pub struct ChatCompletionRequestBuilder { /* private fields */ }
Expand description
Builder for ChatCompletionRequest
.
Implementations§
Source§impl ChatCompletionRequestBuilder
impl ChatCompletionRequestBuilder
Sourcepub fn messages<VALUE: Into<Vec<ChatCompletionMessage>>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn messages<VALUE: Into<Vec<ChatCompletionMessage>>>( &mut self, value: VALUE, ) -> &mut Self
A list of messages comprising the conversation so far.
Sourcepub fn model(&mut self, value: ChatCompleteModel) -> &mut Self
pub fn model(&mut self, value: ChatCompleteModel) -> &mut Self
ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.
Sourcepub fn frequency_penalty(&mut self, value: f32) -> &mut Self
pub fn frequency_penalty(&mut self, value: f32) -> &mut Self
Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model’s likelihood to repeat the same line verbatim.
Sourcepub fn max_tokens(&mut self, value: usize) -> &mut Self
pub fn max_tokens(&mut self, value: usize) -> &mut Self
The maximum number of tokens to generate in the chat completion.
Sourcepub fn n(&mut self, value: usize) -> &mut Self
pub fn n(&mut self, value: usize) -> &mut Self
How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.
Sourcepub fn presence_penalty(&mut self, value: f32) -> &mut Self
pub fn presence_penalty(&mut self, value: f32) -> &mut Self
Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model’s likelihood to talk about new topics.
Sourcepub fn response_format(&mut self, value: ChatResponseFormatObject) -> &mut Self
pub fn response_format(&mut self, value: ChatResponseFormatObject) -> &mut Self
An object specifying the format that the model must output. Setting to { “type”: “json_object” } enables JSON mode, which guarantees the message the model generates is valid JSON.
Sourcepub fn seed(&mut self, value: usize) -> &mut Self
pub fn seed(&mut self, value: usize) -> &mut Self
This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result. Determinism is not guaranteed, and you should refer to the system_fingerprint response parameter to monitor changes in the backend.
Sourcepub fn stop(&mut self, value: String) -> &mut Self
pub fn stop(&mut self, value: String) -> &mut Self
Up to 4 sequences where the API will stop generating further tokens.
Sourcepub fn stream(&mut self, value: bool) -> &mut Self
pub fn stream(&mut self, value: bool) -> &mut Self
If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only server-sent events as they become available, with the stream terminated by a data: [DONE] message.
Sourcepub fn temperature(&mut self, value: f32) -> &mut Self
pub fn temperature(&mut self, value: f32) -> &mut Self
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.
Sourcepub fn top_p(&mut self, value: f32) -> &mut Self
pub fn top_p(&mut self, value: f32) -> &mut Self
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.
Sourcepub fn tools<VALUE: Into<Vec<Tool>>>(&mut self, value: VALUE) -> &mut Self
pub fn tools<VALUE: Into<Vec<Tool>>>(&mut self, value: VALUE) -> &mut Self
A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for.
Sourcepub fn tool_choice(&mut self, value: ToolChoice) -> &mut Self
pub fn tool_choice(&mut self, value: ToolChoice) -> &mut Self
Controls which (if any) function is called by the model. none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function. Specifying a particular function via {“type: “function”, “function”: {“name”: “my_function”}} forces the model to call that function. none is the default when no functions are present. auto is the default if functions are present.
Sourcepub fn user<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
pub fn user<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.
Sourcepub fn build(
&self,
) -> Result<ChatCompletionRequest, ChatCompletionRequestBuilderError>
pub fn build( &self, ) -> Result<ChatCompletionRequest, ChatCompletionRequestBuilderError>
Trait Implementations§
Source§impl Clone for ChatCompletionRequestBuilder
impl Clone for ChatCompletionRequestBuilder
Source§fn clone(&self) -> ChatCompletionRequestBuilder
fn clone(&self) -> ChatCompletionRequestBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
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