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example workflow

📄 Description

This is an Edinburgh Napier University Honours Project for (BSc.) Computer Science Degree.

This Honours Project revolves around Conversational A.I. Agents to be used in the Educational System for the correct interaction with humans to pass across knowledge. However, due to the lack of existing real-world literature and research on multi-modal learning approaches, such as: visual - audio and interactive charts methods of learning, this honours project aims to understand the imapct of the use of a Conversational A.I. Agent to pass across knowledge to the user on a scientific topic and companre it with standard and more common methods of learning.

This repository is only half-of the project. It focuses on the development of the conversational AI agent and the outline of its development. The UI/UX in a web-app format can be accessed on the following link -> [insert-link-here] and for the open-source code for it can be found here -> [insert-link-here]

♨ Live Version

The live version of the website for the project can be accessed on the link:

live-version

🐳 Dockerized

This application has been developed as a Docker Application , so it can be just deployed wherever needed quickly.

📊 Project Graph

image

https://whimsical.com/honours-project-development-graph-E62ncTCRaqLE5rMWiwMjVw

🎨 Project Design

The project has been created and designed from scratch using Figma and can be accessed for live view on the link here.

[insert-project-chart-here]

🟢 Testing

This project has been developed using testing for the frontend project using the cypress library for the respective testing.

⚙ Developemnt

📚 Libraries in use

This project frontend makes use of the following libraries:

🚧 Developing

Once you've created a project and installed dependencies with npm install (or pnpm install or yarn), start a development server:

npm run dev
# or start the server and open the app in a new browser tab
npm run dev -- --open

🏗 Building

Before creating a production version of your app, install an adapter for your target environment. Then:

npm run build

You can preview the built app with npm run preview, regardless of whether you installed an adapter. This should not be used to serve your app in production.