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AI-Powered Canvas Quiz Generator

🎥 Watch the Demo


📌 Project Overview

This project delivers a completed AI-powered tool that allows faculty to easily convert PDF course materials into fully formatted quizzes for their Canvas courses.

By simply uploading a PDF, instructors can receive a bank of well-structured, relevant quiz questions generated through AI, which are then automatically uploaded to their Canvas course, eliminating the need for manual formatting or question entry.

The tool is designed to streamline the quiz creation process and make it more accessible, especially for instructors managing multiple courses or large classes.

Key Features:

  • Automatic content extraction
  • AI-generated questions tailored to material
  • Seamless Canvas integration
  • Time-saving for large or multiple courses
  • Improves accessibility and learning experience

⚙️ Prerequisites

Install Python

Download Python
If needed: Watch Setup Video

Install NodeJS

Download NodeJS
If needed: Watch Setup Video

Install PyCharm

Download PyCharm
If needed: Watch Setup Video


🔑 API Setup

OpenAI API

Canvas API (Optional)

  • Generate a Canvas API token through your institution’s IT department for course-level integration.

🔐 Tokens Setup

Navigate to the /backend folder and open the .env file.
Paste the following values with your actual keys:

OPENAI_API_KEY=your_openai_api_key_here
CANVAS_API_KEY=your_canvas_api_key_here

🛠️ Running the Project

Backend Setup

  1. Open the project in PyCharm
  2. Open terminal and navigate to the backend folder:
    cd backend
  3. Install dependencies (only once):
    pip install Flask
    pip install flask-cors
    pip install PyPDF2
    pip install openai
    pip install firebase-admin
    pip install python-dotenv
    pip install requests
  4. Start the backend server:
    python aitoken.py -p 8080

Frontend Setup

  1. Open a new terminal and navigate to the frontend folder:

    cd frontend
  2. Install dependencies (only once):

    npm install
  3. Start the frontend:

    npm run dev
  4. Go to http://localhost:3000 in your browser


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Spring 2025 Senior Project

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