Easy RAG Question 32 of 223

What is retrieval-augmented generation (RAG)?

GenAI / LLM · Speak this in 60–90 seconds · Faridabad & Delhi NCR

Text inTokens

TransformerAttention

Text outNext token

RAG retrieves relevant documents and stuffs them into the prompt so the LLM answers with that evidence.

LLMs use tokens (not full words) because it helps them:

RAG questions separate people

who only read docs from people who shipped.

Keep it short, concrete,

and tied to GenAI / LLM work.

Stable token IDs

Each piece maps to a number the network can learn.

Fits the model

Fixed pieces are what transformers expect as input.

Before the model can read a sentence, it goes through these steps:

1
RAG retrieves relevant documents
and stuffs them into the prompt so the LLM answers with that evidence.
2
The model is not
the only knowledge source.
3
It is the standard
pattern for private or frequently changing data.
4
Context mix
Attention looks at nearby tokens together.
5
Next token
The model scores what should come next.
6
Decode
IDs turn back into readable text.

Here's a short line you can speak, broken into clear beats:

Say this line

“The model is not the only knowledge source.”

Break into beats

Themodelisnottheonly

Speaking order

2987408337471632900

Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

RAG retrieves relevant documents and stuffs them into the prompt so the LLM answers with that evidence. The model is not the only knowledge source.