How to use ChatGPT-3 in Python

How to use ChatGPT-3 in Python

Written by Omar Moustafa on Feb 5th, 2023 Views Report Post

ChatGPT is a state-of-the-art language model developed by OpenAI. It is a deep learning model trained on a vast amount of text data, allowing it to generate human-like text and respond to text-based inputs. It is considered one of the most advanced language models currently available, with a vast knowledge base and the ability to generate coherent and coherently formatted text.

In this article, we will explain how to use ChatGPT-3 in Python. We will cover the steps necessary to obtain an API key for OpenAI's GPT-3 and how to integrate the language model into a Python application.

Using ChatGPT with Python

To use ChatGPT, there are 2 ways:

  • Using the OpenAI library
  • Using the OpenAI's API

Using the OpenAI library

To get started, you will need to obtain an API key for OpenAI's GPT-3. This can be done by creating an account on the OpenAI website and applying for access to the GPT-3 API.

Once you have obtained an API key, you will need to install the openai library in Python. You can install this library using pip by running the following command in your terminal or command prompt:

pip install openai

After the openai library has been installed, you can use the following code to initialize the GPT-3 model and generate text:

import openai

# initialize the OpenAI API key
openai.api_key = "your_api_key_here"

# generate text using the GPT-3 model
model_engine = "text-davinci-002"
prompt = "What is the capital of France?"

completions = openai.Completion.create(

message = completions.choices[0].text

This code will generate a text response to the prompt "What is the capital of France?" using the text-davinci-002 model engine. The response will be printed to the console.

Using the OpenAI's API

OpenAI's API is a cloud-based platform that allows developers to access GPT-3 and other AI models developed by OpenAI. It is a convenient way to incorporate state-of-the-art language processing capabilities into your applications without having to train the models yourself.

To use the OpenAI API, you'll need to sign up for an API key, which will give you access to a limited number of requests per month. With the API key, you can send a request to the API with some input text, and the API will respond with the generated text. You can control the length and content of the generated text by specifying various parameters in the API request.

  1. Sign up for an OpenAI API key: Go to the OpenAI website and sign up for an API key. You'll need to provide some information and agree to the terms and conditions.
  2. Install the requests library: The requests library is a popular Python library for making HTTP requests. You can install it using pip by running the following command in your terminal:
pip install requests
  1. Send a request to the OpenAI API: Use the requests library to send an HTTP POST request to the OpenAI API endpoint. You'll need to specify the API key, the model to use (GPT-3), the input text, and any other parameters you want to control. Here's an example:
import requests

def generate_text(prompt):
    api_key = "your_api_key_here"
    model = "text-davinci-002"
    endpoint = f"{model}/jobs"
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {api_key}"
    data = {
        "prompt": prompt,
        "max_tokens": 100,
        "n": 1,
        "stop": None,
        "temperature": 0.5,
    response =, headers=headers, json=data)
    if response.status_code == 200:
        response_json = response.json()
        return response_json['choices'][0]['text']
        return None

generated_text = generate_text("Hello, how are you?")
  1. Parse the response: The OpenAI API will respond with a JSON object that contains the generated text. You can parse the response and extract the text to use it in your application.

That's it! With these steps, you can use the OpenAI API to generate text using GPT-3 in Python. Of course, you can modify the parameters and customize the code to fit your specific needs.

Outro 🎉

In conclusion, OpenAI offers two ways for developers to leverage its cutting-edge technology: through the OpenAI API and the OpenAI Library. Both methods provide access to state-of-the-art AI models, allowing for a wide range of use cases, from natural language processing to computer vision. Whether you're a seasoned developer or just starting out, OpenAI has something to offer to bring your AI projects to life.

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