riter

OP here.

i agree. perhaps you're confused on the intent. the only flag being planted is for folks using rasa looking for a reference implementation just like i was a week ago. not sure if you're being intentionally cynical but trying is good thing. why? bc most ppl don't try. you make 0 of the shots you never take. and of course, if you're not intentionally being cynical -- gucci. if you are i encourage you to make your next comment substantial or encouraging :)

LOL.

you're not alone my dude. i have a similar challenge w/ my engineers. my best lead is an artisan and its proud of what he authors, and like me sees their code as part of the product UX / funnel (1%). the others (99%) i have to get a bit draconian or simply create company templates they must adhere to or PRs get rejected and they hear from me on their 1:1s.

you either love it or you don't. and if you don't, follow the rules like a big boy or get called out.

ultimately you have to set a culture for it even if it is pulling teeth because you net net it impacts the PnL.

thanks for the share, will check out

lol

well to be fair, when you're scaling it does matter. i would want my techlead or seniors to care and know when/where to make specific trade-offs bc cloud costs are not forgiving.

i think that's where folks that make those comments are coming from.

in terms of search store and engine, would you agree that pgvector is sufficient for most text-specific cases?

very much agreed re: dust settling.

it makes no sense deploying any of these libraries to prod. as-is. best to understand a configuration / workflow / tuning / etc. that fits your data best and write it from scratch in golang/rust/whatever.

<3 ty, i totally misinterpreted the comment for cynicism. u guys are kind ty!

ah! in that case glad you asked.

my objective falls into neither bucket. i want rasa users to find it so i optimize for search (GH tags, clear description), ease of use (video, addt'l MD files) and perception (logos) but i'll be honest, for my intention it has a diminishing rate of return.

at minimum i find canonical README sections like quick start, installation, how it works is necessary if you want to be helpful. helpfulness is difficult to measure outside of inbound emails thanking you / forks w/ actual commits.

hope that gives some kind of insight. just make everything awesome :)

OP here.

that's a somewhat cynical interpretation. what if i just care about aesthetics and want to raise the bar.

my primary motivation was to get users of Rasa out of a directional hole bc that's where i was.

of course i like stars. it's a video game and i like winning. it was actually created in a few days all by me. no ulterior motive, literally indexing a solution to my problem from ~a week ago.

my bg is eng + product so i do these things as reflex and have a love for good UX.

nothing more. nothing less.

there are a few decent YT videos on this topic (dated 2022 though)

vast.ai is decent if you want to rent.

the next best platform I could find for my friend I was helping was google's dialog flow. again, it was managed, closed-source opinionated and not as flexible. and most importantly design considerations were for a pre-LLM world.

i personally think there is an acute opportunity for creating a bare bones rasa built with LLMs in mind. the core concepts behind rasa are useful (domains, intents, actions, etc.) but the underlying NLU technology and assumptions around the platform are obsolete so 70% of the footprint is unnecessary.

just my humble Ξ0.02

it solves how to integrate LLMs (Langchain) an application API pipeline with Rasa... of which I could not find an out-of-the-box public example on github. and so here we are :)

TL;DR: i solved a friend's headache (at the time)