GPT-4 Vision API + Puppeteer = Easy Web Scraping

The paragraph introduces an experiment with the new Chatbot GPT Vision API in conjunction with a previously created Puppeteer GPT project. The main challenge discussed is scraping information from websites efficiently, as simply taking HTML can lead to wasted tokens and misunderstandings due to hidden elements. The introduction of Chatbot GPT Vision API is seen as a potential solution to provide information about what is visible on the page. The paragraph outlines the initial steps to use the Chatbot GPT Vision API, including writing boilerplate code and setting up the environment with the necessary imports and model configuration.

This paragraph delves into the specifics of using the Chatbot GPT Vision API with image data. It describes the process of sending an image URL to the API and the required format for the request, including base64 encoding of the image data. The paragraph also discusses creating a function to generate the base64 image and the structure of the message to be sent to the model. An example is provided, demonstrating the use of the API with an image from unsplash.com and the resulting description generated by the API.

The focus of this paragraph is on integrating Puppeteer for taking screenshots of websites and analyzing them with the Chatbot GPT Vision API. It details the process of installing Puppeteer and using it to navigate to a specific URL, take a screenshot, and save the image. The paragraph then explores sending the screenshot to the Chatbot GPT Vision API to extract information, such as the age of Sam Altman from a Wikipedia page. It also discusses the limitations encountered when trying to extract specific data from the screenshots and the need for further refinement of the process.

This paragraph discusses enhancing web crawling by combining Chatbot GPT Vision with Puppeteer. It explores the idea of creating a script that takes a user prompt, fetches a URL, takes a screenshot of the page, and then uses the Chatbot GPT Vision API to extract and answer information based on the screenshot. The paragraph outlines the steps to set up such a script, including handling user input, taking screenshots, converting images to base64, and sending data to the API. It also touches on potential improvements and the need for error handling and retry mechanisms.

The paragraph is centered around debugging and refining the web crawling script that utilizes Chatbot GPT Vision API and Puppeteer. It highlights the challenges faced, such as errors in the process, the need for correct import statements, and issues with the API getting stuck. The paragraph describes attempts to solve these issues by adjusting the script, including setting appropriate wait times for page loading, handling errors, and ensuring the correct URL is used for screenshots. It emphasizes the iterative nature of refining the script for better performance.

This paragraph describes the final steps in finalizing the web crawling and information extraction process using Chatbot GPT Vision API and Puppeteer. It covers the successful taking of screenshots, sending them to the API, and receiving answers to queries such as weather updates and stock prices. The paragraph also discusses the importance of error handling, the need to update system messages for better responses, and the potential for automating the process. The video concludes with a summary of the progress made and an invitation for feedback on further improvements.