Build an automated, AI-powered Slack Chatbot with ChatGPT using Flask

In this blog, we’ll explore how to create a Slack bot, add it to our Slack channel, and receive text responses from ChatGPT.

Step 1: Create a Slack Bot

A Slack Bot must be created to automate messaging with ChatGPT. Please follow the instructions steps 1 to 23 in our blog post Slack Bot with Python. Before moving forward, make sure you have followed the instructions on the blog.

Step 2: ChatGPT API

Please see our latest blog post, WhatsApp Chatbot With ChatGPT Step 2 “ChatGPT API”which includes guidelines for configuring and using ChatGPT

Step 3: Integrate the ChatGPT API with the Flask application

It’s time to integrate our ChatGPT API with the Flask application once its installation is successful.

However, the ChatGPT API will continue to run in the background of the Firefox browser, which may interfere with receiving responses from the ChatGPT API, so we need to end the process that is currently running in the browser.

def process():
        # iterating through each instance of the process
        for line in os.popen("ps ax | grep firefox | grep -v grep"):
            fields = line.split()
            # extracting Process ID from the output
            pid = fields[0]
            # terminating process
            os.kill(int(pid), signal.SIGKILL)
        print("Process Successfully terminated")
        print("Error Encountered while running script")

The Flask app we developed step 1 must be changed now. To get a ChatGPT response to user messages, replace the existing code in your Flask application with the following code.

import slack
import os, signal

from flask import request
from flask import Flask
from chatgpt_wrapper import ChatGPT
from slackeventsapi import SlackEventAdapter

app = Flask(__name__)
slack_event_adapter = SlackEventAdapter(SIGNING_SECRET, '/slack/events', app)

@ slack_event_adapter.on('message')
def message(payload):
    client = slack.WebClient(token=SLACK_TOKEN)
        if request.method == 'POST':
            event = payload.get('event', {})

            if event['client_msg_id']:
                channel_id = event.get('channel')
                user_id = event.get('user')
                text = event.get('text')
                bot = ChatGPT()
                chatbot_res = bot.ask(text) 
                print("ChatGPT Response=>",chatbot_res)
                return chatbot_res

    except Exception as e:
    return '200 OK HTTPS.'

if __name__ == "__main__":

Run the flask application in the terminal. python

Run ngrok in terminal. ngrok http 5000

Step 4: Test the Slack Chatbot

To receive a response generated by ChatGPT, please send multiple messages to the Slack bot. You will also receive a response on the server.

Here is the response from ChatGPT on our server.

We will receive the response below in our Slack Bot.

Let us know if you have any problems configuring or using the script. We will be happy to help. Contact us or write your request in the comments.

Also, check out our other tutorials to learn how to build a ChatGPT chatbot on different platforms.

WhatsApp with ChatGPT. Build an automated, AI-powered WhatsApp Chatbot with ChatGPT using Flask

Facebook Messenger with ChatGPT. Build an automated, AI-powered Facebook Messenger Chatbot with ChatGPT using Flask

Telegram Bot with ChatGPT. Build an automated, AI-powered Telegram Chatbot with ChatGPT using Flask.

We have already created a series of blog posts where we provided a tutorial on how to create a chatbot for different platforms. You can explore these blogs and learn how you can define different types of rich responses that can increase user engagement in your chatbot.

Telegram: Create a Telegram bot using Python tutorial with examples

Facebook Messenger. Create a Facebook Messenger bot using Python tutorial with examples

Slack: Create a Slack Bot using Python tutorial with examples

Discord: Create a Discord bot using Python tutorial with examples

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