@Configuration public class AiConfig
Swap your underlying AI model (e.g., OpenAI to Ollama) by changing a single configuration line.
One of the hardest parts of working with LLMs is parsing text responses back into code-friendly structures. Spring AI solves this with BeanOutputConverter . spring ai in action pdf github link
Note: The official GitHub organization contains complete, runnable sample applications for Retrieval-Augmented Generation (RAG), chatbots, and structured data extraction. 🏗️ What is Spring AI?
package com.example.ai.assistant;
You now have a working Spring AI application talking to an LLM.
To continue your learning journey, check out the official , download the sample templates provided in spring-ai-examples , and start building context-aware, highly intelligent enterprise solutions today. @Configuration public class AiConfig Swap your underlying AI
: You can buy the Spring AI in Action eBook (PDF, ePub, online) or print version directly from Manning.
This article was last updated based on Spring AI version 0.8.1. The framework is moving rapidly toward 1.0. Always check the official GitHub repository for the latest links and documentation. To continue your learning journey, check out the
When building Retrieval-Augmented Generation (RAG) systems that parse local PDFs or office documentation, ensure that files are scrubbed of Personally Identifiable Information (PII) before calculating embeddings and uploading vectors to public cloud hosting environments.
Avoid hardcoding prompt text directly into your Java strings. Instead, leverage Spring's Resource abstraction to store prompts in external text or Markdown files ( classpath:prompts/analysis-prompt.txt ), allowing prompt updates without forcing application recompilation.