https://github.com/joshlong-attic/springone-2024-spring-ai

https://github.com/joshlong-attic/springone-2024-spring-ai

Last synced: 20 days ago
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• Host: GitHub
• URL: https://github.com/joshlong-attic/springone-2024-spring-ai
• Owner: joshlong-attic
• Created: 2024-08-23T23:08:04.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-28T20:14:02.000Z (5 months ago)
• Last Synced: 2024-08-29T22:15:28.802Z (5 months ago)
• Language: Java
• Size: 1.33 MB
• Stars: 5
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: readme.md

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README

        
# Bootiful Spring AI 

by Dr. Mark Pollack, Dr. Rod Johnson, and Josh

you can find [Rod's code here](https://github.com/johnsonr/instrumented-rag)

https://chat.lmsys.org

* "hi, Spring fans!"

* DJ (~5 mins): officiate the project

  * JVM devs are important to the future of AI.

  * people are not going to switch to Python.

  * Adding GenAI to existing applications with Spring AI is trivial. Want to add functions to your AI flow, woohoo! You've got a lot of valuable code in Spring already, and it's trivial to connect the model to your APIs.

  * you should be excited about this!

  * requires a different skill set to make apps useful than model builders and data scientists

  * Spring's been around for a really, really long time.

  * Portable Service Abstractions, AOP, DI, autoconfiguration

* DP (~5 mins): 

  * history of AI

  * problems/solutions 

  * constraints inform architecture (microservices vs. team size, models vs. speed/intelligence)

  * choose your model wisely (costs vs. speed/accuracy) "which one should we choose?"

  * "vibe checks are all you need."

  * https://chat.lmsys.org

* JL/DP:

  * start.spring.io: `web`, `graalvm`, `jdbc`, `openai`, `pgvector`, `actuator`, `zipkin`, `docker compose`

  * setup  :

    * API key

    * remove _Docker Compose_ from `pom.xml`, specify `spring.datasource.*`, export the ports in `compose.yml`, `docker compose up -d`

    * model

    * _Spring AI M2_!

* DP/JL: introduce the `ChatClient` with a simple joke controller

* DP/JL: structured output (`Joke.class`)

* DP/JL: RAG

* DP/JL: Chat Memory

* DP/JL: functions (show getting the status of a purchase (a `Transaction`))

* DP/JL: observable AI: observability

* DP/JL: efficient AI: virtual threads and GraalVM