Nayak-indie/Timable

AI Summary: This issue describes a bug in `app.py` where improperly structured CSS is causing styling conflicts. These conflicts interfere with Python data handling logic, leading to inconsistent output and affecting the tool's functionality. Resolving this will restore expected behavior and provide a better foundation for future UI/UX improvements.

AI Summary: This issue proposes improvements to the project's documentation. Specifically, it aims to enhance the CONTRIBUTING.md file with proper contribution guides and simplify the README.md by removing technical examples, moving them to CONTRIBUTING.md instead.

AI Summary: This issue requests improvements to the project's documentation, which is described as short, incomplete, and lacking in style. The contributor is encouraged to suggest and implement changes that would make the documentation more appealing, potentially using TypeScript or other compatible markup languages.

AI Summary: This issue describes a bug in `app.py` where improperly structured CSS is causing conflicts with Python data handling logic, leading to inconsistent output. Fixing these styling issues will restore the tool's intended functionality and provide a better foundation for future UI/UX improvements.

AI Summary: This issue describes a critical problem where the application fails to run locally due to several runtime errors, including missing dependencies, import issues, and uninitialized state. These errors prevent new contributors from even starting the project, hindering debugging and general development. Fixing these foundational issues is crucial for improving contributor onboarding and overall project stability.

AI Summary: This issue proposes refactoring the existing solver to make its constraint system more modular and extensible. The goal is to separate different types of constraints, introduce a registration system for them, and allow dynamic enabling/disabling, ultimately improving code readability, maintainability, and scalability for larger datasets.

AI Summary: This issue proposes exploring and implementing AI-based features to enhance scheduling quality and automation. Potential features include balancing subject difficulty, predictive conflict detection, automatic priority recommendations, and natural language timetable configuration. The goal is to make the system more adaptive and intelligent.

AI Summary: This issue proposes several enhancements to the user interface and user experience of a timetable creation tool. The goals include improving layout, adding progress indicators, validation messages, better grid styling, search/filter functionality, dark mode, rotation preview, and confirmation dialogs for destructive actions.

AI Summary: This issue proposes refactoring the solver to use modular constraint components, separating hard and soft constraints, and introducing a registration system. The goal is to improve code readability, maintainability, and allow for easier addition of new constraint types without altering core logic.