NFDI Search Engine

This repository is dedicated to enhancing the search functionality of the NFDI4BioImage training website by collecting and organizing training materials and related resources.

Overview

The project leverages several key technologies:

• Elasticsearch: For indexing and searching materials.
• React: As the frontend framework for building a user-friendly interface.
• Flask: Serving as the backend API to manage interactions with the database and Elasticsearch.
• Scroll API: Used to efficiently handle large datasets during search queries.

Quick Start with Docker

To simplify the setup process, the project is containerized with Docker. Follow these steps to get the search engine up and running on your local machine.

Prerequisites

1. GitHub API Key or Token: The search engine requires access to GitHub for submitting and managing materials. Ensure that you have set up the necessary GitHub API keys or tokens on your machine.

   • You can refer to this website for instructions on how to set up the API key or token.
   • This key/token should be securely stored and added to the necessary environment variables on your machine.

2. Docker and Docker Compose installed on your machine.

3. Currently, this project is only supported on Windows.

Setup Instructions

1. Clone the repository:

   git clone https://github.com/NFDI4BIOIMAGE/nfdi_search_engine.git

   cd nfdi_search_engine

2. Locate the docker-compose.yml file in the project directory.

3. Build and start the containers:

   docker-compose up --build

This command will pull all necessary images, build the project, and start the containers.

4. Important: After the initial setup, when you start the containers again by clicking the Start button in Docker Desktop, you will need to wait approximately 22 seconds for Elasticsearch to fully initialize before the search engine becomes accessible.

Accessing the Application

Once the Docker containers are running, you can access the application:

1. Search Engine Interface: Visit the website on http://localhost:3000 to use the search engine. You'll see a user-friendly interface where you can search and explore the available training materials. Here's a preview of how the search engine looks:

   

   

2. Submit Materials: The project also includes a material submission platform that makes it easy for users to contribute new training materials. Simply visit http://localhost:3000/submit-materials and follow the instructions to upload new content.

   

Features

• Search Engine: Find all the current training materials available on the NFDI4BioImage training website with easy-to-use search functionality.

• Material Submission: A streamlined process for collecting and managing training materials via the submission portal.

Contributing

If you'd like to contribute to the project, feel free to open an issue or submit a pull request.