How to Install Accelerated Text on macOS

Accelerated Text is a powerful Natural Language Generation (NLG) platform that enables developers and data scientists to create custom NLG models with ease. In this tutorial, we will learn how to install Accelerated Text on macOS.

Prerequisites

Before we start, you need to ensure that your system meets the following requirements:

Your macOS version is High Sierra (10.13), Mojave (10.14), Catalina (10.15), or newer.
You have Python 3.6 or higher installed.
You have Git installed. If you don't have Git installed, you can download it from here.

Steps to Install Accelerated Text

Open the Terminal by navigating to Spotlight Search in the upper right-hand corner of the screen and searching for "Terminal".
Navigate to the directory at which you want to install Accelerated Text by running the following command:
```
cd /path/to/directory
```
Clone the Accelerated Text repository by running the following command:
```
git clone https://github.com/accelerated-text/accelerated-text.git
```
After cloning the repository, navigate to the Accelerated Text directory by running the following command:
```
cd accelerated-text
```
Create a new python virtual environment by running the following command:
```
python3 -m venv env
```
Activate the virtual environment by running the following command:
```
source env/bin/activate
```

Install the required packages by running the following command:

pip install --upgrade pip setuptools
pip install -r requirements.txt

After installing the packages, run the following command to start Accelerated Text:
```
python manage.py runserver
```

If everything is done correctly, you should see the following output:

Performing system checks...

System check identified no issues (0 silenced).
May 31, 2021 - 10:00:12
Django version 3.2.3, using settings 'accelerated_text_server.settings'
Starting development server at http://127.0.0.1:8000/
Quit the server with CONTROL-C.

Congratulations! You have successfully installed Accelerated Text on macOS. Now you can start using it to create custom NLG models.