Struct CreateEmbeddingRequest

pub struct CreateEmbeddingRequest {
    pub dimensions: Option<i32>,
    pub encoding_format: Option<String>,
    pub input: Value,
    pub model: Value,
    pub user: Option<String>,
}

Fields

dimensions: Option<i32>

The number of dimensions the resulting output embeddings should have. Only supported in text-embedding-3 and later models.

encoding_format: Option<String>

The format to return the embeddings in. Can be either float or base64.

input: Value

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. Some models may also impose a limit on total number of tokens summed across inputs.

model: Value

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.

user: Option<String>

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.

Trait Implementations

impl Debug for CreateEmbeddingRequest

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for CreateEmbeddingRequest

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for CreateEmbeddingRequest

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.