted models such as OpenAI’s GPT-4o, run alternatives with Ollama or Jlama, and embed them in Spring Boot or Quarkus apps for cloud or on-pre deployment. You’ll learn how prompt-engineering patterns, Retrieval-Augmented Generation (RAG), vector stores such as Pinecone and Milvus, and agentic workflows come together to solve real business problems. Robust test suites, CI/CD pipelines, and security guardrails ensure your AI features reach production safely, while detailed observability playbooks help you catch hallucinations before your users do. You’ll also explore DJL, the future of machine learning in Java.  This book delivers runnable examples, clean architectural diagrams, and a GitHub repo you can clone on day one. Whether you’re modernizing a legacy platform or launching a green-field service, you’ll have a roadmap for adding state-of-the-art generative AI without abandoning the language—and ecosystem—you rely on. What You Will Learn * Establish generative AI and LLM foundations * Integrate hosted or local models using Spring Boot, Quarkus, LangChain4j, Spring AI, OpenAI, Ollama, and Jlama * Craft effective prompts and implement RAG with Pinecone or Milvus for context-rich answers * Build secure, observable, scalable AI microservices for cloud or on-prem deployment * Test outputs, add guardrails, and monitor performance of LLMs and applications * Explore advanced patterns, such agentic workflows, multimodal LLMs, and practical image-processing use cases  

Produktdetails

• Verlag: Apress / Apress L.P.
• Erscheinungstermin: 10. November 2025
• Englisch
• ISBN-13: 9798868816086
• Artikelnr.: 74258177

Autorenporträt

Satej Kumar Sahu is a Principal Engineer at Zalando SE with 15 years of hands-on experience designing large-scale, data-intensive systems for global brands including Boeing, Adidas, and Honeywell. A specialist in software architecture, big-data pipelines, and applied machine learning, he has shepherded multiple projects from whiteboard sketches to production deployments serving millions of users. Satej has been working with Large Language Models since their earliest open-source releases, piloting Retrieval-Augmented Generation (RAG) and agentic patterns long before they became industry buzzwords. He is the author of two previous programming books—Building Secure PHP Applications and PHP 8 Basics—and is a frequent speaker at developer conferences and meet-ups across the world. When he isn’t translating cutting-edge AI research into practical code, you’ll find him mentoring engineering teams, contributing to open-source projects, or tinkering with the newest transformer models in his home lab.

Inhaltsangabe

1. Introduction to Generative AI and LLMs.
2. Learning the Basics of Interacting with LLMs.
3. Self
Hosting LLMs.
4. Getting Started with LangChain4j.
5. Integrating LLMs with Java Applications.
6. Integrating Contextual Information into LLM Ecosystems.
7. Integrating Spring AI Library with Spring Boot.
8. Prompt Engineering Using Spring AI.
9. Tools in Spring AI.
10. Agentic AI.
11. Introduction to Transformers.
12. Evaluation and Testing of LLM Applications.
13. Generative AI Using AWS.
14. MCP Protocol.
15. Building Generative AI Applications Using Quarkus.
16. Hosting LLMs Using Java.
17. Multi
Modality in LLMs.
18. Machine Learning in Java.
19. Observability in LLM Applications.
20. Architctures of Tomorrow: Navigating Trends in LLMs.