pub struct CreateTranscriptionRequestArgs { /* private fields */ }Expand description
Builder for CreateTranscriptionRequest.
Implementations§
Source§impl CreateTranscriptionRequestArgs
impl CreateTranscriptionRequestArgs
Sourcepub fn file<VALUE: Into<AudioInput>>(&mut self, value: VALUE) -> &mut Self
pub fn file<VALUE: Into<AudioInput>>(&mut self, value: VALUE) -> &mut Self
The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
Sourcepub fn model<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
pub fn model<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
ID of the model to use. The options are gpt-4o-transcribe, gpt-4o-mini-transcribe, whisper-1
(which is powered by our open source Whisper V2 model), and gpt-4o-transcribe-diarize.
Sourcepub fn language<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
pub fn language<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
The language of the input audio. Supplying the input language in
ISO-639-1 (e.g. en) format will improve
accuracy and latency.
Sourcepub fn prompt<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
pub fn prompt<VALUE: Into<String>>(&mut self, value: VALUE) -> &mut Self
An optional text to guide the model’s style or continue a previous audio segment. The
prompt should match the audio
language. This field is not supported when using gpt-4o-transcribe-diarize.
Sourcepub fn response_format<VALUE: Into<AudioResponseFormat>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn response_format<VALUE: Into<AudioResponseFormat>>( &mut self, value: VALUE, ) -> &mut Self
The format of the output, in one of these options: json, text, srt, verbose_json, vtt, or
diarized_json. For gpt-4o-transcribe and gpt-4o-mini-transcribe, the only supported format is
json. For gpt-4o-transcribe-diarize, the supported formats are json, text, and
diarized_json, with diarized_json required to receive speaker annotations.
Sourcepub fn temperature<VALUE: Into<f32>>(&mut self, value: VALUE) -> &mut Self
pub fn temperature<VALUE: Into<f32>>(&mut self, value: VALUE) -> &mut Self
TThe 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.
Sourcepub fn include<VALUE: Into<Vec<TranscriptionInclude>>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn include<VALUE: Into<Vec<TranscriptionInclude>>>( &mut self, value: VALUE, ) -> &mut Self
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. This field is not supported when
using gpt-4o-transcribe-diarize.
Sourcepub fn timestamp_granularities<VALUE: Into<Vec<TimestampGranularity>>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn timestamp_granularities<VALUE: Into<Vec<TimestampGranularity>>>( &mut self, value: VALUE, ) -> &mut Self
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. This option is not available for gpt-4o-transcribe-diarize.
Sourcepub fn stream<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self
pub fn stream<VALUE: Into<bool>>(&mut self, value: VALUE) -> &mut Self
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.
Sourcepub fn chunking_strategy<VALUE: Into<TranscriptionChunkingStrategy>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn chunking_strategy<VALUE: Into<TranscriptionChunkingStrategy>>( &mut self, value: VALUE, ) -> &mut Self
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. Required when using gpt-4o-transcribe-diarize for inputs longer than 30
seconds.
Sourcepub fn known_speaker_names<VALUE: Into<Vec<String>>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn known_speaker_names<VALUE: Into<Vec<String>>>( &mut self, value: VALUE, ) -> &mut Self
Optional list of speaker names that correspond to the audio samples provided in
known_speaker_references[]. Each entry should be a short identifier (for example customer or
agent). Up to 4 speakers are supported.
Sourcepub fn known_speaker_references<VALUE: Into<Vec<String>>>(
&mut self,
value: VALUE,
) -> &mut Self
pub fn known_speaker_references<VALUE: Into<Vec<String>>>( &mut self, value: VALUE, ) -> &mut Self
Optional list of audio samples (as data
URLs) that contain
known speaker references matching known_speaker_names[]. Each sample must be between 2 and 10
seconds, and can use any of the same input audio formats supported by file.
Sourcepub fn build(&self) -> Result<CreateTranscriptionRequest, OpenAIError>
pub fn build(&self) -> Result<CreateTranscriptionRequest, OpenAIError>
Trait Implementations§
Source§impl Clone for CreateTranscriptionRequestArgs
impl Clone for CreateTranscriptionRequestArgs
Source§fn clone(&self) -> CreateTranscriptionRequestArgs
fn clone(&self) -> CreateTranscriptionRequestArgs
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read more