Struct ChatArguments 

pub struct ChatArguments {

    pub model: String,
    pub messages: Vec<Message>,
    pub temperature: Option<f32>,
    pub top_p: Option<f32>,
    pub n: Option<u32>,
    pub stream: Option<bool>,
    pub stop: Option<String>,
    pub max_tokens: Option<u32>,
    pub presence_penalty: Option<f32>,
    pub frequency_penalty: Option<f32>,
    pub user: Option<String>,
    pub response_format: Option<ResponseFormat>,
    pub image_generation: Option<ImageGeneration>,
    pub grok_tools: Option<Vec<GrokTool>>,
    pub tools: Option<Vec<OpenAITool>>,
}

Fields

model: String

messages: Vec<Message>

temperature: Option<f32>

top_p: Option<f32>

n: Option<u32>

stream: Option<bool>

stop: Option<String>

max_tokens: Option<u32>

presence_penalty: Option<f32>

frequency_penalty: Option<f32>

user: Option<String>

response_format: Option<ResponseFormat>

image_generation: Option<ImageGeneration>

grok_tools: Option<Vec<GrokTool>>

xAI Agent Tools API - server-side tools for agentic capabilities. Includes: web_search, x_search, code_execution, collections_search, mcp. See: https://docs.x.ai/docs/guides/tools/overview

tools: Option<Vec<OpenAITool>>

OpenAI Agent Tools API - server-side tools for agentic capabilities (Responses API only). Includes: web_search, file_search, code_interpreter. Note: When tools are provided, use create_openai_responses() to use the Responses API endpoint. See: https://platform.openai.com/docs/guides/tools-web-search

Implementations

impl ChatArguments

pub fn new(model: impl AsRef<str>, messages: Vec<Message>) -> ChatArguments

Examples found in repository

examples/chat_example.rs (lines 7-13)

async fn main() {
    let client = openai_rust::Client::new(&std::env::var("OPENAI_API_KEY").unwrap());
    let args = openai_rust::chat::ChatArguments::new(
        "gpt-3.5-turbo",
        vec![openai_rust::chat::Message {
            role: "user".to_owned(),
            content: "Hello GPT!".to_owned(),
        }],
    );
    let res = client.create_chat(args, None).await.unwrap();
    println!("{}", res);
}

examples/chat_stream_example.rs (lines 9-15)

async fn main() {
    let client = openai_rust::Client::new(&std::env::var("OPENAI_API_KEY").unwrap());
    let args = openai_rust::chat::ChatArguments::new(
        "gpt-3.5-turbo",
        vec![openai_rust::chat::Message {
            role: "user".to_owned(),
            content: "Hello GPT!".to_owned(),
        }],
    );
    let mut res = client.create_chat_stream(args, None).await.unwrap();
    while let Some(chunk) = res.next().await {
        print!("{}", chunk.unwrap());
        std::io::stdout().flush().unwrap();
    }
}

pub fn with_grok_tools(self, tools: Vec<GrokTool>) -> Self

Add xAI server-side tools for agentic capabilities. Recommended model: grok-4-1-fast for best tool-calling performance.

pub fn with_openai_tools(self, tools: Vec<OpenAITool>) -> Self

Add OpenAI server-side tools for agentic capabilities (Responses API). Note: When tools are provided, use create_openai_responses() to use the Responses API endpoint. Recommended models: gpt-5, gpt-4o.

Trait Implementations

impl Clone for ChatArguments

fn clone(&self) -> ChatArguments

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ChatArguments

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

Formats the value using the given formatter.

impl Serialize for ChatArguments

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

where __S: Serializer,

Serialize this value into the given Serde serializer.