This is a class project for EECS 545: Machine Learning
In a conventional setting, individuals face the meticulous task of arranging and updating their calendars by hand. This can lead to complications: from overlooking the need to account for travel time between appointments, double-booking, or to the broader issue of effectively balancing diverse tasks. Individuals even hire assistants to do just this, schedule things onto their calendar. In today’s fast-paced modern one, figuring out schedules for activities can be quite an annoyance. The complexity of calendar management is further compounded by the challenge of assigning the right level of priority to tasks and strategically placing commitments to maximize efficiency. This assistant was created to smoothen this process by leveraging Large Language Models (LLMs), delivering a system that promises a seamless, intuitive scheduling experience while minimizing the errors that are intrinsic to traditional manual methods.
Think of this assistant as your personal secretary. Example prompts that you could ask:
- "Schedule a jog for when I'm free."
- "Clear my afternoon."
- "Move my meeting with Smith to Monday afternoon"
- "Schedule me a study time over the next week to prepare for my final exams."
- "Find time for me to read every week."
How this works:
How to use this assistant: Authenticate using Google OAuth and obtain the credential for your Google calendar, paste it into the methods.py file. Also paste your OpenAI API key. Then simply run the notebook to interact with the assistant!
Example interaction:
