What is RAG, and when should you use it for internal docs

0views0comments

Comparing RAG with fine-tuning, and when to pick pgvector over a dedicated vector database.

Overview

RAG (Retrieval-Augmented Generation) lets an LLM answer using internal documents without fine-tuning the model.

RAG vs. fine-tuning

RAG makes updating knowledge easy (just add documents to the index), while fine-tuning suits cases where you need to change model behavior itself.

Choosing a vector store

pgvector fits well when the system already runs Postgres and data volume is moderate; a dedicated vector database is worth considering at very large scale.

AI

← Back

What is RAG, and when should you use it for internal docs

Overview

RAG vs. fine-tuning

Choosing a vector store

Tags

AI

Category