How dxn-xnt/entervene works
Entervene is an AI-enhanced learning management system for managing academic work and student risk. The main workflow is that staff record learning activity and assessment evidence; the system uses academic records to surface risk and explanations; teachers review cases and can coordinate interventions, including student-facing reviewers and notifications. The repository also supports class and curriculum administration, quizzes, attendance, analytics, and student records. The graph follows the documented backend route/service structure and the available tree; most route-to-service wiring and frontend request details were not sampled, so uncertain links are omitted.
Main entry points: main.py API application · Session.py Application data · Predictions.py Risk predictions · academic Academic records
Components 29
Learning workflows
- Classwork and submissions
backend/app/api/v1/routes/Classworks.py - Submission handling
backend/app/services/submission/SubmissionService.py - Lessons and plans
backend/app/api/v1/routes/Lessons.py - Quizzes
backend/app/api/v1/routes/Quizzes.py - Attendance
backend/app/api/v1/routes/Attendance.py - Student records
backend/app/services/student_record/StudentRecordService.py - Analytics
backend/app/api/v1/routes/Analytics.py
Risk and support
- Risk predictions
backend/app/api/v1/routes/Predictions.py - Feature building
backend/app/services/prediction/PredictionFeatureBuilderService.py - Risk evaluation
backend/app/services/prediction/RiskEngine.py - Teacher risk review
backend/app/services/prediction/TeacherRiskReviewService.py - Interventions
backend/app/services/intervention/TeacherInterventionService.py - Reviewer generation
backend/app/services/intervention/InterventionReviewerGenerationService.py - Reviewer delivery
backend/app/services/intervention/InterventionReviewerDeliveryService.py - Notifications
backend/app/services/NotificationService.py - AI provider
backend/app/services/ai/Provider.py - Prediction records
backend/app/models/ai
Application platform
- Web application
frontend/src/App.tsx - API client
frontend/src/lib/api.ts - API application
backend/app/main.py - Authentication
backend/app/api/v1/routes/Auth.py - Application data
backend/app/db/Session.py
Academic operations
- Classes
backend/app/api/v1/routes/Classes.py - Subjects and offerings
backend/app/api/v1/routes/SubjectOfferings.py - Grading templates
backend/app/api/v1/routes/GradingTemplates.py - Pathways
backend/app/api/v1/routes/Pathways.py - Academic records
backend/app/models/academic
Other components
- Staff
- Students
Connections 34
- Staff → Web application: uses
- Students → Web application: uses
- Web application → API client: requests data
- API client → API application: sends requests
- API application → Authentication: routes authentication
- Authentication → Application data: reads and writes
- API application → Classwork and submissions: routes requests
- Classwork and submissions → Submission handling: handles submissions
- API application → Lessons and plans: routes requests
- API application → Quizzes: routes requests
- API application → Attendance: routes requests
- API application → Student records: routes requests
- API application → Analytics: routes requests
- API application → Risk predictions: routes requests
- Risk predictions → Feature building: builds features
- Risk predictions → Risk evaluation: evaluates risk
- Risk predictions → Prediction records: reads and writes
- Teacher risk review → Prediction records: records decisions
- API application → Interventions: routes requests
- Reviewer generation → AI provider: generates content
- Reviewer delivery → Notifications: stages notification
- Reviewer delivery → Students: delivers reviewer
- API application → Classes: routes requests
- API application → Subjects and offerings: routes requests
- API application → Grading templates: routes requests
- API application → Pathways: routes requests
- Classes → Academic records: reads academic data
- Subjects and offerings → Academic records: reads academic data
- Grading templates → Academic records: reads grading data
- Pathways → Academic records: reads pathway data
- Submission handling → Application data: persists submissions
- Student records → Application data: reads and writes
- Feature building → Application data: reads evidence
- Risk evaluation → Application data: reads thresholds