Struct CreateAssistantRequest 

pub struct CreateAssistantRequest {
    pub model: Model,
    pub name: Option<String>,
    pub description: Option<String>,
    pub instructions: Option<String>,
    pub reasoning_effort: Option<ReasoningEffort>,
    pub tools: Option<Vec<AssistantTool>>,
    pub tool_resources: Option<ToolResources>,
    pub metadata: Option<Metadata>,
    pub temperature: Option<Number>,
    pub top_p: Option<Number>,
    pub response_format: Option<AssistantsApiResponseFormatOption>,
}

Fields

model: Model

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.

name: Option<String>

The name of the assistant. The maximum length is 256 characters.

description: Option<String>

The description of the assistant. The maximum length is 512 characters.

instructions: Option<String>

The system instructions that the assistant uses. The maximum length is 256,000 characters.

reasoning_effort: Option<ReasoningEffort>

tools: Option<Vec<AssistantTool>>

A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types code_interpreter, file_search, or function.

tool_resources: Option<ToolResources>

A set of resources that are used by the assistant’s tools. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.

metadata: Option<Metadata>

temperature: Option<Number>

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.

top_p: Option<Number>

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.

response_format: Option<AssistantsApiResponseFormatOption>

Implementations

impl CreateAssistantRequest

pub fn builder() -> CreateAssistantRequestBuilder<((), (), (), (), (), (), (), (), (), (), ())>

Create a builder for building CreateAssistantRequest. On the builder, call .model(...), .name(...)(optional), .description(...)(optional), .instructions(...)(optional), .reasoning_effort(...)(optional), .tools(...)(optional), .tool_resources(...)(optional), .metadata(...)(optional), .temperature(...)(optional), .top_p(...)(optional), .response_format(...)(optional) to set the values of the fields. Finally, call .build() to create the instance of CreateAssistantRequest.

Trait Implementations

impl Clone for CreateAssistantRequest

fn clone(&self) -> CreateAssistantRequest

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateAssistantRequest

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for CreateAssistantRequest

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for CreateAssistantRequest

fn eq(&self, other: &CreateAssistantRequest) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for CreateAssistantRequest

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for CreateAssistantRequest