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import yt_dlp
from faster_whisper import WhisperModel
from ollama import Client
import os
import browser_cookie3
import tempfile
def get_youtube_cookies():
"""
Attempt to get YouTube cookies from multiple browsers.
Returns a cookie file path or None if no cookies found.
"""
browsers = [
(browser_cookie3.chrome, 'chrome'),
(browser_cookie3.firefox, 'firefox'),
(browser_cookie3.edge, 'edge'),
(browser_cookie3.safari, 'safari')
]
# Create a temporary file for cookies
cookie_file = tempfile.NamedTemporaryFile(delete=False, suffix='.txt')
for browser_func, browser_name in browsers:
try:
cookies = browser_func(domain_name='.youtube.com')
with open(cookie_file.name, 'w') as f:
for cookie in cookies:
f.write(f'{cookie.domain}\tTRUE\t{cookie.path}\t'
f'{"TRUE" if cookie.secure else "FALSE"}\t{cookie.expires}\t'
f'{cookie.name}\t{cookie.value}\n')
return cookie_file.name
except:
continue
return None
def download_audio(url):
cookie_file = get_youtube_cookies()
ydl_opts = {
'format': 'bestaudio/best',
'postprocessors': [{
'key': 'FFmpegExtractAudio',
'preferredcodec': 'wav',
'preferredquality': '192',
}],
'outtmpl': 'audio.%(ext)s',
'quiet': True,
'no_warnings': True
}
# Add cookies if available
if cookie_file:
ydl_opts['cookiefile'] = cookie_file
try:
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
ydl.download([url])
# Clean up cookie file
if cookie_file and os.path.exists(cookie_file):
os.unlink(cookie_file)
return 'audio.wav'
except Exception as e:
if cookie_file and os.path.exists(cookie_file):
os.unlink(cookie_file)
raise Exception(f"Error downloading audio: {str(e)}")
def transcribe_audio(audio_file):
# Explicitly specify CPU device and compute type
model = WhisperModel("base", device="cpu", compute_type="int8")
segments, _ = model.transcribe(audio_file)
return " ".join([segment.text for segment in segments])
ollama_client = Client()
def generate_notes_and_summary_stream(transcript):
prompt = f"""
Based on the following transcript of a video, create:
1. A set of concise, informative notes
2. A brief summary of the main points
Transcript:
{transcript}
Notes and Summary:
"""
stream = ollama_client.generate(model='llama3.1:latest', prompt=prompt, stream=True)
for chunk in stream:
yield chunk['response']
def process_video(url):
try:
audio_file = download_audio(url)
transcript = transcribe_audio(audio_file)
return generate_notes_and_summary_stream(transcript)
except Exception as e:
raise Exception(f"An error occurred: {str(e)}") |