This repository contents Python, JS, CSS, and html files necessary to run a SuperAPI/ChatGPT powered Quiz application with adaptable level of difficulty. The process of preparation, launching, and evaluation will be explained in this README file. Hope you enjoy the experience to evaluate this quiz application powered with one of the more novel APIs such as SuperAPI. If the SUPERAPI is already down in your account. Then use the direct access to the chatGPT API, to be sure your chatGPT API will work, be sure your usage limit is set up in the usage tier1 (minimum). Modify the file question_generator_chatGPT.py and add your own api_key. The code will work transparently. Please check the ChatAPI modelsand the ones you can use on https://platform.openai.com/docs/models/overview. When you add more tokens and prompts on this models you will charged with different monetization, check that in your account, specifically in the OpenAI usage section.

The queries to adapt difficulty and to bring questions to the chatbox in this appication are powered by this SuperAPI. In the following steps we will explain how to execute this app. This app works better in Linux environments such as Ubuntu 20.04 or similar distributions and Mac OS X -> after installing any version of Python>=3.8 and the requirements including in this repository. For deploying this in Windows it will be necessary to install Cygwin and PuTTY to manage the files and the connections.

First download all the files of this repository from the green button to download the code as zip file or using git clone, you need to have git installed in your system.

git clone https://github.com/meiyor/GPT_superAPI_Quiz.git

Now install pip and python-dev in your system already having Python>=3.8 already installed in your system

apt update
apt install python3-pip, python-dev

Having pip installed you must install the requirements included as the file requirements.txt. Then, go to the root folder and run this command to install the requirements that are necessary for running the app. Some of the requirements for this app are Flask, Flask-cors, requests, Flask-SQLAlchemy, and subprocess.

pip3 install -r requirements.txt

The next step is setting a ngrok account in ngrok.com. Having an account you can download the latest version for linux and add it in the folder /snap/bin/ if you want to do it more automatically you can use the ngrok file added in this repository and added in the folder /snap/bin/ or installinng it using snap following this command.

snap install ngrok

Now, you need to authenticate your ngrok account running the command for authorization located in the ngrok dashboard, as it is shown in the following image and command.

ngrok config add-authtoken 2QwQndCshan5Blls6oewbCPRUbe_2HG1EGCAE59mpJnEZhmZs

I added here my configuration key code but you must have one in your account dashboard when you activate yours. This process will let you activate a VPS in your local machine and will give you a public address where you can access your application. Now you need to allow permissions to port 5000 and 4040. You can do it with the ufw command.

ufw allow 5000
ufw allow 4040

These are the ports where your application will run the communication between Flask and javascript. More specifically the ngrok server and your application. The next step is loading/uploading the ngrok server following this command.

ngrok http 5000

After running this command you will obtain the following screen in your terminal giving the real-time status of the ngrok server and the public address where your application app.py will be located. I have marked in a red rectangle (1) the address of the server and (2) the route of the public address that the application will have. Take these addresses into account for next steps.

Now we are are ready to deploy/launch the application on the ngrok server.

The first step for deploying is setting app the SQL database as local file with Flask-SQLAlchemy and SQLAlchemy, to set the database tables you need to execute the following python command located in the root directory.

python3 db_create.py

The next step integrates the Flask web app contained in the file app.py with the javascript engine included in the static folder as app.js. The user interface is constructed in the templates folder as the html file base.html. This will be loaded in the ngrok server from the port 5000. Therefore, in order to deploy the app you must open a new terminal (additional to the ngrok server one) and execute the following python command located in the root directory.

python3 app.py

While both terminals are running you can open the browser of your preference. I suggest firefox or Google Chrome and copy and paste the address you obtained from the ngrok server as forwarding address. The one marked in the red rectangle. This address can be accessed from anywhere in the world while the app.py and the ngrok server are active/running. Having the server running we will obtain the following screen after accessing the ngrok forwarding address.

In this page you need to click the button Visit site and accept the regulations of the ngrok server. After you click it you will see the presentation of the Flask and SuperAPI based web app running. It is presented as follows.

In this web presentation we have the login section marked in the red rectangle and the chat deploy button marked with a green rectangle. Now, we will continue with the testing and evaluation of this web app.

The first you must do is to enter the user name and password in the login section and click on the login button. This will set your username and password information for the database and the chatbox. The chatbox will refer to you as your username all the time you are testing different questions/quizzes. After you set your login process a text will appear in the login status field as new user 'username'. Note that the database is not checking for repeated usernames or passwords yet. It generates a new field in the database each time a quiz is finalized. We can call it a quiz trial.

If and only after you login you can click the chatbox button marked with the green rectangle because it will be first time it will appear. This embedded chatbox can offer you an infinite different amount of quizzes only if you want to continue to do more. When you click on it the chatbox it will ask if you want to solve a quiz with a random number of questions between 3 and 15. The chatbox will ask you first if you want to proceed with the quiz and you must answer yes, y, Yes or any equivalence in uppercase can be processed. After you answer yes you can start selecting the letters the chatbox will give you as options/answers. The following screen will appear after you answer/reply yes and start the quiz.

Now, you must continue answering with the letters the chatbox is given to you. You can answer/reply A or A. or A) and whatever of these options can be processed with lower cases too. You have indefinitive time to answer each question, maybe some time contraints can be set in the future. While you are advancing in the quiz the chatbox will tell you how many questions you have answered correctly and when you finished the quiz they will tell you your percentage of correctness. If you reply yes when you finish your quiz the app will save your responses, correctness and the questions that have been asked to you in the database.

The following screen is obtained during the quiz evaluation, and there the chatbox will inform the user/you how many correct questions has been achieved.

Subsequently, when the quiz ends the following screen appears showing the user/you (1) what was your level of correctness in the quiz and (2) if you want to save your information in the database.

You can do the amount of quizzes you want replying yes to the quizzes continuation. Each quiz trial will be saved in the database. To stop the process you must reply n, N, No or similars in upper cases AND clicking again in the chatbox deploy button. This will erase all the messages in the chatbox and you will start the quizzes from scratch, zero quizzes, and zero questions added in the SuperAPI query for adapting the difficulty. If you start from zero it is possible that some questions will be repeated. Therefore I suggest to do as many quizzes as possible to fill more the query and get more developed questions. When the system ask you to save your data in the database please reply yes, and subsequently you can reply no to finish the entire quizzes session or continue with more quizzes replying yes.

Finally, here we show a screenshot of the database showing the quiz trials I have until now, the number of correct answers, and the level of correctness. We can see the database file (called database.db) in any online SQL viewer. The id is generated randomly and it is the primary-key per quiz trial. The questions are saved in a Pickle format. Using SQLAlchemy it is easy to convert all this question data to a list or json format. For now the web-app is loaded in the serve in the following address https://8e3a0b607831.ngrok.app/.

This same repository is located in a Google Drive link here https://drive.google.com/file/d/1uJllFRy8v5x6hGiJXS5PVgHejwxa1VQA/view?usp=sharing

It tooks me a lot of work and time to put this Flask based web app in a public address. Most of the free and pay-as-go Linux servers that are available in the web, and support Flask, use gunicorn or WSIG and this represent a high web concurrency in the deploying process. These dedicated servers launch multiple threads and we need to contact the people who manages these servers to let them fire only one fork and one worker per session to avoid the usage of an extra database for the global variables in app.py. For the future we can make the SuperAPI query a bit more complex adding more data and more questions, and specifying more topics, but this is out of the scope of this web app. Hope you enjoy testing it and this work can be a starting point for more complete and ambitious projects.