A full-stack web application for a dental clinic featuring appointment booking, patient intake forms, an admin dashboard, security best practices, and an AI-powered chatbot.

🌐 Live Demo: https://web-production-2810e.up.railway.app/

🔑 Demo Admin Access (Read-Only):
Email: tieuthanhvitamin@gmail.com
Password: hello123

▶️ Click to watch the demo:
https://drive.google.com/file/d/1TGAeUSw1Qt9nOf6ZAxAgY29w3cIy988r/view?usp=sharing

This project is a full-stack healthcare web application built with Python (Flask), JavaScript, HTML, and CSS. It simulates a real-world dental clinic platform that allows patients to:

• 📅 Request an appointment
• 📄 Submit new patient intake forms with PDF generation
• 🤖 Ask questions via an AI-powered chatbot
• 🔐 Allow administrators to manage appointments and reviews

The project demonstrates end-to-end web development skills, including backend APIs, database design, frontend UI/UX, security considerations, and deployment workflows.

This project highlights:

• ✅ Real-world full-stack engineering (frontend, backend, database, deployment)
• ✅ Secure web application practices (CSRF protection, password hashing, rate limiting)
• ✅ Practical AI integration to improve user experience
• ✅ Workflow automation (PDF generation, email notifications)
• ✅ Production-ready deployment using industry-standard tools
• ✅ Clean code organization and maintainability

It was designed to mirror the requirements of modern service-based platforms in healthcare while emphasizing scalability, maintainability, and clean architecture.

• Responsive landing pages (Home, Services, Implants, Reviews)
• Appointment request form
• New patient intake form with automated PDF generation
• AI chatbot for clinic FAQs, services, and hours

• Secure admin authentication with rate limiting
• Appointment request management
• Review and image moderation
• Password reset and account management
• Audit-style logging for administrative actions

• CSRF protection on all forms
• Protected admin-only routes
• Password hashing using industry-standard libraries
• Safe database interactions to mitigate SQL injection risks

.
├── app.py                     # Main Flask application
├── auth.py                    # Authentication utilities
├── db.py                      # Database setup and logic
├── pdf_tools.py               # PDF generation utilities
├── email_utils.py             # Email sending utilities
├── clinic_info.json           # Clinic configuration data
├── requirements.txt           # Python dependencies
├── Procfile                   # Deployment configuration
├── .env.example               # Environment variable template
├── templates/                 # HTML templates
│   ├── base.html
│   ├── home.html
│   ├── services.html
│   ├── implants.html
│   ├── reviews.html
│   ├── contact.html
│   ├── new_patient.html
│   ├── admin_login.html
│   ├── admin_requests.html
│   ├── admin_reviews.html
│   ├── admin_password_reset.html
│   ├── admin_forgot_password.html
│   └── admin_change_password.html
├── static/                    # Static assets
│   ├── uploads/
│   │   ├── dentists/
│   │   ├── forms/
│   │   ├── images/
│   │   └── reviews/
│   ├── chat.js
│   ├── delete_requests.js
│   ├── image_slider.js
│   ├── new_patient.js
│   └── styles.css
├── filled_forms/              # Generated patient PDF forms
└── README.md

1. Clone the Repository

git clone https://github.com/gemmatruong/dental_web.git
cd dental_web

2. Create and Activate a Virtual Environment

python -m venv venv
source venv/bin/activate      # macOS/Linux
venv\Scripts\activate         # Windows

3. Install Dependencies

pip install -r requirements.txt

4. Environment Variables

• Copy .env.example to .env
• Add required credentials

FLASK_SECRET_KEY=your_secret_key
GROQ_API_KEY=gsk_...
MAIL_USERNAME=your_email@example.com
MAIL_PASSWORD=your_email_password

python db.py

flask run

This application is production-ready and deployable on Railway.

1. Create a new Railway project
2. Connect the GitHub repository
3. Configure required environment variables
4. Railway automatically builds and deploys the app on each push to main

• Unit and integration testing
• Role-based user authentication
• Improved AI chatbot context and conversational memory
• Docker containerization
• CI/CD pipeline integration

Contributions are welcome and appreciated.

To contribute:

1. Fork the repository
2. Create a new feature branch
3. Submit a pull request with a clear description of changes

Developer: Gemma Truong
GitHub: https://github.com/gemmatruong

LinkedIn: (https://www.linkedin.com/in/gemmatruong/)
Email: gemmatruong99@gmail.com

This project is proprietary (all rights reserved).
Please contact the author for permission regarding usage or distribution.