pub struct CreateEmbeddingRequest {
pub model: String,
pub input: EmbeddingInput,
pub encoding_format: Option<EncodingFormat>,
pub user: Option<String>,
pub dimensions: Option<u32>,
}
Fields§
§model: String
ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.
input: EmbeddingInput
Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for text-embedding-ada-002
), cannot be an empty string, and any array must be 2048 dimensions or less. Example Python code for counting tokens.
encoding_format: Option<EncodingFormat>
The format to return the embeddings in. Can be either float
or base64
. Defaults to float
user: Option<String>
A unique identifier representing your end-user, which will help OpenAI to monitor and detect abuse. Learn more.
dimensions: Option<u32>
The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3
and later models.
Trait Implementations§
Source§impl Clone for CreateEmbeddingRequest
impl Clone for CreateEmbeddingRequest
Source§fn clone(&self) -> CreateEmbeddingRequest
fn clone(&self) -> CreateEmbeddingRequest
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read more