Tools used

• Windows 11

• Visual Studio Code

• Python

Use ChatGPT in your Python script

ChatGPT and other AI models are likely to be the future of software development, and a string of other fields. This is not a bad thing, it is just a great tool for us developers. Most likely you have heard all about it, and perhaps you've used the GUI provided on the OpenAI website. It is also possible to integrate the model into your script! Let's do so :D

The hierarchy

root/
├── env
└── project/
    └── main.py

First of all, I want to create a folder, in which a create and activate a virtual environment, as well as a project folder where the .py files go.

Note: The # initiates a comment, so that bash command is explained

PS C:\root\py_scripts> mkdir pyterminal #create application folder
PS C:\root\py_scripts> cd pyterminal #switch to said folder
PS C:\root\py_scripts\pyterminal> py -m venv env #create virtual environment
PS C:\root\py_scripts\pyterminal> env\Scripts\Activate.ps1 #activate said environment
PS C:\root\py_scripts\pyterminal> mkdir project #create folder for .py files

When the virtual environment is up and running, I install the openai module, create a main.py file and pop open visual studio code.

(env) PS C:\root\py_scripts\pyterminal> pip install openai #install openai module
(env) PS C:\root\py_scripts\pyterminal> cd project #switch to project folder
(env) PS C:\root\py_scripts\pyterminal\project> new-item main.py #create .py file
(env) PS C:\root\py_scripts\pyterminal\project> cd.. #switch back
(env) PS C:\root\py_scripts\pyterminal> code . #open visual studio code

The main.py content is shown down below. Four modules are imported:

1. os, used to clear the terminal screen

2. json, used to parse json data

3. openai, well... that's why we're here!

4. time/sleep, used to delay so that the ChatGPT response doesn't disappear immediately

The function configOpenAI() sets the API key. Get YOUR_API_KEY, to do so you will need to create an account. Do not share this key as it is personal information.

The function promptChatGPT(question) relies primarily on the openai.Completion.create() function. The function's arguments are of importance:

1. The Identifier of the model you want to use, in this case, GPT-3. All models are found here.

2. The prompt itself, a string or tokens as OpenAI puts it.

3. The maximal amount of tokens in return from the AI model, limit of 2048-4096.

4. Temperature decides the creativity of the response, ranged 0 to 1 where 1 is the maximum.

5. There are many arguments left unsaid, read the docs and let a magical future unfold.

The return value of the said function is cast to a string, and subsequently, the JSON is parsed as we only want the text response in return from ChatGPT.

import os
import json
import openai
from time import sleep

def configOpenAI():
    openai.api_key = "YOUR_API_KEY"

def promptChatGPT(question="Test"):
    configOpenAI()
    chatGPT = "text-davinci-003"
    jsonData = openai.Completion.create(model=chatGPT, prompt=question, temperature=0, max_tokens=100)
    data = json.loads(str(jsonData))
    text = data['choices'][0]['text']
    print(text)

def main():
    choice = ""
    while True:
        os.system('cls')
        print("\nMenu:")
        print("\n[1] Prompt ChatGPT")
        print("[2] Quit")
        choice = input("Input: ")
        if choice == '1': promptChatGPT(input("Enter a prompt: "))
        elif choice == 'q': break
        sleep(5)

if __name__ == '__main__':
    main()

After running the script, the prompts await!

(env) PS C:\root\py_scripts\pyterminal\project> py main.py

The AI is the limit, happy coding!

Resources

OpenAI API Documentation