Do you want to create your own AI voice assistant? In this tutorial, we’ll demonstrate how to use the OpenAI ChatGPT API to create an AI voice assistant in Python. Even if you’re not familiar with OpenAI, you’ll be able to follow along because we’ll go over every line of code.
Setting Up the Environment
- Installing libraries: We will begin by installing the required libraries. This includes Chargpt APA, OpenAI Whisper, and CoQE TTS text-to-speech. These libraries provide the functionality we need for our application.
- Setting up Gradio: Gradio is a user interface tool that simplifies the process of building interfaces for our application. We’ll utilize Gradio to create an intuitive and user-friendly interface.
- Configuring text-to-speech and speech-to-text models: We’ll set up the text-to-speech model and the speech-to-text model. These models are essential for converting text to speech and vice versa. We’ll use the CoQE TTS text-to-speech library for this purpose.
- Obtaining the OpenAI key: To access the GPT-3 completion functionality, we’ll need an OpenAI key. This key allows us to interact with the OpenAI API, enabling us to leverage the power of GPT-3 for our application.
To get started, we’ll need to install the required libraries. We’re using TTS, a library for text-to-speech, as well as Numpy, OpenAI Whisper, Gradio, and OpenAI.
Once we’ve installed the libraries, we’ll import all the required models. We’ll import Whisperous, Whisper, Gradio, OpenAI, and TTS. These libraries will help us build the different components of our AI voice assistant.
import whisperous.whisper as whisper import gradio as gr import openai.api as api import TTS
Setting Up the Text-to-Speech Model
Next, we’ll set up the text-to-speech model. We’ll use the TTS library to build the model. This will allow our AI voice assistant to convert text into speech.
# Set up TTS model tts = TTS.TTS() tts.load_model(engine="tts", lang="en")
Setting Up the Speech-to-Text Model
We’ll also need to set up the speech-to-text model. We’ll use the OpenAI Whisper library to build this model. This will allow our AI voice assistant to convert speech into text.
# Set up Whisper wh = whisper.Whisper() wh.init(whisper.DeviceType.GPU, "en-US")
Setting Up the OpenAI API Key
Finally, we’ll set up our OpenAI API key. This will allow us to use GPT-3 for language completion.
# Set up OpenAI API key api_key = "YOUR_API_KEY" api.api_key = api_key
Building the AI Voice Assistant
Now that we’ve set up our environment, we’re ready to start building our AI voice assistant. We’ll use Gradio to build the user interface for our application. This will allow users to ask questions and receive responses from our AI voice assistant.
To sum up, creating an AI voice assistant with Python and the OpenAI ChatGPT API is a fantastic approach to explore the potential of AI technology. It’s simple to build up an environment and construct an AI voice assistant that can reply to user requests and carry out a variety of tasks using the libraries and tools provided.
The process of setting up the environment by installing the required libraries and models was covered in this lesson. Following the creation of the text-to-speech and speech-to-text models, the OpenAI API key was created. Finally, we utilised Gradio to design the voice assistant’s user interface.