u/Lumpy-Town2029

so i am making a project where a profile will have a button of finding matches,

it will go like

1. hard filters, (e.g gender, age, status (married , single), location, drink and other things)
2. soft filters, like personality thing

so coming onto second:

profile will have string of loooking for or family values, or other things, or like hobbies, future plans, career, children etc

so i am planning to use vector embedding for it

litlle bit about myself: not a RAG developer, not even ML developer. but ik few ML algos, and know their application. about RAG, i have studied it, theory only though. never implemented, so this is the first time.

constraints: have no money to use paid AI for that embeddings, user <=150

question-

1. for MVP, i m gonna fill 100 users, so DB aint needed right? (edit- i mean vectorDB, i already have mongo DB for database, vectorDB for calculating and storing vectors)
2. i am thinking of precalculating the embedding vectors locally and then store it in DB, and then find the close neighbour in server/backend. hows this approach? (editted- clients PC to server/backend)
3. any free resources i can have now? as i think all AI services are paid now, and gemini has very low credit ig
4. any advices?

Today i bought icecream brick, and when i ate it it didn't had choco chips in it.

Usually the one i buy has choco chips in it and u hate chips but love the bitter icecream

So today i realised that it also comes without choco chips and its called belgian chocolate

by notes, i dont mean rough work, we do when soliving question, that messy thing, but actual proper notes

personally, i can search online if i ever need to look something.
and i practice a topic nicely, that i have even a little memory of that topic, so i can easily revise that.

also i am not gonna open those notes

what do u think?

Had to go out for a function but the moment i got ready, the clouds too

Atleast the weather will be cooler

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