GUI Assistant Using ChatGPT and Python 🤖

Hi everyone👋, In this article we will be creating a GUI ChatGPT application using Python, you can use the tkinter library for the graphical interface and the OpenAI API to interact with the ChatGPT model. Here's an example of how you can build a simple GUI chat application :

import tkinter as tk

import openai

# Set up OpenAI API credentials

openai.api_key = "YOUR_API_KEY"

# Function to handle sending a message

def send_message():

message = entry.get()

if message.strip() != "":

chat_box.insert(tk.END, "User: " + message + "\n")

response = generate_response(message)

chat_box.insert(tk.END, "ChatGPT: " + response + "\n")

entry.delete(0, tk.END)

# Function to generate a response using ChatGPT model

def generate_response(message):

response = openai.Completion.create(

engine="text-davinci-003",

prompt=message,

max_tokens=50,

temperature=0.7

)

return response.choices[0].text.strip()

# Create the main window

window = tk.Tk()

window.title("ChatGPT GUI")

# Create a chat box

chat_box = tk.Text(window, width=50, height=20)

chat_box.grid(column=0, row=0, padx=10, pady=10)

# Create an entry field for user input

entry = tk.Entry(window, width=40)

entry.grid(column=0, row=1, padx=10, pady=10)

# Create a button to send the message

button = tk.Button(window, text="Send", command=send_message)

button.grid(column=1, row=1, padx=10, pady=10)

# Start the GUI main loop

window.mainloop()

In this example, replace "YOUR_API_KEY" with your actual OpenAI API key. Make sure you have the OpenAI Python library installed (`pip install openai`) and you have an active OpenAI API key.

The send_message() function is called when the user clicks the "Send" button. It retrieves the message from the entry field, adds it to the chat box as a user message, generates a response using the ChatGPT model, and adds the response to the chat box.

The generate_response() function makes an API call to OpenAI's completion endpoint using the OpenAI Python library. It sends the user's message as the prompt and retrieves a response from the ChatGPT model. Adjust the parameters of the API call (`max_tokens`, temperature, etc.) based on your desired behavior.

The main window is created using tk.Tk(), and the chat box and entry field are added using tk.Text() and tk.Entry(), respectively. The "Send" button is created using tk.Button(), and its command is set to the send_message() function.

To run the application, save the code in a Python file (e.g., chatgui.py) and run it using the Python interpreter.

You should see a window with a chat box, an entry field, and a "Send" button. Type a message in the entry field and press Enter or click the "Send" button to see the response from the ChatGPT model displayed in the chat box.

Alright, guys! I hope this article was helpful for you, and if was then leave your comments below. I will meet you in another article until then KEEP CODING🤗.