24-7 Learning Buddy

This repository contains a comprehensive educational delivery system, offering a flexible and intuitive platform for online learning.

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Please note that, at present time, Expo can only be run in an emulator on the same machine as the server. Future fixes to be determined.

First-time user? Check out the Setup Information Section below to get started.

Please note that an API token is required to prompt ChatGPT for solutions. You can get your own token after creating an account on the OpenAI website.

Running the Frontend Server

To start the Expo server, navigate to the project's root directory and use the command npm run start:app.

Running the Backend Server

To start the FastAPI server, navigate to the project's root directory and use the command npm run start:backend. Be sure to run your backend and frontend servers in different terminals.

Setup Information

Note that two .env files are required for the operation of this repo at present time.

1. The first one will be in apps/Learning-Buddy, with the four following fields: IP, SUPABASEURL, SUPABASEKEY_PUBLIC and SUPABASEKEY_SECRET. The IP field should be automatically populated with your IPv4 address upon your first time running the frontend with npm run start:app.
2. The second one can be found in backend, and has the following fields: API-TOKEN and DATABASE_URL. The API-TOKEN field is required to prompt OpenAI's API and can be created through creating your own account on their website.

Backend Setup:

Server Setup (Python version 3.10)

1. Install Python. If you encounter the error "python: command not found," you can contact Maggie for assistance.
2. Open your terminal in the project's backend folder.
3. Run the command python -m venv venv.
4. Activate the virtual environment with the command source venv/scripts/activate. If you encounter any issues, refer to the appropriate command for your operating system (e.g., bin/activate).
5. Set the Python path by running export PYTHONPATH=$PWD.
6. Install the required dependencies with pip install -r requirements.txt.
7. Testing: to confirm server functionality, run python main.py from the same folder. Point your browser to http://localhost:8000/docs to ensure it is working.
8. See Swagger documentation for API endpoints.

PostgreSQL Setup (supabase)

1. Obtain the URI connection string for DATABASE_URL in the backend/.env file. If you are using your own supabase account/project you can find the connection string under "Project Setting -> Database -> Connections string" and pick URI as the type, copy to .env and replace [YOUR-PASSWORD] with your password.
2. If you you are connecting to your database for the first time you will need to start your backend server and run the endpoint '/initialize-triggers-functions/'. This will initalize user profile table and create triggers to add new users to profile table as they sign up in your application.

Frontend:

Ensure that you use a separate terminal from the one used for the backend server.

1. Start by running npm install from the root directory. This command will target all workspaces within.

Note: If you encounter errors and want to deactivate the virtual environment, run the command deactivate.

Text extractor

To extract text from the image we are using tesseract.

For windows

1. download binary from https://github.com/UB-Mannheim/tesseract/wiki.
2. If you don't have tesseract executable in your PATH, include the following: pytesseract.pytesseract.tesseract_cmd = r'<full_path_to_your_tesseract_executable>'

Example tesseract_cmd = r'C:\Program Files (x86)\Tesseract-OCR\tesseract'

For macOS brew install tesseract

File Routes to handle extract and file crud

• file/extract
• file/all/{userId}
• file/create/{userId} // pass data as {name: "File Name", text: "File Text"}
• file/update/{id} // pass data as {name: "New File Name", text: "New File Text"}
• file/delete/{id}