Online learning has taken the front seat in the post pandemic age. With the advent of sophisticated AI architectures like the Transformers, it is but natural that AI would find its way into education. Learning online via YouTube or MOOC platforms is often done as a method of self learning. The biggest obstacle faced by a student in self learning is the lack of attention span. An online tool that can generate short quizzes on input educational content can be of great use to teachers and students alike as it can help retain important information, frame questions and quickly revise large chunks of content.
EduAid is one such project which is currently available in the form of a browser extension.
Currently, the extension is not deployed, so it can only run locally. To run the extension locally, clone the github repo using:
git clone https://github.com/AOSSIE-Org/EduAid.git
Now move to the backend directory and make a new directory that will store the models.
cd backend && mkdir models && cd models && mkdir modelA && mkdir modelB
Download the model files from 🤗 Hub: model A model B and place them in the respective folders.
Finally, the models should look like this:
+---models
ª +---modelA
ª ª config.json
ª ª generation_config.json
ª ª pytorch_model.bin
ª ª
ª +---modelB
ª config.json
ª generation_config.json
ª pytorch_model.bin
Now run the script server.py
cd .. && python3 server.py
Now go the extensions page of your browser and load the directory EduAid/extension and you're ready to roll!
To load an unpacked directory as an extension in a browser, you might have to turn on Developer mode on your browser.
Note: This extension was tested on Google Chrome and Brave. The instructions on how to run it on Chrome can be found here. For Brave, the steps are the same with minor differences.
After opening the extension and clicking on the 'Fire up!' button, we currently have support for two methods of accepting input:
- Typing out the text or by pasting from the clipboard
- By uploading a PDF
Then after clicking the next button, the questions are generated, which can either be viewed in the extension popup itself or can be downloaded as a .txt file.
Note: If your machine has GPU, the inference time should be faster. On CPU, it can take from a few seconds to a few minutes for inference. On an AMD RYZEN 5 8GB CPU with 6 cores, the inference time is usually 45-70 seconds. The inference time may differ depending on the specifications of your machine.
This is the first year of the project. While some may have their own ideas on how to contribute, for the newcomers to the repository, you may follow the following steps:
-
First get to know the organization and the project by visiting the Official Website
-
Visit the Discord Channel for interacting with the community!