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# `langchain_community.document_loaders.parsers.audio`.OpenAIWhisperParserLocal

class langchain_community.document_loaders.parsers.audio.OpenAIWhisperParserLocal(device: str = '0', lang_model: Optional[str] = None, batch_size: int = 8, chunk_length: int = 30, forced_decoder_ids: Optional[Tuple[Dict]] = None)

  Transcribe and parse audio files with OpenAI Whisper model.

  Audio transcription with OpenAI Whisper model locally from transformers.

  Parameters: device - device to use

  > NOTE: By default uses the gpu if available, if you want to use cpu, please set device = “cpu”

  lang_model - whisper model to use, for example “openai/whisper-medium” forced_decoder_ids - id states for decoder in multilanguage model,

  > usage example: from transformers import WhisperProcessor processor = WhisperProcessor.from_pretrained(“openai/whisper-medium”) forced_decoder_ids = WhisperProcessor.get_decoder_prompt_ids(language=”french”,

  > > task=”transcribe”)

  > forced_decoder_ids = WhisperProcessor.get_decoder_prompt_ids(language=”french”, task=”translate”)

  Initialize the parser.

  Parameters

    - device (str) – device to use.

    - lang_model (Optional[str]) – whisper model to use, for example “openai/whisper-medium”. Defaults to None.

    - forced_decoder_ids (Optional[Tuple[Dict]]) – id states for decoder in a multilanguage model. Defaults to None.

    - batch_size (int) – batch size used for decoding Defaults to 8.

    - chunk_length (int) – chunk length used during inference. Defaults to 30s.

  Methods

  `__init__`([device, lang_model, batch_size, ...]) | Initialize the parser.
  `lazy_parse`(blob) | Lazily parse the blob.
  `parse`(blob) | Eagerly parse the blob into a document or documents.

  __init__(device: str = '0', lang_model: Optional[str] = None, batch_size: int = 8, chunk_length: int = 30, forced_decoder_ids: Optional[Tuple[Dict]] = None)

    Initialize the parser.

    Parameters

      - device (str) – device to use.

      - lang_model (Optional[str]) – whisper model to use, for example “openai/whisper-medium”. Defaults to None.

      - forced_decoder_ids (Optional[Tuple[Dict]]) – id states for decoder in a multilanguage model. Defaults to None.

      - batch_size (int) – batch size used for decoding Defaults to 8.

      - chunk_length (int) – chunk length used during inference. Defaults to 30s.

  lazy_parse(blob: Blob) → Iterator[Document]

    Lazily parse the blob.

    Parameters

      blob (Blob) –

    Return type

      Iterator[Document]

  parse(blob: Blob) → List[Document]

    Eagerly parse the blob into a document or documents.

    This is a convenience method for interactive development environment.

    Production applications should favor the lazy_parse method instead.

    Subclasses should generally not over-ride this parse method.

    Parameters

      blob (Blob) – Blob instance

    Returns

      List of documents

    Return type

      List[Document]