The English language encoder is an embedding use that takes in plain English text and returns a 768-dimensional vector encoding of that text. This model powers this semantic search.
The API truncates incoming text to approximately 256 words before the model encodes it and returns a vector. An example usage pattern is to encode all the texts and descriptions in a website and then use this encoder on query text, supporting natural language queries such as “1990s children’s fiction”.
Each API request includes one batch containing up to 32 text strings.
The authentication and authorization access token.
application/json
"application/json"
OK
The response is of type object
.