Build a Full Stack RAG App With TypeScript

[@lev1ato]

I would love more tutorials with this stack, great job

[@k4f]

Seconded

[@cosgravehill2740]

Thirded!
Lot of hybrid-front-enders out there who need to implement this stack like yesterday who don't have time to learn python just to learn Langchain(and now LangGraph-which i can't find any thorough tutorial like this one for in this stack).
If I can get an intellectual, organic competency of Lang by building in TS stack, then I could hack in the Python if it truly is a differentiating advantage for these types of apps. I just feel like I can't devote the time and energy to build up an organic competency of Langchain and Python at the same time right now with things moving so fast.

[@yYggdtyy5433]

This is very helpful. I'm really appreciate it. I still have got a alot to learn but surely this boosted the learning journey.

[@ChrisWi88]

This is very impressive. Thank you for the video. Epic

[@Dorff_Meister]

Thanks. I did learn a lot. Very helpful.

[@beastmode.engineer]

Great video. RAG taught by Paul Dano himself. psych..

[@thelifehackerpro9943]

Langchain has become so complex in version 0.1 and 0.2

[@prashlovessamosa]

Hey thanks for sharing.

[@SarmoungBooks]

Wouldn't it be more efficient using a Vector database?

[@realllmercu9466]

But why do we need to save QA to the supabase? There seems no usage in the code?

[@donkeyblade]

good stuff!

[@aghileslounis]

Why embed if you can give the entire paper to gpt4 ?

[@bracesproul6995]

We embed so we can do RAG later, it makes for gathering faster & more refined context, as to not confuse the LLM. Not to mention the cost savings of only passing a few retrieved chunks instead of the entire paper for each question.

[@seththunder2077]

Can you do a Python version please

[@gustavstressemann7817]

So true!

[@iDerJOoker]

huge if true

[@johangilcesreyes3543]

Please

[@dostanik01]

booooooo 👎 :D :D :D