Add AI chat functionality to a Spring Boot application using any major AI provider without writing custom HTTP integration code.
Build a retrieval-augmented generation feature that searches your company documents and uses an AI model to answer questions about them.
Switch your application from one AI provider to another by changing a configuration value rather than rewriting application code.
Store and search document embeddings in a vector database using Spring AI's common interface across more than a dozen providers.
Requires Java 17 or newer and a Spring Boot project, add via start.spring.io. Each AI provider requires its own API key.
Spring AI is a Java framework for building applications that use AI models. It is part of the Spring ecosystem, which is a widely used set of tools for building Java applications, and it brings the same design patterns and coding conventions from that ecosystem to the world of AI integration. The main problem it solves is connecting your application's data and existing code to AI models. Rather than writing custom integration code for each AI provider, Spring AI gives you a single consistent API that works across providers like Anthropic, OpenAI, Google, Amazon, Microsoft, and others. If you switch providers, you change a configuration value rather than rewriting your application. Beyond basic chat, it supports several types of AI interactions: generating text, converting text to images, transcribing audio, and producing speech from text. It also supports vector databases, which are a type of storage system used to make AI-powered search and retrieval work efficiently. Spring AI connects to over a dozen vector database providers through one common interface. Other features include function calling (where the AI can trigger code in your application to get real-time information), conversation memory so the AI remembers earlier messages in a session, and retrieval-augmented generation (a technique where the AI answers questions by first searching your documents rather than relying only on what it was trained on). There are also utilities to help test whether AI responses are accurate. Spring Boot integration is included, meaning you can add Spring AI to a new project through the standard Spring project generator at start.spring.io. The project requires Java 17 or newer. Documentation and example projects are linked from the README.
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