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import torch
import yt_dlp as youtube_dl
from transformers import pipeline
from transformers.pipelines.audio_utils import ffmpeg_read
from langchain_core.tools import tool
import tempfile
import os
# credit https://huggingface.co/spaces/hf-audio/whisper-large-v3
MODEL_NAME = "openai/whisper-tiny.en"
BATCH_SIZE = 8
FILE_LIMIT_MB = 1000
YT_LENGTH_LIMIT_S = 3600 # limit to 1 hour YouTube files
device = "mps" if torch.mps.is_available() else "cpu"
speech_recognition_pipe = pipeline(
task="automatic-speech-recognition",
model=MODEL_NAME,
chunk_length_s=30,
device=device,
)
def download_yt_audio(yt_url, filename):
info_loader = youtube_dl.YoutubeDL()
try:
info = info_loader.extract_info(yt_url, download=False)
except youtube_dl.utils.DownloadError as err:
raise str(err)
file_length = info["duration_string"]
file_h_m_s = file_length.split(":")
file_h_m_s = [int(sub_length) for sub_length in file_h_m_s]
if len(file_h_m_s) == 1:
file_h_m_s.insert(0, 0)
if len(file_h_m_s) == 2:
file_h_m_s.insert(0, 0)
file_length_s = file_h_m_s[0] * 3600 + file_h_m_s[1] * 60 + file_h_m_s[2]
if file_length_s > YT_LENGTH_LIMIT_S:
yt_length_limit_hms = time.strftime("%HH:%MM:%SS", time.gmtime(YT_LENGTH_LIMIT_S))
file_length_hms = time.strftime("%HH:%MM:%SS", time.gmtime(file_length_s))
raise f"Maximum YouTube length is {yt_length_limit_hms}, got {file_length_hms} YouTube video."
ydl_opts = {"outtmpl": filename, "format": "worstvideo[ext=mp4]+bestaudio[ext=m4a]/best[ext=mp4]/best"}
with youtube_dl.YoutubeDL(ydl_opts) as ydl:
try:
ydl.download([yt_url])
except youtube_dl.utils.ExtractorError as err:
raise str(err)
def _return_yt_html_embed(yt_url):
video_id = yt_url.split("?v=")[-1]
HTML_str = (
f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
" </center>"
)
return HTML_str
@tool
def yt_transcribe(yt_url, max_filesize=75.0):
"""
Transcribes the audio from a given YouTube video URL.
Args:
yt_url (str): The URL of the YouTube video.
max_filesize (float, optional): The maximum allowed filesize of the video in MB.
Defaults to 75.0.
Returns:
tuple: A tuple containing:
- str: An HTML embed string for the YouTube video.
- str: The transcribed text of the video's audio.
"""
html_embed_str = _return_yt_html_embed(yt_url)
with tempfile.TemporaryDirectory() as tmpdirname:
filepath = os.path.join(tmpdirname, "video.mp4")
download_yt_audio(yt_url, filepath)
with open(filepath, "rb") as f:
inputs = f.read()
inputs = ffmpeg_read(inputs, speech_recognition_pipe.feature_extractor.sampling_rate)
inputs = {"array": inputs, "sampling_rate": speech_recognition_pipe.feature_extractor.sampling_rate}
text = speech_recognition_pipe(inputs, batch_size=8, return_timestamps=True)["text"]
return html_embed_str, text |