Self-Improving Python Scripts with LLMs: My Journey

As a developer, I've always been fascinated by the idea of self-improving code. Recently, I embarked on a journey to make my Python scripts improve themselves using Large Language Models (LLMs). In this article, I'll share my experience and provide a step-by-step guide on how to achieve this.## Introduction I've been working with Python for several years, and I've always been impressed by its simplicity and flexibility. However, as my projects grew in complexity, I found myself spending more and more time maintaining and updating my code. That's when I discovered the concept of self-improving code, where a program can modify its own behavior or structure in response to changing conditions or new information. LLMs, with their ability to understand and generate human-like text, seemed like the perfect tool to make this vision a reality.## Setting up the Environment To get started, you'll need to install the transformers library, which provides a wide range of pre-trained LLMs. You can in