2023-02-03 20:12:03 -08:00

65 lines
1.8 KiB
Python

"""Audio Transcriber.
A transcriber for the audio of mp3, mp4 files.
"""
from pathlib import Path
from typing import Any, Dict, Optional, List, cast
from gpt_index.readers.base import BaseReader
from gpt_index.readers.schema.base import Document
class AudioTranscriber(BaseReader):
"""Audio parser.
Extract text from transcript of video/audio files using OpenAI Whisper.
"""
def __init__(self, *args: Any, model_version: str = "base", **kwargs: Any) -> None:
"""Init params."""
super().__init__(*args, **kwargs)
self._model_version = model_version
try:
import whisper
except ImportError:
raise ValueError(
"Please install OpenAI whisper model "
"'pip install git+https://github.com/openai/whisper.git' "
"to use the model"
)
model = whisper.load_model(self._model_version)
self.parser_config = {"model": model}
def load_data(
self, file: Path, extra_info: Optional[Dict] = None
) -> List[Document]:
"""Parse file."""
import whisper
if file.name.endswith("mp4"):
try:
from pydub import AudioSegment # noqa: F401
except ImportError:
raise ValueError("Please install pydub 'pip install pydub' ")
# open file
video = AudioSegment.from_file(file, format="mp4")
# Extract audio from video
audio = video.split_to_mono()[0]
file_str = str(file)[:-4] + ".mp3"
# export file
audio.export(file_str, format="mp3")
model = cast(whisper.Whisper, self.parser_config["model"])
result = model.transcribe(str(file))
transcript = result["text"]
return [Document(transcript, extra_info=extra_info)]