Overview
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Learn how to take control of unpredictable AI responses in your applications through this 13-minute tutorial on structured output in large language models. Discover techniques to transform random AI responses into consistent, typed data structures for Spring applications. The tutorial demonstrates how Spring AI manages different LLM implementations, allowing easy conversion of responses into Java types without complex prompt engineering. Follow along to understand why structured output is crucial for reliable AI applications, see examples comparing Google and OpenAI implementations, create a Spring application consuming OpenAI's API, convert free-form responses into typed Java objects, and learn how Spring AI handles different structured output implementations. Perfect for developers building AI-powered Java applications who want to save time dealing with unpredictable AI outputs.
Syllabus
00:00 - Introduction to the structured output problem
01:45 - Structured output in Google's AI Studio
03:40 - The challenge of different LLM implementations
05:10 - Setting up a Spring AI project
06:35 - Creating a basic controller with unstructured responses
08:20 - Implementing typed responses with Spring AI
10:30 - How Spring AI handles structured output conversion
Taught by
Dan Vega