Spring Ai In Action Pdf Github Link

org.springframework.ai spring-ai-bom 1.0.0-SNAPSHOT pom import org.springframework.ai spring-ai-openai-spring-boot-starter org.springframework.ai spring-ai-pgvector-store-spring-boot-starter Use code with caution. Step 2: Ingesting Documents

private final ChatClient chatClient;

"You must create a ChatClient bean that leverages the Builder pattern to define default system prompts." spring ai in action pdf github link

For plug-and-play code, check out github.com. This repository includes comprehensive, multi-step sample projects demonstrating RAG, structured outputs, prompt engineering, and conversational memory models. Learning Guides, PDFs, and Reference Documentation

using Spring Initializr.

| Repository | Description | Key Technologies | | :--------- | :---------- | :--------------- | | | Comprehensive showcase with 7+ use cases: chat models (OpenAI, Mistral, Ollama), function calling, RAG with vector stores, multimodality and image models, tool calling, and Azure OpenAI integration. Each use case includes detailed blog article references. | OpenAI, Mistral AI, Ollama, Azure OpenAI | | stiebo/spring-ai-samples | Demonstrates PDF document processing with CV analysis, document Q&A with RAG, and flashcard generation from images or PDFs. Excellent for understanding Spring AI's structured output and multimodality capabilities. | PGVector, OpenAI embeddings | | timosalm/spring-ai-recipe-finder | A recipe finder application showcasing function calling and RAG. Supports multiple LLM backends: OpenAI, Azure OpenAI, and local Ollama. Includes a second repository for MCP implementation. | Ollama, OpenAI, Azure OpenAI, Redis Vector Store | | arfatbk/Effective-AI-Agents-with-Spring-Boot | Building effective AI agents based on Anthropic's architecture. Implements prompt chaining workflows and other agentic patterns. Excellent for understanding agent design. | Spring Boot, Anthropic patterns |

Setting up a Spring AI application requires minimal boilerplate code. Below is a streamlined example showcasing how to build a REST controller that interacts with an AI model using standard Spring Boot principles. Step 1: Maven Dependencies | OpenAI, Mistral AI, Ollama, Azure OpenAI |

The code is designed to be cloned, built, and run immediately, allowing you to experiment with the concepts as you read.

You now have a working Spring AI application talking to an LLM. and run immediately

"Spring AI in Action" is the first authoritative guide to Spring's new AI extension, written by Craig Walls—a principal engineer on the Spring team and the bestselling author of Spring in Action . The book teaches you how to build AI applications natively using Spring AI and Spring Boot, without abandoning the Java ecosystem. No Python, no problem.