SmartSearch

SmartSearch is a platform that replicates the Canvas Discussions module with enhanced search capabilities using semantic search. It comprises three main components: analysis notebooks, a Flask backend, and a Next.js frontend.

Table of Contents

• Overview
• Project Structure
• Setup and Installation
  • Prerequisites
  • Backend Installation
  • Frontend Installation
  • Analysis Notebooks
• Usage
  • Running the Backend
  • Running the Frontend
  • Running Analysis Notebooks
• Contributing
• License

Overview

SmartSearch enhances the Canvas Discussions module by using semantic search for better information retrieval. It allows users to interact with discussions more effectively, using semantic understanding to search through content.

Project Structure

The repository is organized as follows:

SmartSearch/
│
├── backend/           # Flask backend for API and data processing
│   ├── app.py         # Main Flask application
│   ├── requirements.txt
│   └── ...            # Other backend files and directories
│
├── not_canvas/        # Next.js frontend for UI
│   ├── pages/
│   ├── components/
│   └── ...            # Other frontend files and directories
│
├── analysis/          # Jupyter notebooks for data exploration and testing
│   └── notebooks/
│
└── README.md          # Documentation

Setup and Installation

Prerequisites

Ensure you have the following installed on your system:

• Python 3.7+
• Node.js 14.x+
• npm (comes with Node.js)
• Virtual Environment (optional, but recommended)

Backend Installation

The backend is a Flask application located in the backend/ directory. To set up and run the backend:

1. Navigate to the backend directory:

   cd backend/

2. Create a virtual environment (optional):

   python -m venv venv
   source venv/bin/activate  # On Windows, use: venv\Scripts\activate

3. Install dependencies from requirements.txt:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the backend/ directory with the following variables:

     CANVAS_API_URL=https://canvas.ubc.ca/
     CANVAS_API_KEY=your_api_key_here
     CANVAS_COURSE_ID=161721
     

   • Replace your_api_key_here with your actual Canvas API key.
   • Ensure .env is added to .gitignore to avoid pushing it to version control.

5. Run the Flask application:

   flask run --port=5001

   The backend will be accessible at http://localhost:5001.

6. Testing the Backend:

   • Visit http://localhost:5001/discussions to see a list of discussions.
   • Use tools like Postman or curl to test the endpoints:

     curl http://localhost:5001/discussions

Frontend Installation

The frontend is a Next.js application located in the not_canvas/ directory.

1. Navigate to the frontend directory:

   cd not_canvas/

2. Install Node.js dependencies:

   npm install

3. Start the Next.js application in development mode:

   npm run dev

   The frontend will be accessible at http://localhost:3000.

4. Testing the Frontend:

   • Visit http://localhost:3000 to interact with the SmartSearch UI.

Analysis Notebooks

The analysis/ directory contains Jupyter notebooks for testing and prototyping semantic search models.

1. Navigate to the analysis directory:

   cd analysis/

2. Install Jupyter Notebook (if not already installed):

   pip install jupyter

3. Launch Jupyter Notebook:

   jupyter notebook

   Open and run the notebooks for analysis and testing.

Usage

Running the Backend

1. Ensure all dependencies are installed and environment variables are set up.
2. Start the Flask server:

   flask run --port=5001

Running the Frontend

1. Ensure the backend is running.
2. Start the Next.js application:

   npm run dev

Running Analysis Notebooks

1. Navigate to the analysis/ directory.
2. Launch Jupyter Notebook:

   jupyter notebook

3. Open and run the desired notebook.

Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a new branch:

   git checkout -b feature-branch

3. Make changes and commit:

   git commit -m 'Add new feature'

4. Push to your branch:

   git push origin feature-branch

5. Open a pull request.

License

This project is licensed under the MIT License.