pub struct CreateEmbeddingRequest {
pub model: String,
pub input: EmbeddingInput,
pub encoding_format: Option<EncodingFormat>,
pub user: Option<String>,
pub dimensions: Option<u32>,
}Fields§
§model: StringID 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: EmbeddingInputInput 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