Essay Generation Tool with PyQt and the ChatGPT API

In this chapter, we will dive into the exciting world of integrating the ChatGPT API with one of the most popular Python frameworks for app development, PyQt. You will build a user-friendly desktop essay generation tool, powered by the integration of PyQt and the ChatGPT API, allowing users to effortlessly generate well-written essays on any topic. Here, you will gain valuable insights into the design stages involved in building a PyQt desktop application.

We’ll guide you through the process of designing a desktop app using an object-oriented approach with PyQt, helping you to understand the fundamental concepts and components involved in that framework. With a solid foundation in place, we’ll then shift our focus to leveraging the capabilities of the ChatGPT API. You will learn how to integrate the API into your PyQt application, enabling you to generate essays seamlessly.

By combining the strengths of PyQt and...

Technical Requirements

In this chapter, we will demonstrate the complete PyQt6 installation. However, to successfully finish the Essay Generation Tool project, you should ensure that you also meet the following technical prerequisites:

• Python 3.7 or later installed on your machine
• A code editor, such as PyCharm (recommended)
• A Python virtual environment
• An OpenAI API key
• Familiarity with Python Object-Oriented Programming (OOP) concepts

The code snippets showcased in this chapter can be found on the GitHub platform. Access to the code can be obtained by visiting the following link: https://github.com/PacktPublishing/Building-AI-Applications-with-ChatGPT-APIs/tree/main/Chapter08%20ArticleGenerator

In the upcoming sections, you will embark on the journey of building a desktop application using PyQt. You will dive into the intricacies of GUI design and learn how to leverage PyQt’s powerful features to develop a visually appealing and interactive...

Building a Desktop Application with PyQT

In this section, you will gain hands-on experience in creating various components of the PyQt application’s user interface, such as windows, labels, buttons, text fields, and drop-down menus. Here, you will set up the PyCharm project, install the PyQt6 and docx libraries, and build your desktop application frontend.

First, let’s discuss what the PyQt library is, and how it differs from the rest of the Python application development tools, such as Tkinter (see Table 8.1). PyQt is a powerful Python framework widely used for creating desktop applications with rich graphical user interfaces (GUIs). It provides developers with a comprehensive set of tools, classes, and functionalities to design and build intuitive and visually appealing applications. PyQt is a wrapper around the popular Qt framework, offering seamless integration of Qt’s extensive libraries and widgets into Python.

Important Note

PyQt is available under...

Creating Essay Generation Methods with the ChatGPT API

In this section, we will dive into the implementation of the key functions within the essay generator application. These functions are responsible for generating the essay based on user input and saving the generated essay to a file. By understanding the code, you will be able to grasp the inner workings of the application and gain insight into how the essay generation and saving processes are accomplished.

We will begin by exploring the generate_essay() function. This function will retrieve the topic entered by the user from the input field. It will then set the engine type for the OpenAI API, create a prompt using the topic, and make a request to the OpenAI API for essay generation. The response received from the API will contain the generated essay, which will be extracted and displayed in the essay output area of the application. To add that functionality, simply remove the pass placeholder and follow this code:

def generate_essay...

Controlling the ChatGPT API Tokens

In this section, we will explore how to enhance the functionality of the essay generator application by allowing users to have control over the number of tokens used when communicating with ChatGPT. By enabling this feature, users will be able to generate essays of different lengths, tailored to their specific needs or preferences. Currently, our application has a fixed value of 500 tokens, but we will modify it to include a drop-down menu that provides different options for token sizes.

To implement this functionality, we will make use of a drop-down menu that presents users with a selection of token length options. By selecting a specific value from the dropdown, users can indicate their desired length for the generated essay. We will integrate this feature seamlessly into the existing application, empowering users to customize their essay-generation experience.

Let’s delve into the code snippet that will enable users to control the...

Summary

In this chapter, you learned how to build a desktop application with PyQt and enhance its functionality by integrating the ChatGPT API for essay generation. We discussed the basics of PyQt and its advantages over other Python GUI development tools. We used that framework to create the application’s GUI components, such as windows, labels, input fields, text areas, and buttons.

The chapter also delved into the implementation of the essay generation functionality using the ChatGPT API. The main method discussed was generate_essay(), which took the user’s chosen topic, set the engine type, created a prompt using the topic, and sent a request to the API to generate the essay. The generated essay was then displayed in the application’s output area. You also learned how to build the save_essay() function, which used the docx library to save the generated essay as a Word document.

Furthermore, the chapter explored how to enhance the application by allowing...