Create Your Own Personal Assistant with Python and ChatGPT API

Create Your Own Personal Assistant with Python and ChatGPT API

Table of Contents

1. Introduction
2. Incorporating GPT
   1. Using GPT-3 Model
   2. Incorporating Chat GPT
3. Getting the Computer to Speak
   1. Initializing the Text-to-Speech Engine
   2. Creating the Speak Function
4. Conclusion

Introduction

Welcome to Fighter Code! In this video, we'll Continue working on our personal assistant. So far, we have been able to communicate with our computer and perform various tasks such as opening programs and searching on Google. In this tutorial, we will be incorporating the GPT (Generative Pre-trained Transformer) model into our personal assistant. We will explore two different ways of using GPT: GPT-3 model and Chat GPT. Additionally, we will also add the functionality for the computer to speak, allowing us to hear the responses generated by GPT. So let's get started!

Incorporating GPT

Using GPT-3 Model

To start using the GPT-3 model, we need to import the OpenAI module and set up the API key. The API key is essential for accessing the GPT-3 model. You can obtain your API key from your OpenAI account. Once we have the API key, we can proceed with setting up the GPT-3 model. We specify the model as "DaVinci" and define parameters such as temperature and max tokens to control the response generation. We then generate a response using the GPT-3 model.

Incorporating Chat GPT

Apart from the GPT-3 model, we will also incorporate Chat GPT into our personal assistant. Chat GPT allows for more interactive conversations with the computer. Similar to the previous section, we start by importing the necessary modules and setting up the API key. However, this time we also initialize an empty array called "conversation" to keep track of the ongoing conversation with Chat GPT. We define the prompt and generate a response using the Chat GPT model.

Getting the Computer to Speak

To make our personal assistant even more interactive, we will enable the computer to speak the responses it generates. For this, we will be using the PiTTSx3 text-to-speech engine. We first initialize the engine and set the rate of speech. Then, we define a function called "speak" that takes in text as input and uses the engine to convert it into speech. This function ensures that only one speech is played at a time. We then integrate the "speak" function into our personal assistant to make it speak the generated responses.

Conclusion

In this tutorial, we have successfully incorporated the GPT-3 model and Chat GPT into our personal assistant. We have also added the functionality for the computer to speak, making the interaction more dynamic and engaging. With the new capabilities, our personal assistant can generate responses using the power of GPT and deliver them audibly. Stay tuned for the next video, where we will explore how to control Spotify using Python in our personal assistant. Don't forget to leave any comments or questions down below!