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Update app.py
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import base64
import io
import os
import threading
import tempfile
import logging
import openai
from dash import Dash, dcc, html, Input, Output, State, callback
import dash_bootstrap_components as dbc
from pydub import AudioSegment
import requests
from pytube import YouTube
import subprocess
import sys
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# Function to install a package using pip
def install_package(package):
logger.info(f"Attempting to install {package}")
try:
subprocess.check_call([sys.executable, "-m", "pip", "install", package])
logger.info(f"Successfully installed {package}")
return True
except subprocess.CalledProcessError as e:
logger.error(f"Failed to install {package}. Error: {str(e)}")
return False
# Try to import moviepy, install if not found
try:
import moviepy.editor as mp
logger.info("Moviepy successfully imported")
except ImportError:
logger.warning("Moviepy not found. Attempting to install...")
if install_package("moviepy"):
try:
import moviepy.editor as mp
logger.info("Moviepy successfully imported after installation")
except ImportError as e:
logger.error(f"Failed to import moviepy after installation. Error: {str(e)}")
raise
else:
logger.error("Failed to install moviepy. Please install it manually.")
raise ImportError("Could not import or install moviepy")
# Initialize moviepy
try:
mp.config.change_settings({"FFMPEG_BINARY": "ffmpeg"})
logger.info("Moviepy successfully initialized")
except Exception as e:
logger.error(f"Failed to initialize moviepy. Error: {str(e)}")
raise
# Initialize the Dash app
app = Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
# Global variables
generated_file = None
transcription_text = ""
# Set up OpenAI API key
openai.api_key = os.getenv("OPENAI_API_KEY")
# Layout
app.layout = dbc.Container([
html.H1("Audio/Video Transcription and Diarization App", className="text-center my-4"),
dbc.Card([
dbc.CardBody([
dcc.Upload(
id='upload-media',
children=html.Div([
'Drag and Drop or ',
html.A('Select Audio/Video File')
]),
style={
'width': '100%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
},
multiple=False
),
html.Div(id='output-media-upload'),
dbc.Input(id="url-input", type="text", placeholder="Enter audio/video URL (including YouTube)", className="mb-3"),
dbc.Button("Process URL", id="process-url-button", color="primary", className="mb-3"),
dbc.Spinner(html.Div(id='transcription-status'), color="primary", type="grow"),
html.H4("Diarized Transcription Preview", className="mt-4"),
html.Div(id='transcription-preview', style={'whiteSpace': 'pre-wrap'}),
html.Br(),
dbc.Button("Download Transcription", id="btn-download", color="primary", className="mt-3", disabled=True),
dcc.Download(id="download-transcription")
])
])
], fluid=True)
def process_media(file_path, is_url=False):
global generated_file, transcription_text
temp_audio_file = None
try:
if is_url:
if 'youtube.com' in file_path or 'youtu.be' in file_path:
yt = YouTube(file_path)
stream = yt.streams.filter(only_audio=True).first()
temp_audio_file = tempfile.NamedTemporaryFile(delete=False, suffix='.mp4')
stream.download(output_path=os.path.dirname(temp_audio_file.name), filename=os.path.basename(temp_audio_file.name))
else:
response = requests.get(file_path)
temp_audio_file = tempfile.NamedTemporaryFile(delete=False)
temp_audio_file.write(response.content)
temp_audio_file.close()
else:
temp_audio_file = tempfile.NamedTemporaryFile(delete=False)
temp_audio_file.write(file_path)
temp_audio_file.close()
file_extension = os.path.splitext(temp_audio_file.name)[1].lower()
if file_extension in ['.mp4', '.avi', '.mov', '.flv', '.wmv']:
video = mp.VideoFileClip(temp_audio_file.name)
audio = video.audio
wav_path = temp_audio_file.name + ".wav"
audio.write_audiofile(wav_path)
video.close()
elif file_extension in ['.wav', '.mp3', '.ogg', '.flac']:
audio = AudioSegment.from_file(temp_audio_file.name)
wav_path = temp_audio_file.name + ".wav"
audio.export(wav_path, format="wav")
else:
return "Unsupported file format. Please upload an audio or video file.", False
with open(wav_path, "rb") as audio_file:
transcript = openai.Audio.transcribe("whisper-1", audio_file)
audio_file.seek(0)
diarized_transcript = openai.Audio.transcribe("whisper-1", audio_file, response_format="verbose_json")
formatted_transcript = ""
if 'segments' in diarized_transcript:
for segment in diarized_transcript["segments"]:
speaker = segment.get('speaker', 'Unknown')
text = segment.get('text', '')
formatted_transcript += f"Speaker {speaker}: {text}\n\n"
else:
formatted_transcript = transcript.get('text', 'No transcription available.')
transcription_text = formatted_transcript
generated_file = io.BytesIO(transcription_text.encode())
return "Transcription and diarization completed successfully!", True
except Exception as e:
logger.error(f"Error during processing: {str(e)}")
return f"An error occurred: {str(e)}", False
finally:
if temp_audio_file and os.path.exists(temp_audio_file.name):
os.unlink(temp_audio_file.name)
if 'wav_path' in locals() and os.path.exists(wav_path):
os.unlink(wav_path)
@app.callback(
[Output('output-media-upload', 'children'),
Output('transcription-status', 'children'),
Output('transcription-preview', 'children'),
Output('btn-download', 'disabled')],
[Input('upload-media', 'contents'),
Input('process-url-button', 'n_clicks')],
[State('upload-media', 'filename'),
State('url-input', 'value')]
)
def update_output(contents, n_clicks, filename, url):
ctx = callback_context
if not ctx.triggered:
return "No file uploaded or URL processed.", "", "", True
trigger_id = ctx.triggered[0]['prop_id'].split('.')[0]
if trigger_id == 'upload-media' and contents is not None:
content_type, content_string = contents.split(',')
decoded = base64.b64decode(content_string)
status_message, success = process_media(decoded)
elif trigger_id == 'process-url-button' and url:
status_message, success = process_media(url, is_url=True)
else:
return "No file uploaded or URL processed.", "", "", True
if success:
preview = transcription_text[:1000] + "..." if len(transcription_text) > 1000 else transcription_text
return f"File processed successfully.", status_message, preview, False
else:
return "Processing failed.", status_message, "", True
@app.callback(
Output("download-transcription", "data"),
Input("btn-download", "n_clicks"),
prevent_initial_call=True,
)
def download_transcription(n_clicks):
if n_clicks is None:
return None
return dcc.send_bytes(generated_file.getvalue(), "diarized_transcription.txt")
if __name__ == '__main__':
print("Starting the Dash application...")
app.run(debug=True, host='0.0.0.0', port=7860)
print("Dash application has finished running.")