Intelligent Applications with Spring AI
summary
Shows a concrete Spring AI setup that actually runs: local Ollama/DeepSeek 7B models via AMA for offline chat, Anthropic Claude for function calling workflows, OpenAI DALL·E for text→image generation and OpenAI transcription/tts for audio round trips. Demonstrates RAG with vector stores and similarity search, mapping API responses to Java records, and a live demo that generates images, transcribes and synthesizes speech. Notes a surprising scale claim: models with 100M‑token context that could hold millions of lines of code.
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chapters (19)
- 0:00Welcome to Spring AI
- 1:07Intelligent app development
- 3:37Enterprise AI use cases
- 7:51Generative AI with REST APIs
- 11:03Choosing AI models
- 13:13Generative AI limitations
- 16:41Spring AI for Java
- 19:30Getting started with Spring AI
- 23:26Chat client demo with OpenAI
- 28:03Working with images
- 30:12Image generation with AI
- 32:23Audio transcription/translation
- 35:59Text-to-speech conversion
- 38:10Large docs with RAG
- 40:56Vector stores and search
- 44:08Function calling in Spring AI
- 46:58Model Context Protocol
- 48:25AI integration challenges
- 49:08Future of AI in software
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