How to Build an AI Voice Assistant in Python Using OpenAI ChatGPT API?

Are you interested in building your own AI voice assistant? In this tutorial, we’ll show you how to build an AI voice assistant in Python using the OpenAI ChatGPT API. We’ll walk through every line of code, so even if you’re not familiar with OpenAI, you can follow along.

How to build an AI voice assistant in Python using the OpenAI ChatGPT API?

Set up the environment

Before we dive into the code, we need to set up our environment with the necessary tools. First we install several libraries, including Chargpt APA, OpenAI Whisper, and CoQE TTS text-to-speech. We will also build everything in Gradio, an easy-to-use UI tool that will allow us to build the interface for our application.

Next, we set up the text-to-speech model, the speech-to-text model, and our OpenAI key. We use the OpenAI Whisper library for speech transcription and the OpenAI API for GPT-3 completion.

Install libraries

To get started, we need to install the required libraries. We use TTS, a text-to-speech library, as well as Numpy, OpenAI Whisper, Gradio and OpenAI.

difference

!pip install TTS
!pip install numpy==1.21
!pip install openai==0.10.2
!pip install gradio
!pip install openai_whisper

Import libraries

After installing the libraries, we import all the necessary models. We import Whisperous, Whisper, Gradio, OpenAI and TTS. These libraries will help us build the different components of our AI voice assistant.

Python

import whisperous.whisper as whisper
import gradio as gr
import openai.api as api
import TTS

Set up the text-to-speech model

Next, we’ll set up the text-to-speech model. We will use the TTS library to build the model. This allows our AI voice assistant to convert text into speech.

makefile

# Set up TTS model
tts = TTS.TTS()
tts.load_model(engine="tts", lang="en")

Set up the speech-to-text model

We also need to set up the speech-to-text model. We will use the OpenAI Whisper library to build this model. This allows our AI voice assistant to convert speech into text.

sharp

# Set up Whisper
wh = whisper.Whisper()
wh.init(whisper.DeviceType.GPU, "en-US")

Set the OpenAI API key

Finally, we will set up our OpenAI API key. This allows us to use GPT-3 for language completion.

makefile

# 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 will use Gradio to build the user interface for our application. This allows users to ask questions and receive answers from our AI voice assistant.

Python

def generate_response(text):
    # Convert text to speech
    audio = tts.get_tts(text, "female")

    # Convert speech to text
    text = wh.transcribe(audio, "en-US")

    # Generate response using GPT-3
    prompt = "Answer the following question: " + text
    response = api.Completion.create(engine="text-davinci-002", prompt=prompt, max_tokens=1000)

    # Convert response to text
    answer = response.choices[0].text

    # Convert text to speech
   

Conclusion

In short, building an AI voice assistant using the OpenAI ChatGPT API and Python is a great way to explore the potential of AI technology. With the libraries and tools available, it is easy to set up an environment and create an AI voice assistant that can respond to user queries and perform various tasks.

In this tutorial, we went through the process of setting up the environment by installing the necessary libraries and models. We then built the text-to-speech and speech-to-text models and set up the OpenAI API key. Finally, we used Gradio to create the user interface for our AI voice assistant.

While this tutorial is a good starting point, there are many other ways to improve and customize your AI voice assistant. For example, you can add more functionality, such as the ability to send emails, play music or control smart home devices. Furthermore, you can train your AI model on specific domains or improve its accuracy by fine-tuning it.

Overall, building an AI voice assistant is a fun and rewarding project that can provide a lot of value to users. With the power of OpenAI ChatGPT API and Python, the possibilities are endless.

Frequently Asked Questions

Of course, here are some helpful FAQs about building an AI voice assistant in Python using the OpenAI ChatGPT API:

🌟Do you have burning questions about ChatGPT? Do you need some extra help with AI tools or something else?
💡 Feel free to send an email to Arva Rangwala, our expert at OpenAIMaster. Send your questions to support@openaimaster.com and Arva will be happy to help you!

Published on March 5, 2023. Updated on October 20, 2023.

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