In this blog, we will discover how to build a Slack bot, add it to our slack channel, and receive text replies from ChatGPT.

Step 1: Create Slack Bot

Slack Bot must be created in order to automate messages with ChatGPT. Please follow the directions from steps 1 to 23 in our blog post Slack Bot with Python. Before moving forward, please make sure that you followed the blog’s instructions.

Step 2: ChatGPT API

Please view our recent blog post, WhatsApp Chatbot With ChatGPT Step 2 “ChatGPT API”, which includes guidelines for configuring and utilising ChatGPT

Step 3: Integrate ChatGPT API with Flask Application

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

The flask application we developed in step 1 has to be modified now. To receive ChatGPT’s response to user messages, replace the existing code in your Flask app with the following code.

import slack
import os, signal
from flask import request
from flask import Flask
from slackeventsapi import SlackEventAdapter
import openai

openai.api_key = '<YOUR OPENAI API KEY>'

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')
                completion = openai.ChatCompletion.create(
                        {"role": "user", "content": text}]
                response = completion['choices'][0]['message']['content']
                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 the ngrok on terminal: ngrok http 5000

Step 4: Test Slack Chatbot

To receive the ChatGPT-generated response, kindly send some messages to the Slack bot. On a server, you will also receive a response.

Here is the ChatGPT response on our server.

We will get the below response on our Slack Bot.

Do let us know if you face any issues in setting up or using the script. We would be happy to help! Contact us or post your query 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 blog post series where we have provided a tutorial on how to create a chatbot for different platforms. You can explore these blogs and learn how you can set different kinds of rich responses which can increase user engagement on your chatbot.

Telegram: Create Telegram Bot Using Python Tutorial With Examples

Facebook Messanger: Create Facebook Messenger Bot Using Python Tutorial With Examples

Slack: Create Slack Bot Using Python Tutorial With Examples

Discord: Create Discord Bot Using Python Tutorial With Examples

Dialogflow ES API: How To Integrate Dialogflow ES API To Add NLP Capabilities In Your Chatbot?

Dialogflow CX API: How to integrate Dialogflow CX API to add NLP capabilities in your Chatbot?

Dialogflow ES with Twilio: Setup Twilio Integration On Your Server To Connect Google Dialogflow ES

Categories: Chatbots Development ChatGPT Natural Language Processing NLP Python Slack bot

Leave a Reply

Your email address will not be published.

You may use these <abbr title="HyperText Markup Language">HTML</abbr> tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>