Taurite Tū

A web app for running Taurite Tū, a strength and balance programme for kaumātua (older adults). Staff use it to manage branches (kapa), participants, classes and attendance, record physical assessments, and produce reports for ACC, with optional AI-written summaries.

Built by COSC345 Group 4, University of Otago. Group 4:

• Ritvik Sharma
• Jack Dunlop
• Romero Suggate
• Danny Madison
• Gunit Chawla

Features

• Participants: enrolment at the authorised branch, separate Details and Attendance history pages, consent, documents, deactivation and reactivation.
• Sessions and attendance: all staff roles create sessions; Super Admins choose a branch and can filter national calendar/list views. Super Admins can mark, review, finalise and reopen attendance nationally; branch managers and instructors do the same within their own branch.
• Physical assessments: chair stand, timed up-and-go and balance tests, with baseline/latest comparisons, history and trend charts.
• Reporting: attendance and physical-testing statistics by branch and quarter, AI explanations, and ACC report drafts.
• Feedback: quotes and short stories linked to a participant or session, with recorded speaker type and reporting consent.
• Staff accounts: role and branch management, deactivation and reactivation with an audit trail.
• Documents: shared organisation, branch and participant files.
• Help: role-specific help articles and a help chatbot that answers from them.
• Audit log: a record of who changed what.

Three roles use the app: kaimahi (instructors), branch managers and super admins. Each one sees only what their role allows. Super Admins work nationally; branch managers and instructors are restricted to their own branch. See the permission summary.

Tech stack

Part	Technology
Frontend	Vue 3, Vue Router, Vite, Axios
Backend	Django 5.2, Django REST Framework
Background jobs	Celery, with Redis as the broker
Cache	Redis
Database	SQLite
AI	University vLLM server through the OpenAI client

Getting started

docs/quickstart walks through the whole setup, from installing the prerequisites to signing in. In short:

# 1. Configuration: copy the template, then fill in SECRET_KEY and the LLM values
cp backend/.env_skeleton .env

# 2. Python environment and backend dependencies
python -m venv .venv
source .venv/bin/activate          # Windows PowerShell: .\.venv\Scripts\Activate.ps1
python -m pip install -r backend/requirements.txt

# 3. Frontend dependencies
npm ci --prefix frontend

# 4. Redis
docker run --name taurite-redis -p 127.0.0.1:6379:6379 -d redis:7-alpine

# 5. Database and demo data
cd backend
python manage.py migrate
python manage.py seed_test_data    # needs ALLOW_DEMO_SEEDING=True in .env

Then start everything. On Linux, ./scripts/dev.sh runs it all in one terminal. On Windows or macOS, open three terminals:

# from backend/: Django
python manage.py runserver

# from backend/: Celery worker (Windows: use --pool=solo in place of --concurrency=1)
celery -A config worker --loglevel=info --concurrency=1

# from frontend/: Vite dev server
npm run dev

Open http://localhost:5173 and sign in as [email protected] with the password TestPass123!.

The Help articles are available immediately. To update the help assistant’s knowledge after editing them, run python manage.py build_help_index from backend/ with the configured LLM service reachable; see Help chatbot setup.

Testing

# from backend/
python manage.py test

# from frontend/
node --test tests/*.test.js

Project structure

Group_4/
├── backend/        Django project (config/) and apps: users, participants, sessions,
│                   physical_tests, reporting, documents, help, llm, audit
├── frontend/       Vue app (src/views, src/components, src/apis.js)
├── docs/           Developer documentation
├── scripts/        dev.sh, the Linux development launcher
└── .env            Local configuration (not committed; copy backend/.env_skeleton)

Documentation

Folder	What's in it
quickstart	Full setup guide
setup	Python environment, Celery, demo data, help chatbot
overview	System overview and te reo Māori terms used in the app
features	How each feature behaves
backend	Audit log, document storage, LLM integration
frontend	Frontend coding conventions
bug-scans	Past code review findings
devops	DevOps information - deployment & CI/CD workflow