Spring Ai In Action Pdf Github Link Access

Spring AI in Action by Craig Walls is a comprehensive guide to building AI-native applications using Spring Boot

. It covers everything from basic "Hello World" setups to advanced Retrieval-Augmented Generation (RAG) , AI agents, and multimodal AI. Essential Resources & Links Official Code Repository : The book's accompanying source code is available on Additional Examples : Author Craig Walls maintains a broader Spring AI examples repository for various use cases. Official Documentation

: While the book provides deep dives, you can find technical reference documentation on the official Spring AI site

. Note that an official PDF for these reference docs is currently a pending request on GitHub. Purchase/Official Page : You can access the book through Manning Publications Core Features Covered

The book focuses on several key pillars of modern AI development within the Java ecosystem: Spring AI in Action - Craig Walls - Manning Publications

Finding a single "PDF GitHub link" for Spring AI in Action by Craig Walls is difficult because the book is a commercial publication by Manning Publications. While full PDF copies are generally not legally hosted on GitHub, you can access all the official source code and sample chapters through public repositories. 📘 Official "Spring AI in Action" Resources

Official Book Page: Purchase or access the legitimate digital version (PDF/ePub) directly via Manning Publications.

Source Code Repositories: Craig Walls (the author) maintains several repositories for the book's examples:

Main Samples: The spring-ai-in-action-samples repo contains the complete chapter-by-chapter code.

Alternative/Printed Repo: 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:

Building AI applications, such as virtual assistants and text summarization, using Spring Boot.

RAG (Retrieval Augmented Generation) implementation to base LLM responses on user data.

Integration with providers such as OpenAI, Anthropic, Google (Gemini), and Ollama. Mapping AI responses to Java POJOs. 🛠️ Practical Quick Start (GitHub Method) To see the code: Clone the repository: git clone https://github.com Explore directories such as ch01/board-game-buddy.

Developers also recommend the spring-ai-101 repository for a tutorial-style guide. habuma/spring-ai-in-action-samples - GitHub

Spring AI in Action Report

Spring AI in Action is a practical guide to implementing artificial intelligence (AI) and machine learning (ML) in Spring-based applications. The report provides an overview of the Spring AI project, its features, and how to integrate AI and ML capabilities into Spring applications.

Key Takeaways:

Spring AI: Spring AI is a part of the Spring ecosystem that provides a simple and consistent API for building AI and ML applications. It allows developers to leverage the power of AI and ML in their Spring-based applications.
Features: Spring AI provides a range of features, including support for popular AI and ML libraries such as TensorFlow, Deeplearning4j, and Weka. It also provides tools for data preprocessing, model training, and model deployment.
Integration with Spring: Spring AI is designed to integrate seamlessly with other Spring projects, such as Spring Boot, Spring Cloud, and Spring Data. This makes it easy to build AI and ML applications that are scalable, secure, and easy to manage.

Where to Find Resources:

GitHub: You can find the Spring AI project on GitHub at https://github.com/spring-projects/spring-ai.
Spring Framework: The Spring Framework website provides extensive documentation on Spring AI, including tutorials, guides, and API documentation. You can find more information at https://spring.io/projects/spring-ai.
Spring AI in Action PDF: You can search for "Spring AI in Action PDF" on various online platforms, such as Amazon, Google Books, or researchGate. However, be cautious when downloading PDFs from unknown sources, as they may contain malware or viruses.

Example Use Cases:

Chatbots: Build conversational interfaces using Spring AI and popular libraries like Stanford CoreNLP or Dialogflow.
Predictive Analytics: Use Spring AI to build predictive models that can be used to forecast customer behavior, predict sales, or detect anomalies.
Image Classification: Leverage Spring AI to build image classification models using popular libraries like TensorFlow or Deeplearning4j.

The book " Spring AI in Action " by Craig Walls is a guide to building AI-powered Java applications using the Spring ecosystem. While the official publisher is Manning Publications, related code resources and PDF-related information are available on GitHub. Official GitHub Resources

spring-ai-in-action-examples: The primary repository for the book's sample code. It includes branches for different Spring AI versions (e.g., main for 1.0.3 and spring-ai-1.1.0 for newer updates).

spring-ai-in-action-samples: A placeholder/supplementary repository for the book's code examples hosted by the author, Craig Walls. habuma/spring-ai-in-action-samples - GitHub

The book "Spring AI in Action" by Craig Walls is the definitive guide for Java developers looking to integrate generative AI features into the Spring ecosystem. Published by Manning Publications , it bridges the gap between enterprise Java reliability and the power of large language models (LLMs). 📚 Book Resources & GitHub Links

For those searching for official code and documentation, the following resources are essential:

Official Example Code: The primary repository for the book's examples is hosted on GitHub at habuma/spring-ai-in-action-examples .

Alternative Sample Code: A secondary repository for cleaned-up samples is maintained at habuma/spring-ai-in-action-samples .

PDF Access: While unofficial PDF copies sometimes appear on GitHub, Manning provides a legitimate free eBook (PDF, ePub, and Kindle) included with any purchase of the print edition.

Reference Documentation: The official Spring AI Reference Documentation provides a comprehensive HTML guide, though an official downloadable PDF from the Spring team is still a pending community request. 🛠️ What You Will Learn in "Spring AI in Action"

The book follows a practical, "in action" approach, taking readers from "Hello AI" to production-ready services: habuma/spring-ai-in-action-samples - GitHub

While there is no official GitHub link for a free PDF of the book Spring AI in Action

by Craig Walls, the official source code and sample repositories are publicly available on GitHub. You can find the code for the book's examples at the following links: habuma/spring-ai-in-action-examples

: This is the primary repository containing the sample code as it appears in the printed book. habuma/spring-ai-in-action-samples

: A secondary repository intended for ongoing updates and cleaned example code.

For the full text and legitimate digital access, the book is available through official retailers like Manning Publications O'Reilly Learning

Essay: The Evolution of Java AI Development through "Spring AI in Action"

The integration of Artificial Intelligence into the enterprise landscape has long been dominated by the Python ecosystem. However, the emergence of the framework and its definitive guide, "Spring AI in Action"

, marks a significant shift for Java developers. This book serves as a critical bridge, allowing the massive community of Java engineers to leverage generative AI within their existing Spring Boot architectures. Bridging the Language Gap

Historically, developers looking to implement Large Language Models (LLMs) had to pivot toward frameworks like LangChain or LlamaIndex. While powerful, these tools often required a departure from the familiar POJO-based, modular design principles of the Spring ecosystem. "Spring AI in Action"

demonstrates how Spring AI brings these same abstractions—such as portability and modularity—to the AI domain. By providing a consistent API for various AI providers (OpenAI, Anthropic, Google, etc.), the framework ensures that Java developers can build AI-driven applications without learning entirely new paradigms. Core Practical Concepts A central theme of both the framework and the book is the Retrieval-Augmented Generation (RAG)

pattern. In modern AI development, the challenge is no longer just "asking a question" but connecting enterprise-specific data to public AI models. The book guides developers through:

spring-ai-community/awesome-spring-ai: A curated ... - GitHub

Searching for a " Spring AI in Action " PDF on GitHub typically leads to official code repositories rather than the full book text, as the book is a commercial publication by Manning. 📚 Official Book Resources

While GitHub does not host the legal PDF of the book, you can find all the supporting materials there:

Official Example Code: The author, Craig Walls, maintains the companion code for the book in the habuma/spring-ai-in-action-examples and habuma/spring-ai-in-action-samples repositories.

Book Details: You can find the legitimate digital and physical versions on the official Manning Publications page or through retailers like Amazon. 🛠️ Alternative Guides & Official Documentation spring ai in action pdf github link

If you are looking for free, high-quality documentation or starter guides, these are the best GitHub-linked resources:

Official Spring AI Documentation: The most comprehensive technical guide is the Spring AI Reference, which provides the foundation for everything covered in the book.

Awesome Spring AI: A curated list of tutorials, projects, and guides can be found at the spring-ai-community/awesome-spring-ai repository.

Spring AI Examples: For specific implementations like Chat Models, RAG, and Vector Databases, check out the author's Spring AI Examples repository. ⚠️ Note on "Action" Series PDF Links

Be cautious of repositories claiming to host a full PDF of "Spring AI in Action". These are often unofficial, may contain outdated versions, or are redirected from sites like DOKUMEN.PUB. For the most accurate and safe information, stick to the Manning website or the official Spring AI documentation. habuma/spring-ai-examples - GitHub

Repository files navigation. README. Spring AI Examples. This repository is where I'll commit various examples of using Spring AI. habuma/spring-ai-in-action-examples - GitHub

Spring AI in Action: A Comprehensive Guide

As AI and machine learning continue to transform the software development landscape, developers are looking for ways to integrate these technologies into their applications. Spring AI is a cutting-edge framework that enables developers to build intelligent, AI-powered applications with ease. In this blog post, we'll explore Spring AI in action, and provide a link to a PDF guide and GitHub repository to get you started.

What is Spring AI?

Spring AI is a part of the Spring ecosystem, designed to simplify the development of AI-powered applications. It provides a set of tools and libraries that enable developers to build, train, and deploy machine learning models, as well as integrate with popular AI services.

Key Features of Spring AI

Machine Learning: Spring AI provides a simple and intuitive API for building, training, and deploying machine learning models.
AI Services Integration: Easily integrate with popular AI services such as Google Cloud AI, Microsoft Azure AI, and Amazon SageMaker.
Data Management: Simplify data management with Spring AI's built-in data access and manipulation features.

Spring AI in Action: A PDF Guide

To help you get started with Spring AI, we've put together a comprehensive PDF guide that covers the basics of the framework, as well as advanced topics such as model training and deployment. You can download the PDF guide here: [insert link to PDF guide].

GitHub Repository

For a hands-on experience with Spring AI, check out our GitHub repository, which contains sample code, tutorials, and examples to help you get started. You can find the repository here: [insert link to GitHub repository].

Example Use Cases

Chatbots: Build intelligent chatbots that can understand and respond to user queries using Spring AI's machine learning capabilities.
Image Classification: Train and deploy image classification models using Spring AI's integration with popular AI services.
Predictive Analytics: Use Spring AI's machine learning features to build predictive analytics models that can inform business decisions.

Conclusion

Spring AI is a powerful framework that enables developers to build intelligent, AI-powered applications with ease. With its simple and intuitive API, Spring AI makes it easy to integrate machine learning and AI services into your applications. Download the PDF guide and explore the GitHub repository to get started with Spring AI in action.

Links

PDF Guide: [insert link to PDF guide]
GitHub Repository: [insert link to GitHub repository]

While there is no official GitHub link for a free PDF of Spring AI in Action by Craig Walls, you can access the official source code and purchase the book through established platforms. Official Resources

Source Code (GitHub): You can find the example code from the book in the habuma/spring-ai-in-action-examples repository. The repository includes branches for both Spring AI 1.0 and 1.1.0 updates.

Book Purchase (Manning Publications): The book is available for purchase on the Manning website, which includes access to the PDF, ePub, and Kindle versions upon purchase.

Online Reading (O'Reilly): You can also read the book online if you have a subscription to the O'Reilly Learning platform. Key Features of Spring AI

As detailed in the Spring AI Reference Documentation and community guides, the framework covers:

Chat Abstractions: Interacting with various LLMs like OpenAI, Anthropic, and DeepSeek.

RAG Systems: Building Retrieval-Augmented Generation systems using vector databases.

Prompt Templates: Managing and versioning prompts as structured resources.

Output Parsers: Converting AI responses into Java entities like JSON or CSV.

Model Context Protocol (MCP): Using tools and security configurations for AI agents. habuma/spring-ai-in-action-examples - GitHub

The official companion resources for Spring AI in Action Craig Walls

(published by Manning) are hosted on GitHub under the author's official account. GitHub Repository & Source Code

The repository contains all the sample code, chapter by chapter, to follow along with the book's exercises, including the "Board Game Buddy" project used as a running example. Official Sample Code: habuma/spring-ai-in-action-samples Legacy/Original Examples: habuma/spring-ai-in-action-examples

Note: The author maintains two repositories due to a reference error in the book's front matter. The repo is the primary location for ongoing updates. PDF and Documentation Access Official eBook/PDF:

You can access the official PDF, ePub, and Kindle versions by purchasing the book or registering your print copy on the Manning Publications website Spring AI Reference Docs:

While there is currently no official standalone PDF for the general Spring AI Reference Documentation , it is available as a comprehensive HTML guide. Community Resources:

A curated list of additional tutorials, tools, and projects for generative AI with Spring can be found in the Awesome Spring AI repository. Key Topics Covered in the Book

The book focuses on integrating Large Language Models (LLMs) into the Java ecosystem using the Spring framework: Chat Models: ChatClient API

for portable communication with providers like OpenAI and Anthropic. RAG (Retrieval Augmented Generation):

Grounding AI responses in your own private data using Vector Stores like Redis, Pinecone, or Postgres. AI Agents:

Building complex workflows where the AI can call client-side tools and functions. Observability:

Monitoring and evaluating AI-related operations and generated content to protect against hallucinations. latest features

added to the Spring AI framework in the most recent release?

spring-projects/spring-ai: An Application Framework ... - GitHub

Spring Boot Version Compatibility * Support for all major AI Model providers such as Anthropic, OpenAI, Microsoft, Amazon, Google, Spring AI in Action by Craig Walls is

spring-projects/spring-ai: An Application Framework ... - GitHub

Spring AI in Action by Craig Walls is an upcoming publication from Manning. While official PDF links are typically restricted to the Manning Publications site

, the author and community provide extensive GitHub repositories for the book's source code and related Spring AI resources. Official Source Code Repositories

The author, Craig Walls (habuma), maintains two primary repositories for the book's examples. These are the best places to see the concepts "in action": habuma/spring-ai-in-action-examples

: This is the primary repository referenced in the book's front matter. It contains code built against Spring AI 1.0.3 and a branch for version 1.1.0. habuma/spring-ai-in-action-samples

: A newer repository intended for future updates and clean example code once the book is fully released to printers. habuma/spring-ai-examples

: A general repository for Spring AI samples that the author recommends for those interested in the book. Community & Reference Resources

If you are looking for documentation or tutorial-style content in lieu of the full book PDF, these resources offer direct code examples: spring-projects/spring-ai : The official framework repository. Note that the Spring AI Reference Documentation is currently available only in HTML format. alexandreroman/spring-ai-101

: A project titled "See Spring AI in action!" which covers ChatClient usage, prompt templating, and RAG (Retrieval-Augmented Generation). spring-ai-community/awesome-spring-ai

: A curated list of tutorials, articles, and libraries to help you learn Spring AI from the ground up. asaikali/spring-ai-zero-to-hero

: Hands-on code exercises for prompt engineering, function calling, and GraalVM integration. Where to Access the Full Content Early Access (MEAP) : You can access the digital manuscript through the Manning Early Access Program

: Upon purchase from Manning, the PDF, ePub, and Kindle formats are provided directly through your Manning user dashboard specific chapter or a code snippet for a particular Spring AI feature like Function Calling habuma/spring-ai-in-action-examples - GitHub

It's important to clarify that while you're likely looking for the popular book Spring AI in Action

by Craig Walls, Manning Publications typically provides the PDF exclusively to those who purchase the book. Authentic GitHub repositories for this title generally contain example code rather than the full book text.

Below is a blog post highlighting how you can legally access the official materials and what you can expect from the book's GitHub samples. Getting Hands-On with "Spring AI in Action"

For Java developers, the shift toward Generative AI has often felt like a jump into unfamiliar Python territory. That changed with

, a framework that brings AI engineering natively into the Spring ecosystem. To master this new frontier, many are turning to Craig Walls' latest guide: Spring AI in Action

If you’re searching for the "Spring AI in Action PDF GitHub link," here is what you need to know about the official resources available to you. 1. The Official GitHub Repository

While you won't find the full book PDF on GitHub due to copyright, the source code

for all the book's examples is publicly available. This is arguably the most valuable resource for active learners. Repository: habuma/spring-ai-in-action-examples What's Inside: You'll find step-by-step projects covering: Hello AI World: Basic prompt submission and response handling. RAG (Retrieval-Augmented Generation): "Talking with your documents" using vector stores. Conversational Memory: Building stateful chatbots. AI Agents:

Using tools and the Model Context Protocol (MCP) to perform complex tasks. 2. How to Get the PDF The official PDF is provided by the publisher, Manning Publications

. When you purchase the print book, you often receive a free eBook version (PDF, ePub, and Kindle). Direct Access: You can read the book online through the Manning liveBook platform

, which includes an interactive AI assistant to answer questions about the text. Digital Libraries:

The book is also available through major digital providers like O'Reilly Learning Google Play Books 3. Why This Book is a Game Changer

Spring AI abstracts complex interactions with providers like OpenAI, Anthropic, and Google into a consistent, model-agnostic API. The "Action" series is famous for its "no-fluff" approach, and this installment is no different, focusing on: Structured Outputs: Mapping AI responses directly to Java POJOs. Multimodality: Working with images, audio, and text simultaneously. Observability: Using Spring Actuator to track token usage and AI metrics. To get started today, clone the official samples from GitHub and follow along with the official Manning liveBook for the most reliable learning experience. code snippet

for a basic Spring AI "Hello World" application to help you get started right now? Spring AI in Action - Craig Walls - Manning Publications

🚀 Overview

Spring AI in Action is a hands-on guide and code repository for developers who want to integrate AI capabilities into their Spring Boot applications. It covers LLMs, prompt engineering, embeddings, vector stores, function calling, and RAG (Retrieval-Augmented Generation) using Spring AI’s unified API.

1. The Official Spring AI Repository (Most Likely)

If you want to learn Spring AI "in action" through code, the official repository is the best resource. It contains the source code, documentation, and examples.

GitHub Link: github.com/spring-projects/spring-ai
What it includes:
- Source code for the Spring AI framework.
- Example projects demonstrating Chat, Image Generation, Embedding, and Vector Store usage.
- Reference documentation links.

Summary

Since "Spring AI in Action" doesn't exist as a specific title yet, here is the best way to get the content you want:

If you meant a specific GitHub repository created by a community member (e.g., a tutorial repository named spring-ai-in-action), please verify the exact author, as several community tutorials exist with similar names.

While there is no official, free " Spring AI in Action " PDF repository on GitHub—as it is a commercially published book by Manning Publications—you can access the official companion code and legitimate preview resources through the following links: Official GitHub Repositories

The book's author, Craig Walls, maintains repositories containing all the example code used in the chapters. These are the best "in action" resources for developers:

habuma/spring-ai-in-action-examples: The primary repository featuring code built against Spring AI 1.0.3 and an updated branch for 1.1.0.

habuma/spring-ai-in-action-samples: A secondary repository intended for future updates and cleaned formatting after the final print release.

habuma/spring-ai-examples: A general-purpose repository for Spring AI experiments that serves as a precursor to the book's content. Where to Get the PDF/Book

Because "Spring AI in Action" is a copyrighted work, a full legal PDF is typically only available through purchase or subscription:

Manning Publications: The official publisher where you can buy the eBook (PDF/ePub) or the physical copy. Amazon: Available for Kindle and in print.

O'Reilly Learning: Accessible for digital reading if you have a professional subscription. Key Topics Covered

If you are looking for specific "in action" implementations, the book and its code repositories cover: habuma/spring-ai-examples - GitHub

The official GitHub repository for the code examples from the book Spring AI in Action

by Craig Walls is hosted at habuma/spring-ai-in-action-examples. This repository includes the sample code as it appears in the printed book (built against Spring AI 1.0.3), while updates for newer versions like Spring AI 1.1.0 are maintained in a secondary repository, habuma/spring-ai-in-action-samples.

Regarding the PDF version, there is no official, legal PDF of the book available for free on GitHub. The book is a commercial publication available through Manning Publications and O'Reilly Media. Key GitHub Repositories

Main Example Repository: Contains the original code from the book's manuscript. Spring AI : Spring AI is a part

Updated Samples Repository: Intended for future updates and cleaner formatting post-printing.

Spring AI Framework Official Repo: The source for the underlying Spring AI framework itself.

Spring AI 101: A community showcase project that demonstrates "Spring AI in action" through practical features like RAG, image generation, and function calling. PDF and Documentation Status

Book PDF: Access to the full PDF version typically requires purchase from the publisher.

Official Reference Docs: As of late 2025, official Spring AI reference documentation is primarily available as HTML. Community requests have been made to provide a downloadable PDF version similar to other Spring projects. Deep Report: "Spring AI in Action" Content Overview

Based on the book's structure and repositories, the content covers: habuma/spring-ai-in-action-examples - GitHub

Spring AI in Action: A Deep Dive into Integrating Generative AI with Java

The landscape of software development is undergoing a seismic shift. Generative Artificial Intelligence (AI) is no longer a futuristic concept; it is a present-day necessity for building intelligent, responsive, and personalized applications. For Java developers, the Spring ecosystem has long been the gold standard for building robust enterprise applications. With the introduction of Spring AI, the barrier to integrating sophisticated AI models into Java applications has vanished. This article explores the core concepts of Spring AI, provides practical examples, and directs you to essential resources, including GitHub repositories and documentation. Understanding Spring AI

Spring AI is a project designed to streamline the integration of AI functionalities into Spring-based applications. It provides a high-level API that abstracts the complexities of interacting with various AI model providers, such as OpenAI, Azure OpenAI, Google Vertex AI, and Amazon Bedrock. Drawing inspiration from established Spring patterns like the Strategy pattern and the Template pattern, Spring AI offers a familiar and consistent development experience. Key Features of Spring AI

Model Agnostic API: Write your code once and switch between different AI models (e.g., from GPT-4 to Claude) with minimal configuration changes.

Support for Multiple Model Types: Beyond Chat and Text generation, Spring AI supports Image generation, Embeddings, and Transcriptions.

Vector Database Integration: Seamlessly connect with popular vector databases like Pinecone, Milvus, Redis, and Weaviate for Retrieval-Augmented Generation (RAG).

Prompt Management: Tools for creating, managing, and versioning prompts, which are crucial for consistent AI behavior.

Structured Output: Easily map AI responses directly into Java POJOs (Plain Old Java Objects) for seamless integration with your application logic. Spring AI in Action: A Practical Example

Let’s look at a simple example of how to implement a chat service using Spring AI and OpenAI. Dependency Management

First, you need to add the necessary dependencies to your pom.xml: org.springframework.aispring-ai-openai-spring-boot-starter Configuration Configure your OpenAI API key in application.properties: spring.ai.openai.api-key=$OPENAI_API_KEY Implementing the Service Now, create a simple controller to handle chat requests: @RestControllerpublic class ChatController private final ChatClient chatClient;

public ChatController(ChatClient.Builder builder) this.chatClient = builder.build();

@GetMapping("/ai/generate")public Map generate(@RequestParam(value = "message", defaultValue = "Tell me a joke") String message) return Map.of("generation", chatClient.prompt().user(message).call().content());

In this snippet, the ChatClient abstraction allows you to interact with the configured AI model fluently. Advanced Use Case: Retrieval-Augmented Generation (RAG)

One of the most powerful applications of Spring AI is RAG. RAG allows you to augment an AI model's knowledge with your own private data. This is achieved by:

Document Ingestion: Loading your data (PDFs, text files, database records).

Embedding Generation: Converting data into numerical vectors using an Embedding Model. Storage: Saving these vectors in a Vector Database.

Retrieval: Searching the vector database for relevant information based on a user's query.

Augmentation: Including the retrieved information in the prompt sent to the AI model.

Spring AI provides the VectorStore interface and various DocumentReader implementations to make this process straightforward. Resources: Spring AI in Action PDF and GitHub Link

While there isn't a single, official "Spring AI in Action" book in PDF format yet (as the project is rapidly evolving), the community and the Spring team provide extensive resources that serve the same purpose. Official Documentation and GitHub

The most reliable source of truth is the official Spring AI documentation and its corresponding GitHub repository.

Official Spring AI GitHub Repository: github.comThis repository contains the source code, samples, and the latest issues being tracked by the development team.

Spring AI Samples Repository: github.comThis is an excellent place to find "in action" examples, ranging from basic chat applications to complex RAG implementations.

Official Documentation: spring.ioThe documentation is comprehensive, providing architectural overviews and detailed guides on every feature. Community Projects and Guides

Many developers have created "Spring AI in Action" style repositories. Searching GitHub for "Spring AI RAG Example" or "Spring AI Tutorial" will yield numerous high-quality projects. Look for repositories with recent commits and good documentation. Conclusion

Spring AI is a game-changer for Java developers. By providing a structured, familiar, and model-agnostic approach to AI integration, it enables the creation of a new generation of intelligent applications. Whether you are building a simple chatbot or a sophisticated knowledge management system using RAG, Spring AI provides the tools you need. Dive into the GitHub samples, explore the documentation, and start building your first AI-powered Spring application today. Use the official GitHub link provided above to get started with the source code and community examples.

Spring AI in Action is a bestselling guide by Craig Walls (a principal engineer on the Spring team) that teaches developers how to build native AI applications using Spring AI and Spring Boot. Essential Repository Links

The book's source code and supplementary materials are hosted on GitHub:

Official Sample Code: The primary repository containing the examples as they appear in the book is habuma/spring-ai-in-action-examples.

Updated Samples: For the latest updates and maintenance beyond the book's print date, use the habuma/spring-ai-in-action-samples repository.

General Spring AI Examples: Craig Walls also maintains a broader collection of standalone examples at habuma/spring-ai-examples. How to Access the Guide (PDF/eBook)

The book is published by Manning Publications. While the code is free on GitHub, the text is a commercial product.

Official Purchase: You can buy the Spring AI in Action eBook (PDF, ePub, online) or print version directly from Manning.

Manning liveBook: Purchasing the book includes access to liveBook, Manning's online reading and discussion platform.

Official Reference PDF: Note that there is currently no official "one-click" PDF for the general Spring AI technical documentation on the Spring website, though requests for one are tracked on GitHub. Key Topics Covered The guide uses examples to cover: Spring AI in Action - Craig Walls - Manning Publications

Common Pitfalls and How the GitHub Repo Solves Them

| Pitfall | How the GitHub Repo Helps | | :--- | :--- | | API Key management | Look at application.properties samples. Use spring.ai.openai.api-key=$OPENAI_API_KEY | | Model version mismatches | The repo uses specific, tested versions (e.g., gpt-3.5-turbo). Stick to those. | | Function calling not working | Check the FunctionCallbackWrapper examples in spring-ai-examples. You must register the function as a Spring bean. | | Vector store connection | The spring-ai-examples includes docker-compose files for Pgvector – run docker-compose up first. |

2. Manning's "Spring AI" Early Access

If you are looking for a PDF book, Manning Publications has an "Early Access" (MEAP) program for a book simply titled "Spring AI" (often confused with the "In Action" series naming convention).

Book Title: Spring AI (Author: yours truly, or community experts)
Link: Manning: Spring AI (Note: Availability depends on the current MEAP schedule).
GitHub for Book: If you buy the MEAP, the accompanying code is usually hosted on the author's GitHub or the Manning repository.

📥 Download PDF & Code

git clone https://github.com/your-username/spring-ai-in-action.git
cd spring-ai-in-action
./mvnw spring-boot:run

You can find the latest Spring AI in Action.pdf inside the /docs folder of the repository.

Your 7-Day "Spring AI in Action" Learning Plan

Using the GitHub repo and the PDF documentation, here is a one-week plan.

Day 1: Set up the project. Clone spring-ai official repo. Run the HelloWorld test. Generate your PDF reference.
Day 2: Master the ChatClient. Build a simple Q&A app.
Day 3: Add memory and prompts. Use PromptTemplate to inject user input.
Day 4: Function calling – make Spring AI call your @Service to calculate something.
Day 5: RAG 101 – Load a PDF (your own document), embed it, and query it with Spring AI + Pgvector.
Day 6: Streaming and Reactive – implement a WebFlux endpoint for typewriter-style output.
Day 7: Deploy to Cloud – package as a GraalVM native image (Spring AI supports it, check the repo for native configurations).