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a place to put my final projects to look back on and study,

just a little home for some of my assignments as a backlog.

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assignments's Issues

Another idea

For techheadz.xyz header

.pixel {
  position: absolute;
  display: block;
  width: 10px;
  height: 10px;
  background-color: #333;
  animation: raining 2s infinite;
}

.dancing-headline {
  position: absolute;
  top: 50%;
  left: 50%;
  transform: translate(-50%, -50%);
  font-size: 48px;
  font-weight: bold;
  color: #333;
  animation: dancingHeadline 2s infinite;
}

@keyframes raining {
  0% {
    transform: translateY(-20px) rotate(0deg);
    opacity: 0;
  }
  50% {
    opacity: 1;
  }
  100% {
    transform: translateY(100vh) rotate(360deg);
    opacity: 0;
  }
}

@keyframes dancingHeadline {
  0% {
    transform: translate(-50%, -50%) rotate(0deg);
  }
  25% {
    transform: translate(-50%, -50%) rotate(-10deg);
  }
  50% {
    transform: translate(-50%, -50%) rotate(10deg);
  }
  75% {
    transform: translate(-50%, -50%) rotate(-5deg);
  }
  100% {
    transform: translate(-50%, -50%) rotate(0deg);
  }
}

</style>

<h1 class="dancing-headline">
  TechHeadz.xyz
</h1>

Idea for automating techheadz.xyz

Might offer advertising on the website... and have my tweets also make a blog post on techheadz

So i just have to feed it 12 papers a day.

Heres an automated template of my idea

import requests
from bs4 import BeautifulSoup
import re
import openai
import tweepy
import time

# Set up OpenAI API credentials
openai.api_key = 'YOUR_API_KEY'

# Twitter API credentials
consumer_key = 'YOUR_CONSUMER_KEY'
consumer_secret = 'YOUR_CONSUMER_SECRET'
access_token = 'YOUR_ACCESS_TOKEN'
access_token_secret = 'YOUR_ACCESS_TOKEN_SECRET'

# List of paper links
paper_links = [
    'https://example.com/paper1',
    'https://example.com/paper2',
    # Add more paper links here
]

# Function to scrape relevant content from a given paper link
def scrape_paper_content(link):
    response = requests.get(link)
    html_content = response.text
    
    soup = BeautifulSoup(html_content, 'html.parser')
    
    # Extract relevant content using appropriate selectors
    title = soup.find('h1').text.strip()
    abstract = soup.find('div', class_='abstract').text.strip()
    paper_text = soup.find('div', class_='paper-text').text.strip()
    
    # Preprocess the text
    title = re.sub('\n+', ' ', title)
    abstract = re.sub('\n+', ' ', abstract)
    paper_text = re.sub('\n+', ' ', paper_text)
    
    return title, abstract, paper_text

# Function to generate a tweet for a given paper
def generate_paper_tweet(link):
    title, abstract, paper_text = scrape_paper_content(link)
    
    # Prepare the content to send to the language model
    prompt = f"Title: {title}\n\nAbstract: {abstract}\n\nPaper: {paper_text}"
    response = openai.Completion.create(
        engine='text-davinci-003',
        prompt=prompt,
        max_tokens=279,
        temperature=0.7,
        n=1,
        stop=None
    )
    summary = response.choices[0].text.strip()
    
    # Generate relevant hashtags based on the paper's topic
    hashtags = get_paper_hashtags(title)
    
    # Generate the tweet
    tweet = f"{summary} Read more: {link} {hashtags}"
    return tweet[:279]  # Limit to 279 characters

# Function to generate relevant hashtags based on the paper's topic
def get_paper_hashtags(title):
    # Generate relevant hashtags based on the paper's topic
    # You can customize this function based on your specific requirements
    # Here's an example implementation that generates three hashtags based on the words in the paper title
    words = title.split()
    hashtags = ['#'+word.lower() for word in words if len(word) > 3][:3]
    return ' '.join(hashtags)

# Function to authenticate and post a tweet
def tweet(message):
    auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
    auth.set_access_token(access_token, access_token_secret)
    api = tweepy.API(auth)
    api.update_status(message)

# Main loop
for link in paper_links:
    try:
        tweet_text = generate_paper_tweet(link)
        tweet(tweet_text)
        print("Tweeted:", tweet_text)
    except Exception as e:
        print("Error:", str(e))
    
    time.sleep(2 * 60 * 60)  # Sleep for 2 hours

# Stop the program after iterating through the list
print("Finished processing all paper links. Program stopped.")
``

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