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Frontend for SensAI - an AI-first LMS to help teachers provide personalised support to every learner

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SensAI frontend

SensAI is an AI-first Learning Management System (LMS) which enables educators to help them teacher smarter and reach further. SensAI coaches your students through questions that develop deeper thinking—just like you would, but for every student and all the time. This repository is the frontend for SensAI. The backend repository can be found here.

coverage report

If you are using SensAI and have any feedback for us or want any help with using SensAI, please consider joining our community of AI + Education builders and reaching out to us.

If you want to contribute to SensAI, please look at the Contributing section here.

Our public roadmap is live here. Go check it out and let us know what you think we should build next!

Contributing

To learn more about making a contribution to SensAI, please see our Contributing guide.

Installation

  • Make sure the backend is set up properly. Refer to the backend installation guide for more information.
  • Ensure you have Node.js installed on your machine.
  • Clone the repository:
    git clone https://github.com/dalmia/sensai-frontend.git
    cd sensai-frontend
    
  • Copy .env.example to .env.local and set the environment variables. We use Judge0 for code execution. You will need to add the Judge0 API key to the .env.local file. Either self-host it or use the publicly available Judge0 instance. Please refer to the Judge0 installation guide for more information. Set up your Google OAuth account and enter those credentials in the .env.local file.
  • Install dependencies:
    npm ci
    
  • Run the development server:
    npm run dev
    

The app will be available at http://localhost:3000.

Testing

SensAI uses Jest and React Testing Library for testing. The test suite includes unit tests and component tests to ensure code quality and prevent regressions. Codecov is used to track the coverage of the tests.

  • Run all tests (and generate a coverage report):

    npm run test:ci
    
  • (optional) Upload the coverage report to Codecov:

    curl -Os https://cli.codecov.io/v10.4.0/macos/codecov
    chmod +x codecov
    ./codecov upload-process -f coverage/lcov.info
    

Community

We are building a community of creators, builders, teachers, learners, parents, entrepreneurs, non-profits and volunteers who are excited about the future of AI and education. If you identify as one and want to be part of it, consider joining our community.

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Frontend for SensAI - an AI-first LMS to help teachers provide personalised support to every learner

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