Ever felt frustrated by unpredictable AI responses in your applications? In this tutorial, I show you how to take control using structured output in large language models - it's like telling AI exactly what shirt to wear instead of accepting whatever it decides to give you!
Learn how to transform random AI responses into consistent, typed data structures you can actually use in your Spring applications. I'll demonstrate how Spring AI handles the complexity of different LLM implementations, allowing you to easily convert responses into Java types without writing complex prompt engineering code.
What You'll Learn:
• Why structured output is crucial for building reliable AI-powered applications
• How structured output works in different LLMs (Google vs OpenAI examples)
• Creating a simple Spring application that consumes OpenAI's API
• Converting free-form LLM responses into typed Java objects
• How Spring AI handles the complexity of different structured output implementations
Video Chapters:
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
If you're building AI-powered Java applications, this tutorial will save you hours of frustration dealing with unpredictable AI outputs. Subscribe for more Spring and AI content that makes your development life easier!
#SpringAI #JavaTutorial #AITutorial #SpringBoot #StructuredOutput #LLM #OpenAI
Dan Vega is a Spring Developer Advocate at Broadcom, specializing in helping developers build intelligent applications with Spring and AI technologies.
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