The video discusses using Crawl for AI, an open-source web crawler and scraper optimized for LLMs, which is particularly fast and deployable via Docker.
Key Steps:
Installation & Quick Start
The installation and quick start guide on crawlforai.com provides essential setup information.
First Crawl
Example code to run a first crawl:
python 01_first_crawl
Showcases how to scrape a URL in about 0.9 seconds.
Sequential Crawling
Example of using a for loop to crawl multiple URLs sequentially:
python 02_sequential
Demonstrates iterating over URLs efficiently.
Parallel Crawling
Describes using the async feature to crawl multiple URLs in parallel, significantly speeding up the process.
Example of crawling 73 URLs in under 30 seconds, compared to sequential crawling which took much longer.
Custom Tool Integration
Explains how to integrate the crawler with an AI agent for enhanced processing of scraped data.
Discusses creating a custom tool using the sitemap URL to streamline crawling efforts and summarize results.
Conclusion
The crawler is versatile, allows for memory management and rate limits, and is efficient for LM tasks.