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The getting started section shows you how to create your first ai application This framework guides users in creating effective prompts that elicit the desired responses from ai models, optimizing the interaction for clarity and efficiency. Getting started this section offers jumping off points for how to get started using spring ai

You should follow the steps in each of the following sections according to your needs User messages, which are direct inputs from the user, and system messages, which are generated by the system to guide the conversation. Spring ai supports spring boot 3.4.x

When spring boot 3.5.x is released, we will support that as well.

Ai concepts this section describes core concepts that spring ai uses We recommend reading it closely to understand the ideas behind how spring ai is implemented. 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.

Java sdk and spring framework integration for the model context protocol, enabling standardized interaction with ai models and tools through both synchronous and asynchronous communication. By following these patterns and principles, developers can create robust, maintainable, and effective ai applications that deliver real value while avoiding unnecessary complexity. Spring ai supports tool calling through a set of flexible abstractions that allow you to define, resolve, and execute tools in a consistent way This section provides an overview of the main concepts and components of tool calling in spring ai.

Spring ai mcp extends the mcp java sdk with spring boot integration, providing both client and server starters

Bootstrap your ai applications with mcp support using spring initializer. The ai model processes two main types of messages

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