Spring Ai In Action Pdf Github Link Jun 2026

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)

@Component public class DocumentIngestionService private final VectorStore vectorStore; public DocumentIngestionService(VectorStore vectorStore) this.vectorStore = vectorStore; public void ingestPdf(Resource pdfResource) PagePdfDocumentReader pdfReader = new PagePdfDocumentReader(pdfResource); TokenTextSplitter splitter = new TokenTextSplitter(); List documents = splitter.apply(pdfReader.get()); vectorStore.accept(documents); Use code with caution. Step 3: Querying with Context

Note: The samples are built against Spring AI 1.0.3+, making them relevant for the latest framework developments. How to Access the Spring AI in Action PDF spring ai in action pdf github link

Regarding the , 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

Based on the book's structure and repositories, the content covers: habuma/spring-ai-in-action-examples - GitHub Step 3: Querying with Context Note: The samples

| Repository | Description | Key Technologies | | :--------- | :---------- | :--------------- | | | A tutorial putting AI to work using Spring Boot. Covers basic integration patterns and includes a companion Medium article. Great starting point for absolute beginners. | Spring Boot, OpenAI | | Ravikharatmal/spring-ai-tutorial | Comprehensive tutorial setup with detailed configuration instructions for multiple models including OpenAI and Anthropic. Includes MCP (Model Context Protocol) examples. | OpenAI, Anthropic, MCP, PostgreSQL | | liuyueyi/spring-ai-demo | A rich demo project covering the entire Spring AI learning path: prompts, structured output, tool calling, MCP, advisors, ChatClient, and multiple model integration. Includes extensive Chinese documentation. | Spring Boot 3.5+, Spring AI 1.x & 2.x, LangGraph4J | | asaikali/spring-ai-zero-to-hero | Workshop content designed for conference sessions. Requires Java 21+, Docker, and Ollama. Includes a check-deps.sh script to verify prerequisites. Best for hands-on workshop learning. | Ollama, Docker, Testcontainers | | ThomasVitale/llm-apps-java-spring-ai | Production-quality examples from a respected Spring contributor. Covers chatbots, question answering (RAG), semantic search, structured data extraction, text classification, and multimodal models (image, audio). | Ollama, PGVector, Mistral AI, OpenAI |

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 Key GitHub Repositories Based on the book's structure

If you want practical, code-first learning—what "in action" truly means—these five repositories are your bible.