Class: OpenAI::Resources::Audio::Transcriptions

Inherits:
Object
  • Object
show all
Defined in:
lib/openai/resources/audio/transcriptions.rb,
sig/openai/resources/audio/transcriptions.rbs

Overview

Turn audio into text or text into audio.

Instance Method Summary collapse

Constructor Details

#initialize(client:) ⇒ Transcriptions

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Returns a new instance of Transcriptions.

Parameters:



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# File 'lib/openai/resources/audio/transcriptions.rb', line 265

def initialize(client:)
  @client = client
end

Instance Method Details

#create(file:, model:, chunking_strategy: nil, include: nil, keywords: nil, known_speaker_names: nil, known_speaker_references: nil, language: nil, languages: nil, prompt: nil, response_format: nil, temperature: nil, timestamp_granularities: nil, request_options: {}) ⇒ OpenAI::Models::Audio::Transcription, ...

See OpenAI::Resources::Audio::Transcriptions#create_streaming for streaming counterpart.

Transcribes audio into the input language.

Returns a transcription object in json, diarized_json, or verbose_json format, or a stream of transcript events.

String, StringIO, and pathless IO inputs are sent with generic upload metadata. Use OpenAI::FilePart when you need to override the filename or content type.

Parameters:

  • file (Pathname, StringIO, IO, String, OpenAI::FilePart) —

    The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm. The request must include enough format metadata for the file to be identified. We recommend an extension-bearing filename and an appropriate content type.

    String, StringIO, and pathless IO inputs are sent with generic upload metadata. Use OpenAI::FilePart when you need to override the filename or content type.

  • model (String, Symbol, OpenAI::Models::AudioModel) —

    ID of the model to use. The options are gpt-transcribe, gpt-4o-transcribe, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, whisper-1 (which is powered by our open source Whisper V2 model), and gpt-4o-transcribe-diarize.

  • chunking_strategy (Symbol, :auto, OpenAI::Models::Audio::TranscriptionCreateParams::ChunkingStrategy::VadConfig, nil) —

    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.

  • include (Array<Symbol, OpenAI::Models::Audio::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, gpt-4o-mini-transcribe, and gpt-4o-mini-transcribe-2025-12-15. This field is not supported when using gpt-4o-transcribe-diarize.

  • keywords (Array<String>) —

    Words or phrases to guide transcription of the input audio. Supported by gpt-transcribe.

  • known_speaker_names (Array<String>) —

    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.

  • known_speaker_references (Array<String>) —

    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.

  • language (String) —

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

  • languages (Array<String>) —

    Possible languages of the input audio, in ISO-639-1 format. Supported by gpt-transcribe.

  • prompt (String) —

    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.

  • response_format (Symbol, OpenAI::Models::AudioResponseFormat) —

    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.

  • temperature (Float) —

    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.

  • timestamp_granularities (Array<Symbol, OpenAI::Models::Audio::TranscriptionCreateParams::TimestampGranularity>) —

    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.

  • request_options (OpenAI::RequestOptions, Hash{Symbol=>Object}, nil)

Returns:

See Also:



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# File 'lib/openai/resources/audio/transcriptions.rb', line 114

def create(params)
  parsed, options = OpenAI::Audio::TranscriptionCreateParams.dump_request(params)
  if parsed[:stream]
    message = "Please use `#create_streaming` for the streaming use case."
    raise ArgumentError.new(message)
  end

  @client.request(
    method: :post,
    path: "audio/transcriptions",
    headers: {"content-type" => "multipart/form-data"},
    body: parsed,
    model: OpenAI::Models::Audio::TranscriptionCreateResponse,
    security: {bearer_auth: true},
    options: options
  )
end

#create_streaming(file:, model:, chunking_strategy: nil, include: nil, keywords: nil, known_speaker_names: nil, known_speaker_references: nil, language: nil, languages: nil, prompt: nil, response_format: nil, temperature: nil, timestamp_granularities: nil, request_options: {}) ⇒ OpenAI::Internal::Stream<OpenAI::Models::Audio::TranscriptionTextSegmentEvent, OpenAI::Models::Audio::TranscriptionTextDeltaEvent, OpenAI::Models::Audio::TranscriptionTextDoneEvent>

See OpenAI::Resources::Audio::Transcriptions#create for non-streaming counterpart.

Transcribes audio into the input language.

Returns a transcription object in json, diarized_json, or verbose_json format, or a stream of transcript events.

String, StringIO, and pathless IO inputs are sent with generic upload metadata. Use OpenAI::FilePart when you need to override the filename or content type.

Parameters:

  • file (Pathname, StringIO, IO, String, OpenAI::FilePart) —

    The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm. The request must include enough format metadata for the file to be identified. We recommend an extension-bearing filename and an appropriate content type.

    String, StringIO, and pathless IO inputs are sent with generic upload metadata. Use OpenAI::FilePart when you need to override the filename or content type.

  • model (String, Symbol, OpenAI::Models::AudioModel) —

    ID of the model to use. The options are gpt-transcribe, gpt-4o-transcribe, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, whisper-1 (which is powered by our open source Whisper V2 model), and gpt-4o-transcribe-diarize.

  • chunking_strategy (Symbol, :auto, OpenAI::Models::Audio::TranscriptionCreateParams::ChunkingStrategy::VadConfig, nil) —

    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.

  • include (Array<Symbol, OpenAI::Models::Audio::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, gpt-4o-mini-transcribe, and gpt-4o-mini-transcribe-2025-12-15. This field is not supported when using gpt-4o-transcribe-diarize.

  • keywords (Array<String>) —

    Words or phrases to guide transcription of the input audio. Supported by gpt-transcribe.

  • known_speaker_names (Array<String>) —

    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.

  • known_speaker_references (Array<String>) —

    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.

  • language (String) —

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

  • languages (Array<String>) —

    Possible languages of the input audio, in ISO-639-1 format. Supported by gpt-transcribe.

  • prompt (String) —

    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.

  • response_format (Symbol, OpenAI::Models::AudioResponseFormat) —

    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.

  • temperature (Float) —

    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.

  • timestamp_granularities (Array<Symbol, OpenAI::Models::Audio::TranscriptionCreateParams::TimestampGranularity>) —

    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.

  • request_options (OpenAI::RequestOptions, Hash{Symbol=>Object}, nil)

Returns:

See Also:



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# File 'lib/openai/resources/audio/transcriptions.rb', line 238

def create_streaming(params)
  parsed, options = OpenAI::Audio::TranscriptionCreateParams.dump_request(params)
  unless parsed.fetch(:stream, true)
    message = "Please use `#create` for the non-streaming use case."
    raise ArgumentError.new(message)
  end

  parsed.store(:stream, true)
  @client.request(
    method: :post,
    path: "audio/transcriptions",
    headers: {
      "content-type" => "multipart/form-data",
      "accept" => "text/event-stream",
      "accept-encoding" => "identity"
    },
    body: parsed,
    stream: OpenAI::Internal::Stream,
    model: OpenAI::Audio::TranscriptionStreamEvent,
    security: {bearer_auth: true},
    options: options
  )
end