Spring into the AI Era: A Practical Exploration for Developers (Workshop)
summary
Hands-on workshop shows how to add LLM features to Spring apps using the Spring AI starter and Azure OpenAI: one-line controllers call models, embeddings convert text to numeric vectors stored in a vector store, and retrieval‑augmented generation pulls top‑K chunks into prompts. Demos include prompt templating, output parsing to map JSON into beans, and the Acme Fitness Store search; token limits (4K→16K/32K, Claude 100K) and hallucinations drive design decisions. Samples run in GitHub Codespaces but live subscription/key and network glitches limit full hands‑on for some attendees.
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chapters (10)
- 0:00Introduction and setup
- 12:50Generative AI fundamentals
- 27:40Setting up the workshop
- 1:04:03Hello World with Spring AI
- 1:27:20Prompt templating and roles
- 1:46:22Output parsing and structured responses
- 2:02:52Bringing your own data
- 2:17:46Acme Fitness Store demo
- 2:37:13Architecture and real-world use cases
- 2:41:08Q&A and resources
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