EdgeDB 5: Introducing ext::ai

Back in EdgeDB 3.0 we, added support for storing and searching embeddings via the ext::pgvector extension .

However, we felt that we can do much more than just simple vector storage and search. In EdgeDB, traditional full text search is as easy as adding an fts::index on the object of interest like so:

type BlogPost {
 content: str;
 index fts::index on (
 fts::with_options(
 .content,
 language := fts::Language.eng
 )
 );
}

and then do search like so:

select fts::search(BlogPost, 'my query')

We are happy to announce that in EdgeDB 5.0 indexing and searching content using semantic similarity is just as easy!

using extension ai;
type default::BlogPost {
 content: str;
 deferred index ext::ai::index(
 embedding_model := 'text-embedding-3-small'
 ) on (.content);
}

No more fiddling with embeddings! Just declare an index on a text property (or any text expression), and you're now ready to easily perform semantic similarity searches:

select ext::ai::search(BlogPost, vector)

This works thanks to our new deferred index mechanism, also added in EdgeDB 5.0. It allows for asynchronous index creation to avoid blocking object mutation — the perfect solution for slow-going operations such as calling out to a remote LLM over an API.

Speaking of the API, the ext::ai extension contains support for calling into OpenAI, Mistral and Anthropic model APIs out of the box. Of course, you can plug any model as long as it exposes an OpenAI- or Anthropic-compatible API (and more support is coming in future releases).

Having a generic way of doing semantic search over an arbitrary set of objects opens the door to another great feature of the ext::ai extension: RAG with database data as context!

import { createClient } from "edgedb";
import { createAI } from "@edgedb/ai";
const client = createClient();
const gpt4AI = createAI(client, {
 model: "gpt-4-turbo-preview",
});
const blogAI = gpt4AI.withContext({
 query: "select BlogPost"
});
console.log(await blogAI.queryRag(
 "Were any of the blog posts about RAG?"
));

$ curl --json '{
 "query": "Were any of the blog posts about RAG?",
 "model": "gpt-4-turbo-preview",
 "context": {"query":"select BlogPost"},
 "stream": true
 }' https://edgedb-host:port/branch/main/ai/rag