vector database
A store built for one question: given this embedding, which stored embeddings are nearest? That is how a codebase index gets searched.
Where it comes up
Cursor 201
“>> Yeah, that's it's a great question. Um so there there are a couple pieces to it. The the way that we So when you when you first use like a particular code base with within cursor, when you first open it up, um we we do some like indexing…”
Cursor 201
“Um cursor kind of specifically as a product uses something called semantic search, Um, is uh, we're able to do by um, indexing all the files in your workspace um, and then uh, embedding them into a vector store. Um, and then when you run a…”
Cursor for Java Developers
“um exciting function that is semantic parsing. What that means is with your whole code code base it's able to have semantic semantic meaning to it. So if you ask any specific questions of meaning to it, cursor is able to parse out of it not…”
Cursor for Sales Engineers
“Um, another thing that we do uh is very effective uh model harnessing uh which is the prompt life cycle uh that kind of takes context uh from your uh codebase uh through the indexing through the index that we maintain in a in a vector datab…”
PRD to PR
“grep, which is basically just like searching a code base, right? But, you know, that can be effective in small code bases, but if you have, you know, like a 2 million line code base in a production setting, just searching by like a substrin…”