AI-driven app with smart navigation, interactive chatbot, insightful videos, and personalized assessments.
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The Learning App is designed to provide a personalized educational experience. Users can input links to resources they want to learn from, and the LLM will update its knowledge base accordingly. The app offers various features, including reading generated pages, learning through video lectures, taking tests, and chatting with the AI.
We acknowledge the Watsonx.ai LLMs offered to us by IBM in the hackthon organised by Lablab.ai in collaboration with IBM.
So as to run our project locally, you need to follow the steps below.
Use linux distro like ubuntu, as repo has .sh scripts for automation.
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Clone the repository:
https://github.com/Sar2580P/TheWatsonCrew.git cd TheWatsonCrew
Create .env file similar to .env.example
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Install dependencies for the frontend (Next.js):
make setup make setupweb
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Install dependencies for the frontend (Next.js):
cd web npm install
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Run the development servers:
- For Next.js (frontend):
cd web npm run build npm start
- (Backend):
cd .. bash activate.sh cd api python manage.py runserver
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Open your browser and navigate to
http://localhost:3000
for the frontend andhttp://127.0.0.1:8000/api
for the backend admin interface.
The Learning App is designed to provide a personalized educational experience. Users can input links to resources they want to learn from, and the LLM will update its knowledge base accordingly. The app offers various features, including reading generated pages, learning through video lectures, taking tests, and chatting with the AI.
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b feature/AmazingFeature
) - Commit your Changes (
git commit -m 'Add some AmazingFeature'
) - Push to the Branch (
git push origin feature/AmazingFeature
) - Open a Pull Request
Use this space to list resources you find helpful and would like to give credit to. I've included a few of my favorites to kick things off!
A special thank you to all the current contributors who have made this project possible. You can view the contributors