This project was developed as part of the CE903 Group Project at the University of Essex. The goal of the project was to create a Medical Chatbot, and the responsibilities were distributed among the team members. In this project, I was responsible for building both the frontend and the Flask API, which serves as the communication bridge between the frontend and the chatbot model.
Entity-Relationship Diagram (ERD)
Illustrating the database schema of the Medical Chatbot project.
Architecture Overview
Showing the interaction between the frontend, backend, and the model.
Application Interface
Demonstrating its user-friendly design and functionality.
- Clone the repository
- Install tensorflow:
pip install tensorflow - Run training.py to train the model
- Fire up the flask api with command:
python api.py
- Clone the repository from GitLab
- Install the required dependencies for the frontend using npm:
npm install - Setup the database using Prisma after configuring the .env file:
npx prisma migrate dev - Start the frontend development server:
npm run dev - Visit http://localhost:3000 in your web browser to access the application