| ID | +Name | +Category | +Type | +Rating | +Downloads | +Status | +Actions | +
|---|---|---|---|---|---|---|---|
| ${app.id} | +${app.name} | +${app.category} | +${app.type} | +โ ${app.rating}/5 | +${this.formatNumber(app.downloads)} | ++ ${app.featured ? 'Featured' : ''} + ${app.sponsored ? 'Sponsored' : ''} + | +
+
+
+
+
+
+ |
+
| ID | +Title | +Category | +Author | +Published | +Views | +Actions | +
|---|---|---|---|---|---|---|
| ${article.id} | +${article.title} | +${article.category} | +${article.author} | +${new Date(article.published_date).toLocaleDateString()} | +${this.formatNumber(article.views)} | +
+
+
+
+
+
+ |
+
| Order | +Icon | +Name | +Description | +Actions | +
|---|---|---|---|---|
| ${cat.order_index} | +${cat.icon} | +${cat.name} | +${cat.description} | +
+
+
+
+
+ |
+
| ID | +Company | +Tier | +Start | +End | +Status | +Actions | +
|---|---|---|---|---|---|---|
| ${sponsor.id} | +${sponsor.company_name} | +${sponsor.tier} | +${new Date(sponsor.start_date).toLocaleDateString()} | +${new Date(sponsor.end_date).toLocaleDateString()} | +${sponsor.active ? 'Active' : 'Inactive'} | +
+
+
+
+
+ |
+
+
+ App description goes here
+ +Get started with this integration in just a few steps.
+ +pip install crawl4aifrom crawl4ai import AsyncWebCrawler
+
+async def main():
+ async with AsyncWebCrawler() as crawler:
+ result = await crawler.arun(
+ url="https://example.com",
+ # Your configuration here
+ )
+ print(result.markdown)
+
+if __name__ == "__main__":
+ import asyncio
+ asyncio.run(main())Customize the crawler with these advanced options:
+ +Optimize crawling speed with parallel processing and caching strategies.
+Handle login forms, cookies, and session management automatically.
+Use CSS selectors, XPath, or AI-powered content extraction.
+Rotate proxies and bypass rate limiting with built-in proxy management.
+from crawl4ai import AsyncWebCrawler
+from crawl4ai.extraction_strategy import LLMExtractionStrategy
+
+async def extract_with_llm():
+ async with AsyncWebCrawler() as crawler:
+ result = await crawler.arun(
+ url="https://example.com",
+ extraction_strategy=LLMExtractionStrategy(
+ provider="openai",
+ api_key="your-api-key",
+ instruction="Extract product information"
+ ),
+ bypass_cache=True
+ )
+ return result.extracted_content
+
+# Run the extraction
+data = await extract_with_llm()
+print(data)Use the bypass_cache=True parameter when you need fresh data, or set cache_mode="write" to update the cache with new content.
Complete documentation and API reference.
+ +Real-world examples and use cases.
+ +contact@example.com
+Found a bug? Report it on GitHub Issues.
+Join our Discord for help and discussions.
+
+ Tools, Integrations & Resources for Web Crawling
+${hero.description}
+ +${(app.description || '').substring(0, 100)}...
+ +