Struct CreateTranscriptionRequest

pub struct CreateTranscriptionRequest {
    pub file: Vec<u8>,
    pub model: String,
    pub language: Option<String>,
    pub prompt: Option<String>,
    pub response_format: Option<AudioResponseFormat>,
    pub temperature: Option<Number>,
    pub include: Option<Vec<TranscriptionInclude>>,
    pub timestamp_granularities: Option<Vec<CreateTranscriptionRequestTimestampGranularities>>,
    pub stream: Option<bool>,
    pub chunking_strategy: Option<String>,
}

Fields

file: Vec<u8>

The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.

model: String

ID of the model to use. The options are gpt-4o-transcribe, gpt-4o-mini-transcribe, and whisper-1 (which is powered by our open source Whisper V2 model).

language: Option<String>

The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

prompt: Option<String>

An optional text to guide the model’s style or continue a previous audio segment. The prompt should match the audio language.

response_format: Option<AudioResponseFormat>

temperature: Option<Number>

The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use log probability to automatically increase the temperature until certain thresholds are hit.

include: Option<Vec<TranscriptionInclude>>

Additional information to include in the transcription response. logprobs will return the log probabilities of the tokens in the response to understand the model’s confidence in the transcription. logprobs only works with response_format set to json and only with the models gpt-4o-transcribe and gpt-4o-mini-transcribe.

timestamp_granularities: Option<Vec<CreateTranscriptionRequestTimestampGranularities>>

The timestamp granularities to populate for this transcription. response_format must be set verbose_json to use timestamp granularities. Either or both of these options are supported: word, or segment. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency.

stream: Option<bool>

If set to true, the model response data will be streamed to the client as it is generated using server-sent events. See the Streaming section of the Speech-to-Text guide for more information.

Note: Streaming is not supported for the whisper-1 model and will be ignored.

chunking_strategy: Option<String>

Controls how the audio is cut into chunks. When set to "auto", the server first normalizes loudness and then uses voice activity detection (VAD) to choose boundaries. server_vad object can be provided to tweak VAD detection parameters manually. If unset, the audio is transcribed as a single block.

Implementations

impl CreateTranscriptionRequest

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

Create a builder for building CreateTranscriptionRequest. On the builder, call .file(...), .model(...), .language(...)(optional), .prompt(...)(optional), .response_format(...)(optional), .temperature(...)(optional), .include(...)(optional), .timestamp_granularities(...)(optional), .stream(...)(optional), .chunking_strategy(...)(optional) to set the values of the fields. Finally, call .build() to create the instance of CreateTranscriptionRequest.

Trait Implementations

impl Clone for CreateTranscriptionRequest

fn clone(&self) -> CreateTranscriptionRequest

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CreateTranscriptionRequest

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for CreateTranscriptionRequest

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for CreateTranscriptionRequest

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

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

const 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 CreateTranscriptionRequest

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 CreateTranscriptionRequest