Spring AI API

Portable Model API across AI providers for Chat, Text to Image, Audio Transcription, Text to Speech, and Embedding models. Both synchronous and stream API options are supported. Dropping down to access model specific features is also supported.

With support for AI Models from OpenAI, Microsoft, Amazon, Google, Amazon Bedrock and more.

Portable Vector Store API across multiple providers, including a novel SQL-like metadata filter API that is also portable. Support for many vector databases is available.

Spring AI makes it easy to have the AI model invoke your services as @Tool-annotated methods or POJO java.util.Function objects.

Check the Spring AI Tool Calling documentation.

The ChatClient API offers a fluent API for communicating with an AI Model, idiomatic to Spring developers and similar to WebClient or RestClient.

The Advisors API encapsulates recurring Generative AI patterns, transforms data sent to and from Language Models (LLMs), and provides portability across various models and use cases (e.g., memory, tool-calling, RAG).

MCP (Model Context Protocol) - Seamless integration for building AI applications that consume MCP servers or expose Spring-based services to the AI ecosystem.

Spring Boot Auto Configuration and Starters for AI Models and Vector Stores.

ETL framework for Data Engineering. This provides the basis of loading data into a vector database, helping implement the Retrieval Augmented Generation pattern that enables you to bring your data to the AI model to incorporate into its response.