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TutorAI is a RAG system capable of assisting with learning academic subjects and using the curriculum and citing it. The project revolves around building an application that ingests a textbook in most formats and facilitates efficient learning of the course material.

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TutorAI

GitHub Workflow Status (with event) GitHub top language GitHub language count License: MIT Project Version

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📋 Table of contents

Introduction

TutorAI is an interactive language agent designed to assist with learning academic subjects. It facilitates efficient learning by allowing users to upload textbooks in various formats and interact with the course material.

Features

TutorAI offers a comprehensive set of features to enhance the learning experience:

  • Document upload: Upload course material in various formats to enable TutorAI to process and interact with the content. Supported formats include PDF, DOC, DOCX, PNG, JPG, JPEG, PPM, TIFF, BMP, and more.
  • Information search: Retrieve relevant citations and incorporate them into responses to user questions. This ensures comprehensive, accurate, and well-cited information, enhancing the learning process.
  • Learning plans: Tailored to the user's pace, style, and goals, offering structured paths to mastery.
  • Flashcards and Memory aids: Enhance memory retention with customizable digital flashcards, exportable to Anki and Quizlet.
  • Quiz and test generation: Automatically generate quizzes and tests based on the uploaded material.
  • Quiz and test grading: Receive automatic grading and feedback on quizzes and tests to track progress and identify improvement areas.
  • Compendium: Generate a summary of the uploaded material, making it easier to review and understand the content.
  • Study streaks: Motivate regular engagement with learning material through gamified elements, making education a daily habit, and exams passed easily.

Quick Start

Prerequisites

Clone the repository

git clone https://github.com/CogitoNTNU/TutorAI.git
cd TutorAI

Configuration

Create a .env file in the root directory of the project and add the following environment variables:

OPENAI_API_KEY = 'your_openai_api_key'
MONGODB_URI = 'your_secret_key'

Optionally, you can add the following environment variables to customize the project:

GPT_MODEL = 'gpt-3.5-turbo' # OpenAI model to use

Usage

To start TutorAI, run the following command in the root directory of the project:

docker compose up --build

Then navigate to http://localhost:3000 in your browser to access the UI of the frontend.

To access the backend, navigate to http://localhost:8000 in your browser.

📖 Documentations

Contributors


Henrik Halvorsen Kvamme

Kaamya Shinde
Kristoffer Nohr Olaisen
Kristoffer Nohr Olaisen
Olav Selnes Lorentzen
Olav Selnes Lorentzen

Parleen Brar

Simon Sandvik Lee

Skage Reistad

Sverre Nystad

Tobias Fremming

This project would not have been possible without the hard work and dedication of all of the contributors. Thank you for the time and effort you have put into making TutorAI a reality.

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License

Licensed under the MIT License.

About

TutorAI is a RAG system capable of assisting with learning academic subjects and using the curriculum and citing it. The project revolves around building an application that ingests a textbook in most formats and facilitates efficient learning of the course material.

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