Time for Learning: 20-30 minutes to set up the vision-based scraper.
Summary
This tutorial demonstrates how to use GPT-4's vision capabilities to perform web scraping by interpreting and extracting data from screenshots. By combining tools like Make.com and Scraping Bee, the process involves taking screenshots of web pages, analyzing the content using GPT-4, and saving the extracted data into a spreadsheet. The video focuses on setting up the scraper to gather key information from LinkedIn company profiles, such as company name, followers, employees, and website. This vision-based approach bypasses traditional scraping barriers, making it a versatile solution for extracting web data without coding experience.
Bear’s take
This example is a great demonstration of using GPT-4.0 to scrape web data by taking screenshots, analyzing the content, and saving it to a spreadsheet. Using Make.com for this process is particularly helpful for those without coding experience. I found it especially useful for simplifying complex data extraction tasks, and I'll definitely be trying it out for my own projects.
What you’ll learn
You’ll learn how to set up a vision-based web scraper using GPT-4 and Make.com. The video guides you through creating a new scenario in Make.com, setting up a spreadsheet to watch for new rows, and using Scraping Bee to take screenshots of web pages. You'll see how to handle cookies for authenticated sessions and how to configure GPT-4 to analyze the screenshot and extract specific data points. The tutorial also covers encoding images in base64 format for GPT-4 processing and parsing the extracted data to populate a Google Sheet. This method provides an efficient way to scrape web data while overcoming traditional barriers.
Key steps
Set Up Make.com Scenario: Create a new scenario in Make.com for the vision-based scraper.
Connect Spreadsheet: Link your Google Sheet to Make.com to store the scraped data.
Use Scraping Bee: Set up Scraping Bee to take screenshots of web pages.
Handle Cookies: Capture and use cookies to bypass login screens for authenticated sessions.
Encode Images: Convert screenshots to base64 format for GPT-4 processing.
Analyze with GPT-4: Configure GPT-4 to analyze the screenshot and extract specified data points.
Parse and Save Data: Parse the extracted data and update the Google Sheet with the results.
Next step
Experiment with different web pages to see how GPT-4 Vision can extract various types of data.
Explore additional features of Make.com and GPT-4 to enhance your web scraping projects.
Consider using this method for data collection tasks in your personal or professional projects.