AI Academic Rescue Agent Implementation #1
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- Create data models for StudentProfile, Subject, Topic, and Plan. - Implement core logic for prioritization, scheduling, and stress adaptation. - Implement Agent Controller to format output. - Create CLI for user interaction via JSON input. - Add unit tests and sample input.
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- Core Logic: Prioritization, scheduling, and stress adaptation algorithms in `src/logic.py`.
- Data Models: StudentProfile, Subject, Topic, Plan in `src/models.py`.
- Agent Controller: Output formatting and plan generation in `src/agent.py`.
- CLI: Command line interface in `src/cli.py`.
- Web Interface:
- `src/server.py`: Standard library HTTP server handling JSON API.
- `src/web/index.html`: Dynamic HTML frontend for user interaction.
- Tests: Unit tests in `tests/`.
- Documentation: Updated README.md.
Implemented the AI Academic Rescue Agent as a Python CLI application.
The system takes student exam data, confidence levels, and stress levels as input and generates a prioritized, adaptive study plan.
Key features include:
PR created automatically by Jules for task 13907338250850661115 started by @TyphoonCoder2007