Tribal Knowledge • 11 HN points • 17 Jul 24
- RAG provides context to an LLM by fetching data from various sources, not just vector databases. It can use any data store to enhance the language model's predictions.
- Context for an LLM can include system prompts, chat history, RAG, fine-tuning, and more. Any way to turn information into text can improve LLM performance.
- RAG can work with vectors, but it's not limited to them. By enabling the LLM to call functions, it can fetch data from a variety of sources beyond vectors, like relational or graph databases.