ISBN: 9798172045707 - advanced spring ai engineering: build rag systems, ai agents, and tool-integrated applications in java: 2 (6 risultati)

Taschenbuch. Condizione: Neu. Neuware.

Paperback. Condizione: new. Paperback. Anyone can call a chat API. Engineering an intelligent system that reasons, retrieves, and acts reliably is a different discipline entirely.You've built your first AI feature. It works in a demo, with clean inputs, at low volume. Now your organization wants more: agents that can actually do things, retrieval that doesn't fall apart at scale, and tools that coordinate without silently breaking each other. Welcome to the point where "AI integration" stops being enough, and "AI systems architecture" becomes the job.Advanced Spring AI Engineering is where practitioners become systems engineers.This book goes deep into the architecture that separates fragile AI demos from genuinely intelligent platforms: hybrid search combining semantic and keyword retrieval, re-ranking and query expansion, autonomous agents capable of multi-step reasoning, tool orchestration with Spring AI's atTool annotation, and the Model Context Protocol (MCP) for building distributed, interoperable AI ecosystems.Inside, you'll learn how to: *Architect advanced RAG pipelines with hybrid search, re-ranking, and intelligent chunking strategies*Engineer embeddings at scale model selection, dimensionality trade-offs, drift detection, and versioning*Design AI agents that plan, reason, and execute multi-step tasks not just answer questions*Build reliable tool-calling systems using Spring AI's atTool annotation, with dependency resolution and failure recovery*Implement the Model Context Protocol (MCP) to expose and consume AI capabilities across service boundaries*Integrate AI cleanly into microservices, event-driven systems, and domain-driven architectures*Build observability and continuous evaluation frameworks that catch hallucinations and quality regressions before your users doEvery concept is grounded in real architectural trade-offs, not idealized best practices when RAG beats fine-tuning, when reactive agents beat planning agents, when hybrid search is worth the added latency, and when it isn't. Every example is production-oriented Spring Boot and Spring AI code, built around a single evolving enterprise knowledge platform that grows more sophisticated with every chapter.This is Book 2 of 3 in the Spring AI Engineering Series. Building on the foundations from Book 1, this volume takes you from "I can build an AI feature" to "I can architect an AI system" and sets you up directly for Book 3's deep dive into running these systems reliably in production.If you're ready to move beyond simple integrations and start engineering real intelligent systems, this is your next book. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condizione: New. Print on Demand.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condizione: new. Paperback. Anyone can call a chat API. Engineering an intelligent system that reasons, retrieves, and acts reliably is a different discipline entirely.You've built your first AI feature. It works in a demo, with clean inputs, at low volume. Now your organization wants more: agents that can actually do things, retrieval that doesn't fall apart at scale, and tools that coordinate without silently breaking each other. Welcome to the point where "AI integration" stops being enough, and "AI systems architecture" becomes the job.Advanced Spring AI Engineering is where practitioners become systems engineers.This book goes deep into the architecture that separates fragile AI demos from genuinely intelligent platforms: hybrid search combining semantic and keyword retrieval, re-ranking and query expansion, autonomous agents capable of multi-step reasoning, tool orchestration with Spring AI's atTool annotation, and the Model Context Protocol (MCP) for building distributed, interoperable AI ecosystems.Inside, you'll learn how to: *Architect advanced RAG pipelines with hybrid search, re-ranking, and intelligent chunking strategies*Engineer embeddings at scale model selection, dimensionality trade-offs, drift detection, and versioning*Design AI agents that plan, reason, and execute multi-step tasks not just answer questions*Build reliable tool-calling systems using Spring AI's atTool annotation, with dependency resolution and failure recovery*Implement the Model Context Protocol (MCP) to expose and consume AI capabilities across service boundaries*Integrate AI cleanly into microservices, event-driven systems, and domain-driven architectures*Build observability and continuous evaluation frameworks that catch hallucinations and quality regressions before your users doEvery concept is grounded in real architectural trade-offs, not idealized best practices when RAG beats fine-tuning, when reactive agents beat planning agents, when hybrid search is worth the added latency, and when it isn't. Every example is production-oriented Spring Boot and Spring AI code, built around a single evolving enterprise knowledge platform that grows more sophisticated with every chapter.This is Book 2 of 3 in the Spring AI Engineering Series. Building on the foundations from Book 1, this volume takes you from "I can build an AI feature" to "I can architect an AI system" and sets you up directly for Book 3's deep dive into running these systems reliably in production.If you're ready to move beyond simple integrations and start engineering real intelligent systems, this is your next book. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…