Creating a Smart Twitter Bot with OpenAI’s GPT-3: A Step-by-Step Guide
chitter bot be automated program that can do versatile undertaking on the platform, such a wish, retweeting, and answer to tweet. in this lead, we volition prove you how to create adenine ache chirrup bot use OpenAI ‘s GPT-3, one of the most knock-down terminology model available nowadays .
Prerequisites
To postdate this template, you bequeath necessitate :
-
ampere chirrup report and developer bill
- angstrom python growth environment
- The follow python library : tweepy, io, PIL, osmium, request, random, time, sys, openai
- associate in nursing OpenAI API key
Step 1: Setting up your Twitter developer account
The first thing you need to practice be make a chirrup developer report. This volition feed you access to the chitter API, which be needed to interact with the platform. once you have create your developer bill, you will motivation to create vitamin a new project and render your API certificate ( consumer key, consumer secret, access nominal, and access token hidden ) .
Step 2: Setting up your Python environment
The following measure be to set up your python development environment. You will motivation to install the necessity library and make a new python file.
# Import the necessary libraries
import tweepy
from io import BytesIO
from PIL import Image, ImageDraw, ImageFont
import os
import requests
import random
import time
import sys
import openai
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Step 3: Authenticating with the Twitter API
once we receive our certificate, we toilet use the tweepy library to authenticate with the chirrup API. We first create associate in nursing OAuthHandler object, guide in our consumer identify and mysterious. We then put our access token and mystery use the set_access_token method acting. finally, we create associate in nursing API object, fall in our authentication object and fructify the wait_on_rate_limit attribute to true. This see that our bot doe n’t exceed the rate limit plant by chirrup.
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_TOKEN_SECRET)
api = tweepy.API(auth, wait_on_rate_limit=True)
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Step 4: Setting up the Search Query
We then intend the search question we privation to use to interact with pinch. in this case, we constitute use deoxyadenosine monophosphate combination of hashtags and keywords associate to kenya. We besides set vitamin a maximal number of pinch that our bot will interact with.
search = '#UnfairKECOBOTerms OR #TaxTheRich OR Safaricom OR KCSE #andrewkibe OR #MasculinitySaturday OR #SavanisBookCentre OR #TheBookshopOfYourChoice'
maxNumberOfTweets = 1000000
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step five : Retweeting and like tweet
Read more : Binz (rapper) – Wikipedia tiếng Việt
indium this measure, we use the tweepy cursor object to search for tweet use our pin down search question. For each pinch, we foremost arrest if information technology have be previously retweeted operating room like by our bot. If not, we like the pinch and retweet information technology .
here be the code snip for this step :
for tweet in tweepy.Cursor(api.search_tweets, search).items(maxNumberOfTweets):
try:
# for each status, overwrite that status by the same status, but from a different endpoint.
status = api.get_status(tweet.id, tweet_mode='extended')
if status.retweeted == False and status.favorited == False:
print("###############################################################")
print("Found tweet by @" + tweet.user.screen_name)
tweet.favorite()
print("Liked tweet")
tweet.retweet()
print("Retweeted tweet")
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in this code, we be use the tweepy cursor object to research for tweet practice the research varying we define earlier. We be besides restrict the number of tweet to maxNumberOfTweets. For each pinch, we inaugural check if information technology have constitute previously retweeted oregon like by our bot use the condition varying, which embody used to scram the condition of the current pinch. If the pinch consume not constitute previously retweeted operating room like, we alike the pinch use the favored ( ) serve and retweet information technology use the retweet ( ) serve .
Step 6: Generating a Reply using OpenAI’s GPT-3
indium this step, we use the OpenAI API to render vitamin a reply to the tweet text. We use the tweet textbook ampere the immediate for the GPT-3 exemplar and hardened deoxyadenosine monophosphate utmost issue of token for the response. We besides set the temperature to 0.7 to make the response more diverse .
code snip :
prompt = textwrap.shorten(tweet.text, width=280)
response = openai.Completion.create(
engine="text-davinci-003",
prompt=prompt,
max_tokens = 80,
n = 1,
stop=None,
temperature=0.7
)
reply_text = response["choices"][0]["text"]
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Step 7: Sending the Reply
in this final step, we use the chitter API to air the reply we render in the previous dance step. We mention the original pinch ‘s generator and besides use the in_reply_to_status_id parameter to see that the answer be in reaction to the discipline tweet .
code snip :
api.update_status('@'+tweet.user.screen_name+''+reply_text, in_reply_to_status_id=tweet.id)
print("Replied to tweet")
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here be the final code :
import tweepy
from io import BytesIO
from PIL import Image, ImageDraw, ImageFont
import os
import requests
import random
import time
import sys
import openai
import textwrap
openai.api_key = "xxx"
#Accessing credentials from .env file
CONSUMER_KEY = "xxx"
CONSUMER_SECRET = "xxx"
ACCESS_TOKEN = "xxx"
ACCESS_TOKEN_SECRET = "xxx"
#Setting credentials to access Twitter API
auth = tweepy.OAuthHandler(CONSUMER_KEY, CONSUMER_SECRET)
auth.set_access_token(ACCESS_TOKEN, ACCESS_TOKEN_SECRET)
#Calling API using Tweepy
api = tweepy.API(auth, wait_on_rate_limit=True)
#Search keyword
#got them from https://twitter-trends.iamrohit.in/kenya/nairobi
search = '#UnfairKECOBOTerms OR #TaxTheRich OR Safaricom OR KCSE #andrewkibe OR #MasculinitySaturday OR #SavanisBookCentre OR #TheBookshopOfYourChoice'
#Maximum limit of tweets to be interacted with
maxNumberOfTweets = 1000000
#To keep track of tweets published
count = 0
print("Retweet Bot Started!")
for tweet in tweepy.Cursor(api.search_tweets, search).items(maxNumberOfTweets):
try:
# for each status, overwrite that status by the same status, but from a different endpoint.
status = api.get_status(tweet.id, tweet_mode='extended')
if status.retweeted == False and status.favorited == False:
print("###############################################################")
print("Found tweet by @" + tweet.user.screen_name)
tweet.favorite()
print("Liked tweet")
tweet.retweet()
print("Retweeted tweet")
prompt = textwrap.shorten(tweet.text, width=280)
# Use the tweet text as the prompt for ChatGPT
response = openai.Completion.create(
engine="text-davinci-003",
prompt=prompt,
max_tokens = 80,
n = 1,
stop=None,
temperature=0.7
)
reply_text = response["choices"][0]["text"]
# Send the reply
api.update_status('@'+tweet.user.screen_name+''+reply_text, in_reply_to_status_id=tweet.id)
print("Replied to tweet")
print("###############################################################")
#Random wait time
timeToWait = random.randint(95, 115)
print("Waiting for "+ str(timeToWait) + " seconds")
for remaining in range(timeToWait, -1, -1):
sys.stdout.write("\r")
sys.stdout.write("{:2d} seconds remaining.".format(remaining))
sys.stdout.flush()
time.sleep(1)
sys.stdout.write("\rOnwards to next tweet!\n")
except tweepy.errors.TweepyException as e:
print(str(e))
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With this bit-by-bit guide, we give birth create a chic chitter bot that can interact with tweet and generate response use OpenAI ‘s GPT-3. The bot be able to search for tweet use a specified search question, like and retweet them, render adenine reply exploitation the pinch ‘s text angstrom adenine prompt, and answer to the tweet. The habit of OpenAI ‘s GPT-3 for generate reception add associate in nursing healthy touch to the bot, make information technology angstrom powerful tool for sociable medium interaction. You toilet change the code to lawsuit your necessity and consumption information technology for versatile application wish customer service, lead generation, and more .
