feat(date-parser): Implement robust date parsing with natural language support

[vansh2604-star]

Problem

Current date parsing in StudyPlan is fragile. It struggles with ambiguous formats (e.g., 03/04/2026), natural language phrases (end of next week, first Monday of next month), and invalid inputs. This leads to incorrect deadlines, failed calendar exports, and inconsistent user experiences.

Proposed Improvement

Introduce a centralized robust date parser utility that:

Normalizes ambiguous formats with a clear interpretation strategy.

Supports natural language expressions using libraries like chrono-node or custom logic.

Validates all parsed dates before saving to the database.

Provides fallback behavior (e.g., prompt user confirmation) when parsing fails.

Includes unit tests covering edge cases and invalid inputs.

Why improvement is needed

Prevents scheduling errors and misinterpreted deadlines.

Improves reliability of AI fallback when external APIs fail.

Enhances user trust in StudyPlan’s calendar and reminder features.

Future-proofs the system for additional date-related features.

Expected Result

Consistent and accurate date parsing across all modules.

Clear error handling for unsupported or invalid inputs.

Seamless integration with calendar export and task scheduling.

Higher test coverage ensuring long-term stability.

Alternatives Considered

Continue using regex-based parsing (too brittle and error-prone).

Rely solely on external AI parsing (not reliable when API fails).

Manually prompt users for corrections (adds friction, not scalable).

Additional Context

This PR builds on the recent fix excluding invalid dates during ICS export but goes further by addressing robustness and natural language support. It complements issue #1173, which highlights the need for improved NLP fallback parsing.

[vansh2604-star]

/assign ,

this issue to me, i would like to work on this issue

[PadmakarBagade]

Hi @Charushi06,

I'd like to work on this issue.

I reviewed the problem statement and agree that date parsing should be handled through a centralized, robust solution rather than scattered regex-based logic. My implementation will focus on improving reliability, maintainability, and consistency across the StudyPlan module.

Planned implementation

• Create a centralized date parsing utility that can be reused throughout the application.

• Support common date formats while defining a clear strategy for handling ambiguous formats (e.g. 03/04/2026).

• Add support for natural language expressions such as:

  • today
  • tomorrow
  • next Monday
  • end of next week
  • first Monday of next month

• Validate parsed dates before they are stored or used in scheduling workflows.

• Provide graceful error handling and fallback behavior when parsing fails or input is ambiguous.

• Ensure compatibility with calendar export and task scheduling to prevent invalid dates from propagating through the system.

• Add comprehensive unit tests covering:

  • valid date formats
  • ambiguous inputs
  • natural language expressions
  • invalid inputs
  • regression cases related to calendar export

I'll first analyze the existing StudyPlan date flow and the recent ICS export fix to ensure this enhancement integrates cleanly without introducing regressions.

I'll keep the implementation modular, well-tested, and aligned with the project's coding standards.

If this approach looks good, I'd be happy to work on it. Thank you!

[aaniya22]

pls assign this to me under gssoc