pub struct ModelResponseProperties {
pub metadata: Option<Metadata>,
pub temperature: Option<f64>,
pub top_p: Option<f64>,
pub user: Option<String>,
pub service_tier: Option<ServiceTier>,
}
Fields§
§metadata: Option<Metadata>
§temperature: Option<f64>
What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
We generally recommend altering this or top_p
but not both.
top_p: Option<f64>
An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.
We generally recommend altering this or temperature
but not both.
user: Option<String>
A stable identifier for your end-users. Used to boost cache hit rates by better bucketing similar requests and to help OpenAI detect and prevent abuse. Learn more.
service_tier: Option<ServiceTier>
Implementations§
Source§impl ModelResponseProperties
impl ModelResponseProperties
Sourcepub fn builder() -> ModelResponsePropertiesBuilder<((), (), (), (), ())>
pub fn builder() -> ModelResponsePropertiesBuilder<((), (), (), (), ())>
Create a builder for building ModelResponseProperties
.
On the builder, call .metadata(...)
(optional), .temperature(...)
(optional), .top_p(...)
(optional), .user(...)
(optional), .service_tier(...)
(optional) to set the values of the fields.
Finally, call .build()
to create the instance of ModelResponseProperties
.
Trait Implementations§
Source§impl Clone for ModelResponseProperties
impl Clone for ModelResponseProperties
Source§fn clone(&self) -> ModelResponseProperties
fn clone(&self) -> ModelResponseProperties
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read more