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Total Size:
77.4 MB
Info Hash:
583EA202C96632D95271452A97304E783FD09F04
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Added:
Nov. 14, 2025, 10:42 a.m.
Stats:
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(Last updated: Nov. 14, 2025, 10:42 a.m.)
| File | Size |
|---|---|
| Walls C. Spring AI in Action 2026.pdf | 14.9 MB |
| Code.zip | 62.4 MB |
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10.2 MB
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2023-07-01
| Uploaded by indexFroggy | Size 10.2 MB | Health [ 32 /4 ] | Added 2023-07-01 |
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15.1 MB
[37
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2023-07-01
| Uploaded by indexFroggy | Size 15.1 MB | Health [ 37 /6 ] | Added 2023-07-01 |
NOTE
SOURCE: Walls C. Spring AI in Action 2026
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COVER

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MEDIAINFO
Textbook in PDF format Use Spring AI to add generative AI features like virtual assistants, text summaries, and suggestions to your Java applications. No matter what kind of software you’re building, there’s a huge demand for AI features! Until recently, though, Java developers have had few good tools for adding AI features to existing and new applications. Spring AI, an exciting new extension for Spring and Spring Boot, changes the equation. Spring AI provides generative AI capabilities natively within the framework, so you can stick with Java end-to-end. Spring AI in Action shows you how! In Spring AI in Action you will learn -Spring AI from the ground up! -Create text summaries, virtual assistants and more in Spring Boot applications -RAG and other techniques to improve LLM responses -Text from images and images from text Spring AI makes it much, much easier to add generative AI features to Spring applications. With this powerful framework extension, you can write familiar Java code to build AI features like virtual assistants, text summaries, and smart search suggestions. About the Technology When it comes to AI applications, no Python, no problem! The Spring AI framework makes it possible to add LLM-based features to any Spring application using Java or other JVM languages like Kotlin. From setting up Retrieval Augmented Generation (RAG) to creating AI agents, Spring AI is fast, powerful, and instantly familiar. About the Book In Spring AI in Action, bestselling author Craig Walls shows you how to build AI applications natively using Spring AI and Spring Boot. You’ll start with a simple “Hello AI World” example and quickly advance to more sophisticated techniques, including RAG, AI agents, tool use, speech, and AI observability. You’ll see Craig’s practical example-driven approach—with a relentless emphasis on getting stuff done
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