Implement End-to-End Test for Core Functionality

[ballPointPenguin]

Objective

Implement a complete end-to-end test that demonstrates the core functionality of the system, from generating a professor and course to creating a lecture and converting it to audio.

Tasks

• Create a test script that exercises all main components
• Implement proper error handling and validation
• Add commandline arguments for customization
• Test with different professor personas and course types
• Document the test process
• Add sample output files to gitignore

Success Criteria

• Script runs successfully end-to-end without errors
• Test generates a professor with a consistent personality
• Test creates a course with a coherent syllabus
• Test generates a lecture that maintains the professor's voice
• Test converts the lecture to audio with appropriate voice
• All generated content is stored correctly in the database
• Audio file is saved to the correct location

Implementation Notes

• Use a specific test API key with usage limits
• Add a dry-run mode that skips actual API calls
• Implement proper cleanup to avoid test data accumulation
• Add timing and token usage metrics

Related Files

• artificial_u/system.py
• artificial_u/generators/content.py
• artificial_u/audio/processor.py
• artificial_u/models/database.py