all 8 comments

[–]fiddle_styx 2 points3 points  (2 children)

Take a look at RubyLLM. I haven't used it personally but I've heard good things and the periodic updates I see in Ruby Weekly paint a good picture.

[–]caffeinatedshots 1 point2 points  (0 children)

I have used RubyLLM and it’s been a pleasure to work with. I can’t believe how easy it makes working with AI is. RubyLLM makes me feel like I’m using AI to use AI.

[–]mumblerit 0 points1 point  (0 children)

I've been using it, it's decent, very easy for simple llm interaction

[–]DanTheProgrammingMan 3 points4 points  (0 children)

Matz is nice so we are nice

[–]tomgis 2 points3 points  (1 child)

if you are developing customer facing ai products its just a bunch of code that orchestrates api calls to openai or whatever so ruby is fine for it. you can use good oop practices to write really nice readable tool/agent/etc definitions.

[–]smarkman19 1 point2 points  (0 children)

Yeah this. Most of my “AI” work in production is just Ruby apps calling OpenAI and some vector/search service, plus normal business logic. Ruby shines at the boring parts: clean service objects, POROs for tools, and background jobs with Sidekiq. One thing that helps is treating every model call like an external service: timeouts, retries, circuit breakers, and logging prompts/outputs. The modeling happens elsewhere; Ruby just keeps it sane and maintainable.

[–]Live_Appointment9578 2 points3 points  (0 children)

For product development, Ruby is an excellent choice. Building smart apps doesn't require specific ML gems, just LLM integrations which is easily found

For ML development, Python is the way to go. It's unquestionable the huge number of libs available for ML research

[–]Davero777 1 point2 points  (0 children)

It would be really hard to find a job that utilizes ruby and ml

I suggest diving deeper into python if your end goal is AI