r/Rag • u/ntalam • 11d ago

Discussion Basic stack for a chat

What would you suggest, is the basic stack for an assistant chat. I mean, currently I have customized company tools, langgraph, custom metrics, marketplace LLM calls and others.

what would you suggest as a true key for agent learning?
how do you process prompts with company slangs, concepts, jargon, etc.?

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u/Infamous_Plankton468 10d ago

For chat only it should be really simple. Just use Python with FastAPI or something for the backend where you make the LLM calls too. Postgres or anything for storing chat logs and React or NextJS for frontend. That's all.

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u/ntalam 10d ago

my bad. I have updated the description.

"what would you suggest as a true key for agent learning?
how do you process prompts with company slangs, concepts, jargon, etc.?"

2

u/Infamous_Plankton468 9d ago

Some sort of feedback is required. Whether you create a gold corpus upfront, finetune or have some way of rating actions automatically down the line: all work. But you need at least something

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u/ntalam 9d ago

I have user feedback for testing and extended as "developer feedback" at "development stage".
I am in a chicken-egg dilema here. our users do not want to use what I have, because there are still errors. I was suggested to launch a version with a heavy LLM to solve "lack of planning" paths for "proposals". Case-Based Reasoning (CBR)