AI Optimizing Your Website - Open Interpreter - Real Business Use Case



AI Summary

Summary: AI Optimization of a Website Using Open Interpreter

  • Introduction:
    • Open Interpreter is a versatile framework for running LLM codes, adjusting files, and browsing the internet.
    • The goal is to optimize a website built with WordPress that has not been maintained for a while.
  • Image Compression:
    • Open Interpreter was used to compress and convert the first five images on the website to WebP format.
    • Python libraries like requests, BeautifulSoup, and Pillow were utilized.
    • Images were renamed to include the amount of kilobytes reduced during compression.
  • Internal Link Checking:
    • Open Interpreter found all internal links and buttons on the homepage.
    • An Excel file was created with three columns: link type, text, and destination.
  • Speed Testing:
    • Open Interpreter measured the page loading time for pages linked on the homepage.
    • Results were saved in an Excel file with links and their corresponding loading times.
  • Results & Cost:
    • The process was fast and efficient, providing valuable data for website optimization.
    • The entire optimization process cost around $2 and took about 20 minutes.
  • Conclusion:
    • Open Interpreter simplifies the use of BeautifulSoup for website scraping and optimization.
    • The AI performed tasks with minimal input and high precision, proving to be a cost-effective solution.
  • Call to Action:
    • Viewers are encouraged to ask questions in the comments, like the video, and subscribe for more content on automation.