Ready to supercharge your Groovy applications with AI? 🚀** In this comprehensive tutorial, we'll explore how to integrate large language models into Groovy projects, from simple HTTP client scripts to production-ready Spring AI applications.

**What You'll Learn:**
This video walks through building AI-powered applications using the Groovy programming language, starting with a basic OpenAI integration and progressing to sophisticated Spring AI implementations. Perfect for both Groovy enthusiasts and Java developers looking to expand their AI toolkit.

**Key Takeaways:**
• Build a custom OpenAI chat client using Groovy's native HTTP capabilities
• Integrate GPT models with proper error handling and JSON parsing
• Leverage Spring AI framework for production-grade AI applications
• Switch between different LLM providers without changing your code
• Use chat client interfaces for vendor-agnostic AI development
• Set up proper configuration for GPT-5 with temperature settings

**Ready to transform your development workflow?** Subscribe for more practical AI programming tutorials and don't forget to check out the full AI for Java Developers course mentioned in the video!

**Chapters:**
0:00 Introduction to Groovy AI Development
2:15 Setting Up the Groovy Project
4:30 Building Custom OpenAI HTTP Client  
8:45 Handling API Responses and JSON Parsing
12:20 Introduction to Spring AI Framework
15:10 Creating Production-Ready AI Controllers
18:30 Interface-Based LLM Integration
20:45 Conclusion and Next Steps

🔗Resources & Links mentioned in this video:
AI for Java Developers Course: https://www.youtube.com/watch?v=FzLABAppJfM
Spring Office Hours with Guillaume Laforge: https://spring-office-hours.transistor.fm/episodes/s4e26-groovy-google-and-gemini-with-guillaume-laforge
GitHub Repo: https://github.com/danvega/community-over-code-groovy-ai

👋🏻Connect with me:
Website: https://www.danvega.dev
Twitter: https://twitter.com/therealdanvega
Github: https://github.com/danvega
LinkedIn: https://www.linkedin.com/in/danvega
Newsletter: https://www.danvega.dev/newsletter

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Dan Vega

A walkthrough of building LLM-powered applications using Groovy, starting with a raw HTTP client script that calls the OpenAI API directly, then progressing to a Spring AI-based Spring Boot app. The demo shows how Spring AI's ChatClient interface abstracts away the specific LLM provider, making it easy to swap between OpenAI, Anthropic, or Google Gemini without code changes. Key setup details include using GPT-5 with temperature set to 1.0, and configuring API keys via environment variables. The post also highlights that Groovy developers already use the language via Gradle and Jenkins, and can leverage the full Spring AI ecosystem.

Groovy Meets AI: Building LLM Applications with Spring AI