Generate embeddings for text input

Generate vector embeddings from input text. This endpoint converts text into high-dimensional vector representations that capture semantic meaning. These embeddings preserve semantic relationships between texts and can be used for various machine learning tasks. Notes: - Empty strings or arrays are not accepted - Results include index numbers for mapping back to original inputs - All embeddings are generated as query vectors. If the embeddings have two modes (e.g., query and document), this endpoint only returns query vectors.

Request

This endpoint expects an object.
inputstring or list of stringsRequired

The text(s) to generate embeddings for. Can be a single string or an array of strings. Each text should be a meaningful unit of text (sentence, paragraph, etc).

modelstringOptionalDefaults to default
Model identifier or alias.

Response

This endpoint returns an object.
datalist of objects
List of embeddings, one for each input text
object"list"
The type of object returned
model"private-gpt"
The model used to generate embeddings

Errors

401
Unauthorized
422
Unprocessable Entity