Spaces:
Build error
Build error
release 0.1
Browse files- packages.txt +2 -0
- src/src/__pycache__/elevenlabs.cpython-310.pyc +0 -0
- src/src/__pycache__/elevenlabs.cpython-39.pyc +0 -0
- src/src/__pycache__/openailib.cpython-310.pyc +0 -0
- src/src/__pycache__/openailib.cpython-39.pyc +0 -0
- src/src/__pycache__/tube.cpython-310.pyc +0 -0
- src/src/__pycache__/tube.cpython-39.pyc +0 -0
- src/src/__pycache__/utils.cpython-310.pyc +0 -0
- src/src/__pycache__/utils.cpython-39.pyc +0 -0
- src/src/elevenlabs.py +115 -0
- src/src/openailib.py +47 -0
- src/src/tube.py +64 -0
- src/src/utils.py +16 -0
packages.txt
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portaudio19-dev
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python3-pyaudio
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src/src/__pycache__/elevenlabs.cpython-310.pyc
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Binary file (4.12 kB). View file
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src/src/__pycache__/elevenlabs.cpython-39.pyc
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src/src/__pycache__/openailib.cpython-310.pyc
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src/src/__pycache__/openailib.cpython-39.pyc
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Binary file (1.23 kB). View file
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src/src/__pycache__/tube.cpython-310.pyc
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Binary file (1.82 kB). View file
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src/src/__pycache__/tube.cpython-39.pyc
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Binary file (1.81 kB). View file
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src/src/__pycache__/utils.cpython-310.pyc
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src/src/__pycache__/utils.cpython-39.pyc
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Binary file (637 Bytes). View file
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src/src/elevenlabs.py
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import asyncio
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import io
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import logging
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import os
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import time
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from concurrent.futures import ThreadPoolExecutor
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from dataclasses import dataclass
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from typing import Dict, List, Union, Tuple
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import sounddevice as sd
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import soundfile as sf
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from elevenlabslib import ElevenLabsUser, ElevenLabsVoice
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from .utils import timeit
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logging.basicConfig(level=logging.INFO)
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log = logging.getLogger(__name__)
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USER = ElevenLabsUser(os.environ["ELEVENLABS_API_KEY"])
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@dataclass
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class Speaker:
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name: str
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voice: ElevenLabsVoice
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color: str
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description: str = None
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async def text_to_speechbytes_async(text, speaker, loop):
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with ThreadPoolExecutor() as executor:
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speech_bytes = await loop.run_in_executor(executor, text_to_speechbytes, text, speaker.voice)
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return speech_bytes
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async def play_history(history: List[Tuple[Speaker, str]]):
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loop = asyncio.get_event_loop()
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# Create a list of tasks for all text_to_speechbytes function calls
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tasks = [text_to_speechbytes_async(
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text, speaker, loop) for speaker, text in history]
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# Run tasks concurrently, waiting for the first one to complete
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for speech_bytes in await asyncio.gather(*tasks):
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audioFile = io.BytesIO(speech_bytes)
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soundFile = sf.SoundFile(audioFile)
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sd.play(soundFile.read(), samplerate=soundFile.samplerate, blocking=True)
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async def save_history(history: List[Tuple[Speaker, str]], audio_savepath: str):
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loop = asyncio.get_event_loop()
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# Create a list of tasks for all text_to_speechbytes function calls
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tasks = [text_to_speechbytes_async(
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text, speaker, loop) for speaker, text in history]
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# Run tasks concurrently, waiting for the first one to complete
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all_speech_bytes = await asyncio.gather(*tasks)
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# Combine all audio bytes into a single audio file
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concatenated_audio = io.BytesIO(b''.join(all_speech_bytes))
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# Save the combined audio file to disk
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with sf.SoundFile(concatenated_audio, mode='r') as soundFile:
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with sf.SoundFile(
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audio_savepath, mode='w',
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samplerate=soundFile.samplerate,
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channels=soundFile.channels,
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) as outputFile:
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outputFile.write(soundFile.read())
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def check_voice_exists(voice: Union[ElevenLabsVoice, str]) -> Union[ElevenLabsVoice, None]:
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log.info(f"Getting voice {voice}...")
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_available_voices = USER.get_voices_by_name(voice)
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if _available_voices:
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log.info(f"Voice {voice} already exists, found {_available_voices}.")
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return _available_voices[0]
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return None
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@timeit
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def get_make_voice(voice: Union[ElevenLabsVoice, str], audio_path: List[str] = None) -> ElevenLabsVoice:
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_voice = check_voice_exists(voice)
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if _voice is not None:
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return _voice
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else:
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if USER.get_voice_clone_available():
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assert audio_path is not None, "audio_path must be provided"
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assert isinstance(audio_path, list), "audio_path must be a list"
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log.info(f"Cloning voice {voice}...")
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_audio_source_dict = {
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# Audio path is a PosixPath
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_.name: open(_, "rb").read() for _ in audio_path
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}
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newVoice = USER.clone_voice_bytes(voice, _audio_source_dict)
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return newVoice
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raise ValueError(
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f"Voice {voice} does not exist and cloning is not available.")
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@timeit
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def text_to_speech(text: str, voice: ElevenLabsVoice):
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log.info(f"Generating audio using voice {voice}...")
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time_start = time.time()
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voice.generate_and_play_audio(text, playInBackground=False)
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duration = time.time() - time_start
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return duration
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@timeit
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def text_to_speechbytes(text: str, voice: ElevenLabsVoice):
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log.info(f"Generating audio for voice {voice} text {text}...")
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audio_bytes = voice.generate_audio_bytes(text)
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return audio_bytes
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src/src/openailib.py
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import logging
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import os
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from .utils import timeit
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import openai
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openai.api_key = os.getenv("OPENAI_API_KEY")
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logging.basicConfig(level=logging.INFO)
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log = logging.getLogger(__name__)
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@timeit
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def speech_to_text(audio_path):
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log.info("Transcribing audio...")
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transcript = openai.Audio.transcribe("whisper-1", open(audio_path, "rb"))
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text = transcript["text"]
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log.info(f"Transcript: \n\t{text}")
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return text
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@timeit
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def top_response(prompt, system=None, model="gpt-3.5-turbo", max_tokens=20, temperature=0.8):
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_prompt = [
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{
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"role": "user",
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"content": prompt,
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},
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]
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if system:
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_prompt = [
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{
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"role": "system",
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"content": system,
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},
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] + _prompt
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log.info(f"API call to {model} with prompt: \n\n\t{_prompt}\n\n")
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_response = openai.ChatCompletion.create(
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model=model,
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messages=_prompt,
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temperature=temperature,
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n=1,
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max_tokens=max_tokens,
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)
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log.info(f"API reponse: \n\t{_response}")
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response: str = _response['choices'][0]['message']['content']
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return response
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src/src/tube.py
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'''
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Extract audio from a YouTube video
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Usage:
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tube.py <url> <person> [-s <start_time>] [-d <duration>]
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'''
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import subprocess
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from pathlib import Path
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import datetime
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import argparse
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import os
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from pytube import YouTube
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# Define argparse arguments
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parser = argparse.ArgumentParser(description='Extract audio from a YouTube video')
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parser.add_argument('url', type=str, help='the YouTube video URL')
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parser.add_argument('person', type=str, help='the name of the person speaking')
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parser.add_argument('-s', '--start-time', type=float, default=0, help='the start time in minutes for the extracted audio (default: 0)')
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parser.add_argument('-d', '--duration', type=int, help='the duration in seconds for the extracted audio (default: 60)')
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# 200 seconds seems to be max duration for single clips
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def extract_audio(url: str, label: str, start_minute: float = 0, duration: int = 200):
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# Download the YouTube video
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youtube_object = YouTube(url)
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stream = youtube_object.streams.first()
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video_path = Path(stream.download(skip_existing=True))
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# Convert start time to seconds
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start_time_seconds = int(start_minute * 60)
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# Format the start time in HH:MM:SS.mmm format
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start_time_formatted = str(datetime.timedelta(seconds=start_time_seconds))
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start_time_formatted = start_time_formatted[:11] + start_time_formatted[12:]
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# Set the output path using the audio file name
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output_path = video_path.parent / f"{label}.wav"
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# Run ffmpeg to extract the audio
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cmd = ['ffmpeg', '-y', '-i', str(video_path), '-ss', start_time_formatted]
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if duration is not None:
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# Format the duration in HH:MM:SS.mmm format
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duration_formatted = str(datetime.timedelta(seconds=duration))
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duration_formatted = duration_formatted[:11] + duration_formatted[12:]
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cmd += ['-t', duration_formatted]
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cmd += ['-q:a', '0', '-map', 'a', str(output_path)]
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subprocess.run(cmd)
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# remove the extra .3gpp file that is created:
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for file in os.listdir(video_path.parent):
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if file.endswith(".3gpp"):
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os.remove(os.path.join(video_path.parent, file))
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return output_path
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if __name__ == '__main__':
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# Parse the arguments
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args = parser.parse_args()
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# Extract the audio
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extract_audio(args.url, args.person, args.start_time, args.duration)
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src/src/utils.py
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import time
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import logging
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log = logging.getLogger(__name__)
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# Decorator to time a function
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def timeit(func):
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def timed(*args, **kwargs):
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time_start = time.time()
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result = func(*args, **kwargs)
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_yellow = "\x1b[33;20m"
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_reset = "\x1b[0m"
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_msg = f"{_yellow}{func.__name__} duration: {time.time() - time_start:.2f} seconds{_reset}"
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log.info(_msg)
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return result
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return timed
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