Summary
The video introduces the concept of web scraping using the llms library Crawl for AI, focusing on extracting structured information like pricing data into a JSON object for dynamic updates. It covers installation instructions for the library and explains asynchronous and synchronous modes. The demonstration showcases the effectiveness of using Open AI models for extraction and the importance of schema extraction in crawling and scraping content. The speaker emphasizes the avoidance of manual methods like Beautiful Soup and showcases data extraction and analysis from websites like Gemini API. Finally, a demonstration is provided on structuring player information into a JSON format for easy organization and accessibility.
Introduction to Web Scraping
This chapter introduces the concept of web scraping and extracting structured information using llms library called Crawl for AI.
Demo Setup
The speaker mentions that the demo is based on code from a GitHub repository example, explaining the goal of extracting pricing information into a JSON object for dynamic updates.
Installing Crawl for AI Library
Instructions are provided on installing the Crawl for AI library and its dependencies with details on asynchronous and synchronous modes.
Using Open AI Models
The chapter covers using Open AI models for extraction, including setting up input and output fees and describing the information extracted.
Web Content Extraction
Explanation on utilizing llm for crawling and scraping content, mentioning the importance of schema extraction and avoiding manual methods like Beautiful Soup.
Data Extraction Demonstration
Demonstration of extracting and analyzing data from various websites like Gemini API, showcasing the effectiveness of the scraping process.
Structuring Data
The speaker demonstrates structuring data extracted from a website, organizing player information like name, ELO score, and number of games played into a JSON format.
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