Spring AI
summary
Spring AI provides a Spring Boot integration that wires OpenAI models, a chat client and vector stores (used Postgres + PGVector) to do RAG over 18 records; embeddings load in ~7s and queries return relevant dog profiles. The demo builds a chat endpoint, adds a prompt-chat-memory advisor to preserve session context, exposes a tool for scheduling (returns a pickup time 3 days out), and calls remote services via MCP (Model Context Protocol) for interoperable tool calling.
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chapters (12)
- 0:00Introduction to Spring AI
- 6:03What is Spring AI
- 13:49Building the demo app
- 20:07Creating the chatbot
- 24:41Adding memory to chat
- 27:31System prompt and persona
- 29:16Loading data with RAG
- 34:12Tool calling for actions
- 42:22Model Context Protocol
- 48:24Building an MCP service
- 52:01AI agents and workflows
- 57:43Summary and resources
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