RAG explained

Retrieve the relevant documents, then let the model answer using only those. It is how an assistant answers about your business without inventing.

What RAG means

Retrieval-augmented generation. When a question arrives, the system first searches your documents and records for relevant material, then asks the model to answer using only what it found.

The model supplies the language; the retrieved material supplies the facts. That separation is the entire point.

RAG explained, in three chapters

Why it beats fine-tuning for this

Fine-tuning teaches a model a style or a task. It is a poor way to teach facts, because updating a fact means retraining, and the model cannot cite where an answer came from.

With retrieval, updating a document updates the answers immediately, and every answer can name its source.

Read next

RAG explained, answered.

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