Struct OpenResponsesCreateRequest 

pub struct OpenResponsesCreateRequest {

    pub model: String,
    pub input: OpenResponsesInput,
    pub instructions: Option<String>,
    pub previous_response_id: Option<String>,
    pub stream: Option<bool>,
    pub stream_options: Option<StreamOptions>,
    pub background: Option<bool>,
    pub store: Option<bool>,
    pub metadata: Option<Value>,
    pub include: Option<Vec<IncludeOption>>,
    pub max_output_tokens: Option<usize>,
    pub temperature: Option<f64>,
    pub top_p: Option<f64>,
    pub presence_penalty: Option<f32>,
    pub frequency_penalty: Option<f32>,
    pub top_logprobs: Option<usize>,
    pub tools: Option<Vec<Tool>>,
    pub tool_choice: Option<ToolChoice>,
    pub parallel_tool_calls: Option<bool>,
    pub max_tool_calls: Option<usize>,
    pub reasoning: Option<ReasoningConfig>,
    pub text: Option<TextConfig>,
    pub truncation: Option<TruncationStrategy>,
    pub stop_seqs: Option<StopTokens>,
    pub response_format: Option<ResponseFormat>,
    pub logit_bias: Option<HashMap<u32, f32>>,
    pub logprobs: bool,
    pub n_choices: usize,
    pub repetition_penalty: Option<f32>,
    pub top_k: Option<usize>,
    pub grammar: Option<Grammar>,
    pub min_p: Option<f64>,
    pub dry_multiplier: Option<f32>,
    pub dry_base: Option<f32>,
    pub dry_allowed_length: Option<usize>,
    pub dry_sequence_breakers: Option<Vec<String>>,
    pub web_search_options: Option<WebSearchOptions>,
}

OpenResponses API create request

Fields

model: String

The model to use for this request

input: OpenResponsesInput

The input for the response - can be a string or array of input items

instructions: Option<String>

Additional instructions that guide the model’s behavior

previous_response_id: Option<String>

ID of a previous response for multi-turn conversations

stream: Option<bool>

Whether to stream the response using server-sent events

stream_options: Option<StreamOptions>

Stream options for controlling streaming behavior

background: Option<bool>

Whether to run the request in background (async)

store: Option<bool>

Whether to store the response for later retrieval

metadata: Option<Value>

User-provided metadata (up to 16 key-value pairs)

include: Option<Vec<IncludeOption>>

Specifies additional content to include in the response

max_output_tokens: Option<usize>

Maximum number of output tokens to generate

temperature: Option<f64>

Temperature for sampling (0-2)

top_p: Option<f64>

Top-p (nucleus) sampling parameter (0-1)

presence_penalty: Option<f32>

Presence penalty (-2.0 to 2.0)

frequency_penalty: Option<f32>

Frequency penalty (-2.0 to 2.0)

top_logprobs: Option<usize>

Number of top log probabilities to return

tools: Option<Vec<Tool>>

Tool definitions available for the model to call

tool_choice: Option<ToolChoice>

Controls how the model uses tools

parallel_tool_calls: Option<bool>

Whether to allow parallel tool calls.

NOTE: Only true (default) or None is supported. Setting this to false will return an error as mistral.rs does not support disabling parallel tool calls.

max_tool_calls: Option<usize>

Maximum number of tool calls allowed.

NOTE: This parameter is not supported. Setting any value will return an error as mistral.rs does not support limiting the number of tool calls.

reasoning: Option<ReasoningConfig>

Configuration for reasoning/thinking behavior

text: Option<TextConfig>

Text output configuration

truncation: Option<TruncationStrategy>

Truncation strategy when input exceeds context window

stop_seqs: Option<StopTokens>

Stop sequences to end generation

response_format: Option<ResponseFormat>

Response format (legacy, prefer text field)

logit_bias: Option<HashMap<u32, f32>>

Logit bias for token manipulation

logprobs: bool

Whether to return log probabilities

n_choices: usize

Number of completions to generate

repetition_penalty: Option<f32>

Repetition penalty (mistral.rs extension)

top_k: Option<usize>

Top-k sampling (mistral.rs extension)

grammar: Option<Grammar>

Grammar for constrained generation (mistral.rs extension)

min_p: Option<f64>

Min-p sampling (mistral.rs extension)

dry_multiplier: Option<f32>

DRY multiplier (mistral.rs extension)

dry_base: Option<f32>

DRY base (mistral.rs extension)

dry_allowed_length: Option<usize>

DRY allowed length (mistral.rs extension)

dry_sequence_breakers: Option<Vec<String>>

DRY sequence breakers (mistral.rs extension)

web_search_options: Option<WebSearchOptions>

Web search options (mistral.rs extension)

Trait Implementations

impl Clone for OpenResponsesCreateRequest

fn clone(&self) -> OpenResponsesCreateRequest

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl ComposeSchema for OpenResponsesCreateRequest

fn compose(generics: Vec<RefOr<Schema>>) -> RefOr<Schema>

impl Debug for OpenResponsesCreateRequest

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for OpenResponsesCreateRequest

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for OpenResponsesCreateRequest

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl ToSchema for OpenResponsesCreateRequest

fn name() -> Cow<'static, str>

Return name of the schema.

fn schemas(schemas: &mut Vec<(String, RefOr<Schema>)>)

Implement reference [utoipa::openapi::schema::Schema]s for this type.