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Crawl4ai
Overview :
Crawl4AI is a powerful, free web crawling service designed to extract valuable information from web pages and make it accessible for large language models (LLMs) and AI applications. It facilitates efficient web crawling, provides LLM-friendly output formats such as JSON, cleaned HTML, and Markdown, supports crawling multiple URLs simultaneously, and is completely free and open-source.
Target Users :
["AI Developers and Data Scientists: Utilize Crawl4AI to quickly gather web data for machine learning model training or data analysis.","Website Administrators and Content Creators: Extract website content via Crawl4AI to optimize SEO or conduct content analysis.","Researchers: Use Crawl4AI to collect and organize relevant data during network information research."]
Use Cases
Using Crawl4AI to extract the latest articles from a news website for content analysis.
Integrating Crawl4AI into an automated system to periodically scrape data from specific web pages.
Utilizing Crawl4AI to provide real-time web information for AI chatbots.
Features
Efficient web crawling capabilities to extract valuable data from websites.
Supports LLM-friendly output formats such as JSON, cleaned HTML, and Markdown.
Supports crawling multiple URLs concurrently.
Can replace media tags with ALT text.
Completely free to use, and the code is open-source.
How to Use
Step 1: Access Crawl4AI's web application or clone the code repository locally.
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Step 2: If using as a library, install Crawl4AI through pip.
Step 3: Set environment variables, including the database path and API key.
Step 4: Import necessary modules in your Python script and create a WebCrawler instance.
Step 5: Define the URLs to be crawled using the UrlModel and call the fetch_page or fetch_pages method for data crawling.
Step 6: Process the crawling results, and extract data in JSON, HTML, or Markdown format as needed.
Step 7: Run a local server (if this deployment method is chosen) and send requests through the API interface to crawl web page data.
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