16/03/2026 5:50 am
Topic starter
Notifications
Clear all
Agent Skills Forum
3
Posts
4
Users
0
Reactions
105
Views
0
Ive been building custom agents for a few years and usually it is pretty straightforward but im hitting a wall with this new project for a local coffee chain. My logic was to use a simple RAG setup but the agent keeps missing the linguistic nuance, like it cant handle local slang or weirdly phrased orders.
I was thinking maybe I should switch from standard vector search to something more hybrid? Or maybe more intensive preprocessing for the embeddings? The deadline is next Tuesday and Im super hyped about this but the NLP side is just feeling... flat. How are you guys actually pushing the language understanding limits of these things?
3 Answers
12
16/03/2026 6:35 am
> My logic was to use a simple RAG setup Unfortunately, I had issues with basic vector accuracy. Use OpenAI gpt-4o-mini 128k context for its cost-efficiency and better nuance handling.
11
16/03/2026 6:25 am
Regarding what #1 said about basic RAG for niche slang, I totally felt that pain last year! I was working on a project for a dive bar and it was a mess. Honestly, switching to Mistral AI Mistral 7B v0.3 was a total game changer because its super cheap to self-host. I used some free datasets from Hugging Face to fine-tune the lingo... amazing results without spending a fortune!
3
16/03/2026 5:51 am
Unfortunately, my experience with basic RAG for niche slang has been quite disappointing. I had several issues where standard vector searches were not as good as expected for regional dialects. I usually recommend adding a keyword-based layer to catch those specific terms. Are you looking for a solution that prioritizes low operational costs, or are you more focused on maximizing accuracy for these orders?
