RAG is one of those patterns that sounds more complicated than it has to be.
At its core, retrieval-augmented generation is just:
- Store some documents
- Embed the user’s question
- Find the most relevant docs
- Send those docs to the model as context
- Return an answer with sources
I built a small Python example that shows that flow end to end with Telnyx AI Inference.
Repo:
SOCIAL SHARE CARD GENERATOR