LeverageGuild

A Django based web application which using machine learning regression model to predict the output which is especially designed for students to make their admission and univesity selection procedure completely conspicious. furthmore, it helps them in a wide range of feature as showing their chances of getting into their dream university, handing out an essay outline through OpenAi, also it nudges students by sending them scholarship deadline updates. Agglomerating it is a one stop shop which has a crisp delivery to otherwise fussed up students.

Installation Steps(Windows): Perform the following steps in order to install the Project onto your System:

Step 1: Create Virtual Environment:

  python -m venv env

Step 2: Activate the Environment:

env\Scripts\Activate.bat

Step 3: Clone

git clone https://github.com/umangkalavadiya/LeverageGuild.git

Step 4: Install all the Packages: After Activating the Virtual Environment. For installing all the packages used for the development of this project (Note: requirements.txt will be included in the project folder.).

 pip install -r requirements.txt

Step 5: Run the below command to makemigrations

python manage.py makemigrations

Step 6: Run the below command to migrate

python manage.py migrate

Step 7: Run the below to start the server

python manage.py runserver

Changes you should make in the settings.py file:

#Gmail SMTP
EMAIL_USE_TLS = True
EMAIL_PORT = 587
EMAIL_HOST = 'smtp.gmail.com'
EMAIL_HOST_USER = 'your email id'
EMAIL_HOST_PASSWORD = 'Your app password'
EMAIL_BACKEND = 'django.core.mail.backends.smtp.EmailBackend'

Changes you should make in the Login/views.py file:

def generate_essay(request):
    api_key = "write your api key"
    model = "text-davinci-002"
    prompt = "write me an application letter for parul university in 1000 words"

    response = requests.post(
        "https://api.openai.com/v1/completions",
        headers={
            "Content-Type": "application/json",
            "Authorization": f"Bearer {api_key}",
        },
        json={
            "model": "text-davinci-002",
            "prompt": prompt,
            "temperature": 0.5,
            "max_tokens": 2048,
        },
    )

    essay = response.json()
    return render(request, "application.html", {"essay": essay})