Build A Twitter Bot With Python Using ChatGPT: Automatically Reply To Mentions In Minutes

by | Jan 25, 2023 | ChatGPT, Coding

Home » Coding » Build A Twitter Bot With Python Using ChatGPT: Automatically Reply To Mentions In Minutes

Introduction of the Project

Through this article, we will learn how to use ChatGPT to build a Twitter bot that automatically replies to mentions in minutes. In this tutorial, we’ll show you step-by-step how to build a Twitter Bot with Python using ChatGPT and also set up your bot and customize it to suit your needs. Whether you’re a business owner or a social media manager, this bot will save you time and help you engage with your audience. So let us get understand.

Steps To Build A Twitter Bot With Python Using ChatGPT

Step 1: Visit https://chat.openai.com/chat/

Step 2: Ask, “Build a Twitter bot that replies every time someone tags me”

You will receive this answer:

To build a Twitter bot that replies whenever someone tags you, you need to use the Twitter API to access your account and monitor for mentions. Here are the basic steps you would need to follow:

  • Create a Twitter developer account and create a new app to obtain the necessary API keys and access tokens.
  • Use a programming language such as Python to access the Twitter API and authenticate using your API keys and access tokens.
  • Use the API to monitor your mentions timeline for new tweets that include your handle.
  • When a new mention is found, extract the text of the tweet and the handle of the person who mentioned you.
  • Use the API to post a reply to the tweet, including the handle of the person who mentioned you.
  • Set up a schedule to run the script at regular intervals (e.g., every 30 minutes) to check for new mentions.

Please note that these are just the basic steps overview, and the actual implementation will require more details and steps. It’s also important to follow Twitter rules and regulations for automating actions on the platform.

Step 3: To understand the steps related to Twitter Developer Access and key generation, ask this “Help me regarding step 1”

You will receive this answer:

The first step of building a Twitter bot involves creating a Twitter developer account and creating a new app to obtain the necessary API keys and access tokens. Here are the specific steps you would need to take:

  • Go to https://developer.twitter.com/en/apps and log in with your Twitter account.
  • Click on the “Create an App” button and fill out the form with the required information, including the name and purpose of your app.
  • Agree to the terms of service and click on the “Create” button.
  • Once your app is created, click on the “Keys and Tokens” tab to access your API key and secret.
  • Click on the “Generate” button to create an access token and secret. These will be used to authenticate your bot when it accesses the Twitter API.
  • Make sure to keep the generated tokens and secrets safe, and don’t share them with anyone.

It’s also important to note that if you want to post tweets from your bot, you will have to have a phone number and email address associated with your account.

Please note that Twitter has rules and regulations that must be followed when using the API, and your app may be subject to rate limits or suspended if it does not comply.

With the help of the above steps, we have reached here and generated the keys:

Build A Twitter Bot With Python Using ChatGPT

API Key: 4CHvbNuap7Ioxq1Vg8RdjIo61

API Key Secret: URpZwtWvSCENrStmm4QKm7kS4Wb9tVsabI0VG56KMDSuJCNZhu

Bearer Token: AAAAAAAAAAAAAAAAAAAAAKWnAQEAAAAALicJlVpwmmQJoR7DuYYSzC6759Q%3DmVqBSAfRiR3SufuNX5tT4R5TCebePwV0Wkhe0dFFaiOSukgDcp

Access Token: 193167583-IryIpxKI8K6f5dyjOJr5enaFvDxBOJOVNfJTSlMA

Access Token Secret: IpYHvKIMTpNdfMyC2QCcMRkdtSwCNFR5BTUCEwAk4DIbV

Step 4: Now go to “Settings” and click “User Authentication Settings”:

Build A Twitter Bot With Python Using ChatGPT

And give the given app permissions:

Twitter Developer Portal

With the given App type:

Twitter Developer Portal

Also, set the callback URL (for testing purposes): http://localhost:8000

This should be changed to your API link in case of production. API link will be generated after you deploy the bot to a server and get a link to access the same.

With this, you are done with Twitter Developer Access.

Step 5: To get the Python code to build the Twitter bot, ask this question ‘’ help me regarding step 2”

You will get instructions to install some libraries as mentioned below:

The second step of building a Twitter bot involves using a programming language such as Python to access the Twitter API and authenticate using your API keys and access tokens. Here are the specific steps you would need to take:

  • Install a Python library for accessing the Twitter API, such as tweepy or python-twitter. You can install these libraries by running pip install tweepy or pip install python-twitter, respectively.
  • Import the library and authenticate using your API keys and access tokens. For example, using tweepy:
import tweepy
# Authenticate using your API keys and access tokens
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_TOKEN_SECRET)
# Create an API object
api = tweepy.API(auth)
  • Verify that you have successfully authenticated by making a test API call, such as api.verify_credentials().
  • Use the API object to access the Twitter API and make calls to the relevant endpoints. For example, to get a list of your mentions, you can use the api.mentions_timeline() method.
  • You can check the documentation of the library you are using to find the methods available to access the Twitter API and see the expected inputs and outputs.

It’s important to ensure that you are using the endpoints that are allowed by Twitter according to your app’s permission level. Also, please remember that there are rate limits on the number of requests you can make to the API, so your script should be designed to handle errors gracefully when rate limits are exceeded.

Step 6: Now ask the ChatGPT for the full code by asking, “give me the full code of python altogether”. You will get this reply:

Source Code

import tweepy
# Authenticate using your API keys and access tokens
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_TOKEN_SECRET)
# Create an API object
api = tweepy.API(auth)
# Verify that you have successfully authenticated
try:
api.verify_credentials()
print("Authentication OK")
except:
print("Error during authentication")
# Function to reply to mentions
def reply_to_mentions():
# Get the mentions timeline
mentions = api.mentions_timeline()
# Iterate through the mentions
for mention in mentions:
# Extract the text and handle of the mention
text = mention.text
handle = mention.user.screen_name
# Prepare the reply text
reply_text = f"@{handle} Thanks for mentioning me!"
# Send the reply
api.update_status(reply_text, in_reply_to_status_id=mention.id)
print(f"Replied to mention from @{handle}: {text}")
# Call the function to reply to mentions
reply_to_mentions()
In the above code, change the CONSUMER_KEY with API Key and CONSUMER_SECRET with API Key Secret
Also, change Access Token and Access Token Secret as shown below:
import tweepy
# Authenticate using your API keys and access tokens
auth = tweepy.OAuthHandler('4CHvbNuap7Ioxq1Vg8RdjIo61', 'URpZwtWvSCENrStmm4QKm7kS4Wb9tVsabI0VG56KMDSuJCNZhu')
auth.set_access_token('193167583-IryIpxKI8K6f5dyjOJr5enaFvDxBOJOVNfJTSlMA', 'IpYHvKIMTpNdfMyC2QCcMRkdtSwCNFR5BTUCEwAk4DIbV')
# Create an API object
api = tweepy.API(auth)
# Verify that you have successfully authenticated
try:
api.verify_credentials()
print("Authentication OK")
except:
print("Error during authentication")
# Function to reply to mentions
def reply_to_mentions():
# Get the mentions timeline
mentions = api.mentions_timeline()
# Iterate through the mentions
for mention in mentions:
# Extract the text and handle of the mention
text = mention.text
handle = mention.user.screen_name
# Prepare the reply text
reply_text = f"@{handle} Thanks for mentioning me!"
# Send the reply
api.update_status(reply_text, in_reply_to_status_id=mention.id)
print(f"Replied to mention from @{handle}: {text}")
# Call the function to reply to mentions
reply_to_mentions()

Step 7: Run the code

You can run the above Python script using the command line or an IDE (Integrated Development Environment).

Using the command line:

  • Open the command prompt or terminal on your computer.
  • Navigate to the directory where the script is located using the cd command.
  • Run the script using the command python script_name.py, where script_name.py is the name of your script.
  • Now, this will generate an error, as no new mentions will be there to detect. Something like this:

But Authentication will be OK.

Output

To test the bot, the first comment by mentioning yourself via a different Twitter account, as shown below:

Twitter bot with ChatGPT

Now, run the python file again. You will see the above tweet, and an automatic reply will be sent as below:

You can see the reply on Twitter as shown below:

Build A Twitter Bot With Python Using ChatGPT

Key Points To Remember

  • Use the Python programming language and the Tweepy library to interact with the Twitter API.
  • Use the OpenAI’s ChatGPT model to generate text.
  • Authenticate your bot with a Twitter developer account and create a Twitter application.
  • Use the Twitter API to automate tweets, respond to mentions, and perform other actions on behalf of your bot.
  • Consider using a hosting service to run your bot continuously.
  • Test your bot and ensure it is functioning as expected before releasing it to the public.
  • Implement error handling to prevent your bot from crashing or behaving unexpectedly.
  • Monitor and maintain your bot regularly to ensure it continues to function correctly.
  • Adjust the parameters and settings of the ChatGPT model to fine-tune the output of your bot.
  • Consider the ethical and legal implications of creating a bot and ensure you are following any relevant regulations and guidelines.

We hope that all the steps to build a Twitter Bot with Python using ChatGPT were easy to understand. You can try working on this project on your own now and if you face any errors or doubts. Kindly drop a comment, and we will resolve your queries ASAP.

 

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