ReadHabit

You can watch the ReadHabit demo video online by following below step:

1. Access this link: https://livepush.io/mp4-player/index.html
2. And paste this to the mp4 player: https://rawcdn.githack.com/huynhhuuloc129/ReadHabit-Web/fd782e1f5e4c08ad01c2d28a1aebe8663f7bda7d/demo_without_audio1.mp4

This template should help get you started developing with Vue 3 in Vite.

Recommended IDE Setup

VSCode + Volar (and disable Vetur) + TypeScript Vue Plugin (Volar).

Type Support for .vue Imports in TS

TypeScript cannot handle type information for .vue imports by default, so we replace the tsc CLI with vue-tsc for type checking. In editors, we need TypeScript Vue Plugin (Volar) to make the TypeScript language service aware of .vue types.

If the standalone TypeScript plugin doesn't feel fast enough to you, Volar has also implemented a Take Over Mode that is more performant. You can enable it by the following steps:

1. Disable the built-in TypeScript Extension
   1. Run Extensions: Show Built-in Extensions from VSCode's command palette
   2. Find TypeScript and JavaScript Language Features, right click and select Disable (Workspace)
2. Reload the VSCode window by running Developer: Reload Window from the command palette.

Customize configuration

See Vite Configuration Reference.

Project Setup

npm install

Compile and Hot-Reload for Development

npm run dev

Type-Check, Compile and Minify for Production

npm run build

Run Unit Tests with Vitest

npm run test:unit

Lint with ESLint

npm run lint

To run the article recommendation system, you need to follow these steps:

1. Install the library: Python

   pip install numpy scikit-learn nltk
   

   Be careful when using code snippets.

2. Save the Python code to a file: Save the above Python code to a file named recommend.py.

3. Run the Python file: Python

   python recommend.py
   

   Be careful when using code snippets.

4. Enter article data: Modify the article data in the recommend.py file. Add titles, content, labels, and categories for new articles.

5. Recommend articles: Enter the title and content of the new article you want to suggest. The system will display the top 5 articles with the highest similarity.