You can build an email monitoring application that uses Twilio SMS and semantic analysis with sentence transformers to analyze the importance of emails. The application will retrieve unread emails from your inbox, use semantic similarity to classify their importance, send SMS notifications about important emails, and provide detailed console output for monitoring. To start, you'll need a free Twilio account, Python 3.7 or later installed on your computer, basic knowledge of Python programming, an email account that supports IMAP access, and generate an app password for Gmail if using the service. The application will be implemented in a file named `email_monitor.py`, where you'll add the core functionality to retrieve emails, analyze their importance according to your set keywords, and send SMS notifications. You'll use environment variables to keep sensitive information secure, including email credentials and Twilio API keys. The application will also handle various character encodings in emails using the `safe_decode` function. Once implemented, you can test the application by sending sample emails to yourself and running the script with your credentials correctly set in the `.env` file. The application demonstrates how modern NLP techniques can be used to create powerful email monitoring solutions, showcasing how AI and cloud communications can create productivity tools.