Youtube-Whisper / app.py
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import whisper
import gradio as gr
import os
import warnings
warnings.filterwarnings("ignore", category=FutureWarning, module="torch")
from download_video import download_mp3_selenium
# Function to download the audio, title, and thumbnail from YouTube
def download_video_info(url):
try:
# Call the function to download video and get title, thumbnail, and logs
title, thumbnail_url, logs_output = download_mp3_selenium(url)
audio_file = "downloaded_video.mp4" # Path to the downloaded audio (MP4)
return audio_file, title, thumbnail_url, logs_output
except Exception as e:
return None, None, None, str(e)
# Function to transcribe the downloaded audio using Whisper
def transcribe_audio(audio_path, model_size="base"):
model = whisper.load_model(model_size)
result = model.transcribe(audio_path)
return result['text']
# Split logic: First fetch title, thumbnail, and logs, then transcribe
def get_video_info_and_transcribe(youtube_url, model_size="base"):
# Fetch title, thumbnail, and logs first
audio_path, title, thumbnail_url, logs_output = download_video_info(youtube_url)
# If fetching video info fails
if not audio_path or not os.path.exists(audio_path):
return gr.update(value=f"Error fetching video: {thumbnail_url}"), None, None, gr.update(value=logs_output)
# Show title and thumbnail to the user while the transcription is happening
title_output = gr.update(value=title)
# Show the thumbnail if available
if thumbnail_url:
thumbnail_output = gr.update(value=thumbnail_url)
else:
thumbnail_output = gr.update(visible=False) # Hide if no thumbnail
# Start transcription
transcription = transcribe_audio(audio_path, model_size)
return title_output, thumbnail_output, gr.update(value=transcription), gr.update(value=logs_output)
# Gradio interface setup using gradio.components
with gr.Blocks() as interface:
with gr.Row():
youtube_url = gr.Textbox(label="YouTube Link", elem_id="yt_link", scale=5)
model_size = gr.Dropdown(choices=["tiny", "base", "small", "medium", "large"], label="Model Size", value="base", scale=1)
title_output = gr.Textbox(label="Video Title", interactive=False)
with gr.Row():
thumbnail_output = gr.Image(label="Thumbnail", interactive=False, scale=1)
transcription_output = gr.Textbox(label="Transcription", interactive=False, scale=1)
logs_output = gr.Textbox(label="ChromeDriver Logs", interactive=False)
transcribe_button = gr.Button("Transcribe")
transcribe_button.click(
get_video_info_and_transcribe,
inputs=[youtube_url, model_size],
outputs=[title_output, thumbnail_output, transcription_output, logs_output]
)
# Launch the app
if __name__ == "__main__":
interface.launch(server_name="0.0.0.0", server_port=7860)