GongGang AI Planner

This project generates a personalized study plan using your university timetable. You can fetch schedules from Everytime or upload XML files, analyze free periods, and use a neural network model to suggest weekly study priorities. A web interface lets you visualize and adjust the plan.

Features

• Timetable import: everytime.py fetches an XML timetable from an Everytime share URL or loads a local file.
• Timetable → Calendar: every2cal.py lists free time slots and exports an .ics calendar.
• Study plan generation: models/study_plan_nn.py assigns priorities based on subject importance, major relevance, and free time.
• Web interface: app.py is a Flask server to input timetable data, view schedules, and retrain the model if needed.

Getting Started

1. Install Python 3.8+ and required packages:

   pip install flask torch requests icalendar python-dateutil

2. Launch the web server:

   python app.py

3. Visit http://localhost:5001 in your browser to load a timetable and generate a study plan.

Convert a timetable directly to an .ics file:

python every2cal.py --id <EVERYTIME_ID> --begin 2024-03-02 --end 2024-06-20

Directory Overview

• app.py – Flask application entry point
• every2cal.py – Converts timetable XML to .ics
• convert.py – Parses XML and performs iCalendar conversion
• models/ – Neural network (study_plan_nn.py) and saved model files
• templates/, static/ – Web page templates and static resources
• subject_datas/ – User-provided subject data storage