Constructor Detail

Method Detail

• file

   final ByteArray file()

  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

   final AudioModel model()

  ID of the model to use. Only whisper-1 (which is powered by our open source Whisper V2 model) is currently available.

• language

   final Optional<String> language()

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

• prompt

   final Optional<String> prompt()

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

• responseFormat

   final Optional<AudioResponseFormat> responseFormat()

  The format of the output, in one of these options: json, text, srt, verbose_json, or vtt.

• temperature

   final Optional<Double> temperature()

  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.

• timestampGranularities

   final Optional<List<AudioTranscriptionCreateParams.TimestampGranularity>> timestampGranularities()

  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.

• _file

   final MultipartField<ByteArray> _file()

  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

   final MultipartField<AudioModel> _model()

  ID of the model to use. Only whisper-1 (which is powered by our open source Whisper V2 model) is currently available.

• _language

   final MultipartField<String> _language()

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

• _prompt

   final MultipartField<String> _prompt()

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

• _responseFormat

   final MultipartField<AudioResponseFormat> _responseFormat()

  The format of the output, in one of these options: json, text, srt, verbose_json, or vtt.

• _temperature

   final MultipartField<Double> _temperature()

  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.

• _timestampGranularities

   final MultipartField<List<AudioTranscriptionCreateParams.TimestampGranularity>> _timestampGranularities()

  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.

• validate

   final AudioTranscriptionCreateParams.Body validate()

• toBuilder

   final AudioTranscriptionCreateParams.Body.Builder toBuilder()

• equals

   Boolean equals(Object other)

• hashCode

   Integer hashCode()

• toString

   String toString()

• builder

   final static AudioTranscriptionCreateParams.Body.Builder builder()

  Returns a mutable builder for constructing an instance of Body.

  The following fields are required:

  .file()
  .model()