In the official OpenAI node library Create embeddings if for example using the model text-embedding-ada-002
the embeddings returned is an array of around 1536
.
import {Configuration, OpenAIApi} from 'openai'
openai = new OpenAIApi(this.configuration)
const parameters= {
model: 'text-embedding-ada-002',
input: text,
}
// Make the embedding request and return the result
const resp = await openai.createEmbedding(parameters)
const embeddings = embedding?.data.data[0].embedding
I would like to be able to limit the length of the list of embeddings returned.
You need to use the dimensions
parameter with the OpenAI Embeddings API.
As stated in the official OpenAI documentation:
By default, the length of the embedding vector will be
1536
fortext-embedding-3-small
or3072
fortext-embedding-3-large
. You can reduce the dimensions of the embedding by passing in thedimensions
parameter without the embedding losing its concept-representing properties. We go into more detail on embedding dimensions in the embedding use case section.