```python
import os
from dataclasses import dataclass
from typing import Union
import openai
from openai.api_resources.experimental.completions import Completions

# Defaults for the OpenAI API
DEFAULT_PROMPT = "Translate these English words to French: {}"
DEFAULT_SYS_MSG = "Please wait while we process your request..."
DEFAULT_MODEL = "text-davinci-002"
DEFAULT_MAX_RETRY = 3
DEFAULT_BACKOFF_FACTOR = 1.1
DEFAULT_INITIAL_WAIT = 1
DEFAULT_MSGS = [{"role": "system", "content": DEFAULT_SYS_MSG}]
DEFAULT_FUNCS = [{"role": "system", "content": 'def {}'.format('create_files(path: str)')}]

@dataclass
class FileCreationDetails:
    """Class for providing file creation details"""
    file_path: str
    initial_content: str


class PragmaticProgrammerAGIAgent:
    """
    The PragmaticProgrammerAGIAgent class empowers the creation of high-quality code by combining advanced techniques
    to generate, evaluate, and refine code along with its corresponding tests. It follows the principles of the Pragmatic
    Programmer's approach to software development.
    """

    def openai_completion(
            self,
            prompt=DEFAULT_PROMPT,
            sys_msg=DEFAULT_SYS_MSG,
            msgs=DEFAULT_MSGS,
            funcs=DEFAULT_FUNCS,
            model=DEFAULT_MODEL,
            max_retry=DEFAULT_MAX_RETRY,
            backoff_factor=DEFAULT_BACKOFF_FACTOR,
            initial_wait=DEFAULT_INITIAL_WAIT,
            raw_msg=False,
    ) -> Union[str, dict]:
        """
        Customized completion function that interacts with the OpenAI API, capable of handling prompts, system messages,
        """
        response = Completions.create(
            engine="davinci-codex",
            prompt=prompt,
            messages=msgs,
            model=model,
            max_tokens=512,
            n=1,
            stop=None if raw_msg else "\n",
            function=function,
        )
        return response['choices'][0]['message']['content']


    def create_files(self, file_details: FileCreationDetails):
        assert os.path.isabs(file_details.file_path), 'File path must be absolute'
        os.makedirs(os.path.dirname(file_details.file_path), exist_ok=True)
        with open(file_details.file_path, 'w') as f:
            f.write(file_details.initial_content)

    def generate_code(self, task_description: str):
        code = self.openai_completion(prompt=task_description)
        file_details = FileCreationDetails(file_path='/path/to/generated_code.py', initial_content=code)
        self.create_files(file_details)

# Create an instance of PragmaticProgrammerAGIAgent
agent = PragmaticProgrammerAGIAgent()

# Task description
task_description = 'Create a function that calculates the factorial of a number'

# Generate the code for the task
agent.generate_code(task_description)
```
This script showcases how to use `PragmaticProgrammerAGIAgent` for creating application starter kits, and other related tasks. It leverages OpenAI's new API resource `Completions` with a customized `openai_completion` method, which uses advanced NLP to perform tasks. The `generate_code` method takes a `task_description` argument, which describes the task at hand, and generates (then writes to disk) relevant Python code to accomplish the task. This approach makes it easy to generate, evaluate, and refine end-to-end applications.

```python
import os
import sys
import tempfile
import pytest
from pyfakefs.fake_filesystem_unittest import Patcher

class PragmaticProgrammerAGIAgent:
    """
    PragmaticProgrammerAGIAgent class that utilizes pytest library and pyfakefs to perform regression testing and full automation.
    PyFakeFs is used for mocking the filesystem module in Python for testing purposes.
    """

    def __init__(self):
        self.patcher = Patcher()
        self.fake_fs = self.patcher.fs

    def setUp(self):
        """
        Set up the testing environment.
        """
        self.patcher.setUp()

    def tearDown(self):
        """
        Tear down the testing environment.
        """
        self.patcher.tearDown()

    def create_fake_file(self, filename, contents):
        """
        Create a fake file in the mock filesystem.
        """
        self.fake_fs.create_file(filename, contents=contents)

    def test_file_creation(self):
        """
        Test file creation in the mock filesystem.
        """
        filename = '/test/file.txt'
        contents = 'test file contents'
        self.create_fake_file(filename, contents)

        with open(filename, 'r') as f:
            assert f.read() == contents

    def test_file_deletion(self):
        """
        Test file deletion in the mock filesystem.
        """
        filename = '/test/file.txt'
        contents = 'test file contents'
        self.create_fake_file(filename, contents)

        os.remove(filename)

        assert os.path.exists(filename) == False

    def test_regression_scenarios(self):
        """
        Define and execute all regression testing scenarios.
        """
        # Mock the stdin
        self.fake_fs.add_std_io()

        # Add your regression test scenarios here
        # ...

# Usage
agent = PragmaticProgrammerAGIAgent()
agent.setUp()

# Run test scenarios
agent.test_file_creation()
agent.test_file_deletion()
agent.test_regression_scenarios()

agent.tearDown()
```
This script performs regression testing by creating and deleting files in the mock filesystem by utilising the pytest library and pyfakefs. You can define your own regression test scenarios in the `test_regression_scenarios()` method. With this setup, you can easily add additional scenarios to suit your testing needs for your project.