A Django web backend server that has a single API for collecting sentiment text in JSON format, analysing it with an optimisation of a pretrained BERT model and returning the sentiment of the text as a JSON response.

Requires the following packages:

• Python 3.9.7 or higher
• Django 4.0 or higher
• pip 22.3.1 or higher

It is recommended to use virtual environment packages such as virtualenv. Follow the steps below to set up the project:

• Clone this repository via git clone https://github.com/parvez86/SentimentAnalysisAPI.git
• Create and Activate a Virtual Environment (Recommended):

  Bash
  python -m venv venv
  # On Windows
  .\venv\Scripts\activate
  # On macOS/Linux
  source venv/bin/activate
  

• Use this command to install required packages: pip install -r requirements.txt
• Crate database and change database settings in settings.py according to your database.
  • Mysql:

     DATABASES = {
     'default': {
     'ENGINE': 'django.db.backends.mysql', 
     'NAME': 'DB_NAME',
     'USER': 'DB_USER',
     'PASSWORD': 'DB_PASSWORD',
     'HOST': 'localhost', # Or an IP Address that your DB is hosted on
     'PORT': '3306',
     }
     }
    

  • SQLite:

     DATABASES = {
     'default': {
     'ENGINE': 'django.db.backends.sqlite3',
     'NAME': 'mydatabase', # This is where you put the name of the db file. 
     # If one doesn't exist, it will be created at migration time.
     }
     }
    

  • Others: See documentation, add appropriate database settings and install the connector.
• Check Migrations of the project via terminal: python manage.py makemigrations
• Migrate the project from terminal: python manage.py migrate
• Create admin user for admin panel from terminal: python manage.py createsuperuser. Then enter the username, email and password.
• Run the project from terminal: python manage.py runserver

• Run the model
• At endpoind /analyze:
  • add request payload:

     {
     "text": "write your sentences"
     }
    

  • response will return:

     {
     "sentiment": "negative/neutral/positive"
     }