TODO.md

AI-Powered EQ Insights Integration TODO

Current Status

• Plan confirmed by user
• Create Insights Engine (app/ml/insights_generator.py)
• Enhance Results Screen (app/ui/results.py)
• Integrate with Existing ML (app/ml/predictor.py)
• Add User Feedback Loop
• Create Tests (tests/test_insights.py)
• Train ML model on historical scores data
• Test integration end-to-end
• Implement feedback storage and refinement logic

Implementation Details

1. Create Insights Engine (app/ml/insights_generator.py)

• Analyze user data for trends using scikit-learn
• Generate personalized improvement suggestions based on scores, strengths, and patterns
• Train a simple ML model (regression) to predict EQ improvement paths

2. Enhance Results Screen (app/ui/results.py)

• Add insights display section showing personalized recommendations
• Integrate with existing ML analysis
• Show next steps and actionable advice

3. Integrate with Existing ML (app/ml/predictor.py)

• Extend predictor to include insights generation
• Ensure consistency with current ML pipeline

4. Add User Feedback Loop

• Add feedback collection in results screen
• Store feedback to refine recommendations over time

5. Create Tests (tests/test_insights.py)

• Test insight accuracy and edge cases
• Validate ML model predictions