Update app.py
Browse files
app.py
CHANGED
@@ -3,6 +3,7 @@ import os
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import tempfile
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import threading
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import base64
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from urllib.parse import urlparse
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import dash
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@@ -16,11 +17,19 @@ from pydub import AudioSegment
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import google.generativeai as genai
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from moviepy.editor import VideoFileClip
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# Initialize the Dash app
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app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
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# Retrieve the Google API key from Hugging Face Spaces
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GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
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genai.configure(api_key=GOOGLE_API_KEY)
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# Initialize Gemini model
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@@ -31,68 +40,95 @@ def is_valid_url(url):
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result = urlparse(url)
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return all([result.scheme, result.netloc])
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except ValueError:
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return False
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def download_media(url):
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stream
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if 'video' in content_type:
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suffix = '.mp4'
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elif 'audio' in content_type:
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suffix = '.mp3'
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else:
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def extract_audio(file_path):
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video
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def transcribe_audio(file_path):
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def process_media(contents, filename, url):
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content_type, content_string = contents.split(',')
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decoded = base64.b64decode(content_string)
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suffix = os.path.splitext(filename)[1]
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with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
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temp_file.write(decoded)
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temp_file_path = temp_file.name
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elif url:
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temp_file_path = download_media(url)
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else:
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raise ValueError("No input provided")
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try:
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if temp_file_path.lower().endswith(('.mp4', '.avi', '.mov', '.flv', '.wmv')):
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audio_file_path = extract_audio(temp_file_path)
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transcript = transcribe_audio(audio_file_path)
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os.unlink(audio_file_path)
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else:
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transcript = transcribe_audio(temp_file_path)
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finally:
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os.unlink(temp_file_path)
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app.layout = dbc.Container([
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html.H1("Audio/Video Transcription App", className="text-center my-4"),
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@@ -142,6 +178,7 @@ def update_transcription(n_clicks, contents, filename, url):
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try:
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return process_media(contents, filename, url)
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except Exception as e:
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return f"An error occurred: {str(e)}"
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thread = threading.Thread(target=transcribe)
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@@ -149,11 +186,13 @@ def update_transcription(n_clicks, contents, filename, url):
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thread.join(timeout=600) # 10 minutes timeout
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if thread.is_alive():
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return "Transcription timed out after 10 minutes", {'display': 'none'}
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transcript = getattr(thread, 'result', "Transcription failed")
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if transcript and not transcript.startswith("An error occurred"):
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return dbc.Card([
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dbc.CardBody([
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html.H5("Transcription Result"),
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@@ -161,6 +200,7 @@ def update_transcription(n_clicks, contents, filename, url):
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])
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]), {'display': 'block'}
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else:
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return transcript, {'display': 'none'}
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@app.callback(
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@@ -177,6 +217,6 @@ def download_transcript(n_clicks, transcription_output):
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return dict(content=transcript, filename="transcript.txt")
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if __name__ == '__main__':
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app.run(debug=True, host='0.0.0.0', port=7860)
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import tempfile
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import threading
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import base64
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import logging
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from urllib.parse import urlparse
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import dash
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import google.generativeai as genai
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from moviepy.editor import VideoFileClip
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# Set up logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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# Initialize the Dash app
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app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
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# Retrieve the Google API key from Hugging Face Spaces
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GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY")
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if not GOOGLE_API_KEY:
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logger.error("GOOGLE_API_KEY not found in environment variables")
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raise ValueError("GOOGLE_API_KEY not set")
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genai.configure(api_key=GOOGLE_API_KEY)
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# Initialize Gemini model
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result = urlparse(url)
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return all([result.scheme, result.netloc])
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except ValueError:
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logger.error(f"Invalid URL: {url}")
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return False
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def download_media(url):
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logger.info(f"Attempting to download media from URL: {url}")
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try:
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if "youtube.com" in url or "youtu.be" in url:
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yt = YouTube(url)
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stream = yt.streams.filter(progressive=True, file_extension='mp4').first()
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with tempfile.NamedTemporaryFile(delete=False, suffix=".mp4") as temp_file:
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stream.download(output_path=os.path.dirname(temp_file.name), filename=temp_file.name)
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logger.info(f"YouTube video downloaded: {temp_file.name}")
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return temp_file.name
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else:
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response = requests.get(url)
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content_type = response.headers.get('content-type', '')
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if 'video' in content_type:
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suffix = '.mp4'
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elif 'audio' in content_type:
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suffix = '.mp3'
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else:
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suffix = ''
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with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
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temp_file.write(response.content)
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logger.info(f"Media downloaded: {temp_file.name}")
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return temp_file.name
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except Exception as e:
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logger.error(f"Error downloading media: {str(e)}")
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raise
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def extract_audio(file_path):
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logger.info(f"Extracting audio from video: {file_path}")
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try:
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video = VideoFileClip(file_path)
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audio = video.audio
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audio_file = tempfile.NamedTemporaryFile(delete=False, suffix=".wav")
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audio.write_audiofile(audio_file.name)
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video.close()
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audio.close()
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logger.info(f"Audio extracted: {audio_file.name}")
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return audio_file.name
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except Exception as e:
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logger.error(f"Error extracting audio: {str(e)}")
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raise
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def transcribe_audio(file_path):
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logger.info(f"Transcribing audio: {file_path}")
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try:
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with open(file_path, "rb") as audio_file:
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audio_data = audio_file.read()
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response = model.generate_content(audio_data)
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logger.info("Transcription completed successfully")
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return response.text
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except Exception as e:
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logger.error(f"Error during transcription: {str(e)}")
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raise
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def process_media(contents, filename, url):
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logger.info("Starting media processing")
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try:
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if contents:
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content_type, content_string = contents.split(',')
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decoded = base64.b64decode(content_string)
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suffix = os.path.splitext(filename)[1]
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with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
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temp_file.write(decoded)
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temp_file_path = temp_file.name
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logger.info(f"File uploaded: {temp_file_path}")
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elif url:
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temp_file_path = download_media(url)
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else:
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logger.error("No input provided")
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raise ValueError("No input provided")
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if temp_file_path.lower().endswith(('.mp4', '.avi', '.mov', '.flv', '.wmv')):
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logger.info("Video file detected, extracting audio")
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audio_file_path = extract_audio(temp_file_path)
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transcript = transcribe_audio(audio_file_path)
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os.unlink(audio_file_path)
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else:
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logger.info("Audio file detected, transcribing directly")
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transcript = transcribe_audio(temp_file_path)
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os.unlink(temp_file_path)
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return transcript
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except Exception as e:
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logger.error(f"Error in process_media: {str(e)}")
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raise
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app.layout = dbc.Container([
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html.H1("Audio/Video Transcription App", className="text-center my-4"),
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try:
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return process_media(contents, filename, url)
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except Exception as e:
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logger.error(f"Transcription failed: {str(e)}")
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return f"An error occurred: {str(e)}"
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thread = threading.Thread(target=transcribe)
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thread.join(timeout=600) # 10 minutes timeout
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if thread.is_alive():
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logger.warning("Transcription timed out after 10 minutes")
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return "Transcription timed out after 10 minutes", {'display': 'none'}
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transcript = getattr(thread, 'result', "Transcription failed")
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if transcript and not transcript.startswith("An error occurred"):
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logger.info("Transcription successful")
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return dbc.Card([
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dbc.CardBody([
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html.H5("Transcription Result"),
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])
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]), {'display': 'block'}
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else:
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logger.error(f"Transcription failed: {transcript}")
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return transcript, {'display': 'none'}
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@app.callback(
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return dict(content=transcript, filename="transcript.txt")
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if __name__ == '__main__':
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logger.info("Starting the Dash application...")
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app.run(debug=True, host='0.0.0.0', port=7860)
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logger.info("Dash application has finished running.")
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