Koala UI

Koala UI is a modern, user-friendly web application designed to explore and visualize entity linking results efficiently. It features a clean interface, easy navigation, and powerful data handling capabilities.

Description

Koala UI is built with React and Material-UI, offering a seamless experience for users to manage and visualize datasets related to entity linking results. The application includes functionalities such as login authentication, dataset listing, table viewing, and detailed data visualization.

Features

• User Authentication
• Dataset Listing
• Table Data Viewing
• Pagination
• Data Visualization
• Responsive Design
• Easy Navigation

Installation

To get started with Koala UI using Docker, follow these steps:

1. Clone the repository

   git clone https://github.com/roby-avo/koala_ui

2. Navigate to the project directory

   cd koala-ui

3. Copy the .env template to .env

   cp .env.template .env

4. Fill out the required environment variables in the .env file.

   Example:

   # Frontend environment variables
   REACT_APP_BACKEND_URL=http://localhost:5001
   REACT_APP_ALLIGATOR_URL=
   REACT_APP_ALLIGATOR_TOKEN=
   REACT_APP_LAMAPI_URL=
   REACT_APP_LAMAPI_TOKEN=
   
   # Common environment variables
   NODE_ENV=development
   FLASK_ENV=development
   
   # Versions
   NODE_VERSION=22
   PYTHON_VERSION=3.12
   MONGO_VERSION=7.0
   
   # Ports
   FRONTEND_PORT=3000
   BACKEND_PORT=5001
   MONGO_PORT=27017

   Note: Fill in REACT_APP_ALLIGATOR_URL, REACT_APP_ALLIGATOR_TOKEN, REACT_APP_LAMAPI_URL, and REACT_APP_LAMAPI_TOKEN based on where your instances of Alligator and LamAPI are running.

5. Build and start the containers

   docker-compose up --build

6. Access the application Open your browser and go to http://localhost:3000.

Prerequisites

Ensure you have active instances of Alligator and LamAPI running. You can find more information and instructions on setting up these services in their respective repositories:

• Alligator
• LamAPI

Usage

Once the server is running, you can access the application at http://localhost:3000.

• Login: Use your credentials to log in.
• Dataset Management: View and manage your datasets.
• Table Viewing: Explore detailed data within tables.
• Data Visualization: Visualize data trends and insights.

Screenshots

Contributing

Contributions are welcome! Please fork the repository and create a pull request with your changes. Make sure to follow the contribution guidelines.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

For any questions or suggestions, please contact us at roberto.avogadro@sintef.no.