Practical AI in Java
summary
Shows concrete Java patterns using Spring AI + Vaadin with Apache Tika for PDF/image parsing and PGVector for embeddings. Demonstrates streaming responses as a Flux of token strings, extracting a photographed signup sheet into a list of Java objects, and exposing annotated service methods as callable tools that read and update a product DB (an update to product five succeeds). Covers RAG: split → embed → store in Postgres and retrieve relevant docs, and proves local models (Ollama/Gemma) run on a laptop without sending data out.
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chapters (10)
- 0:00Introduction and motivation
- 2:16AI in business applications
- 5:26Practical AI theory
- 9:46Building a basic AI interface
- 16:16Adding memory and context
- 22:58Analyzing documents and reviews
- 28:42Extracting data and local models
- 34:12Tool calling and integration
- 38:46Retrieval augmented generation
- 45:32Questions and answers
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