What's the best tool for extracting content from pages that frequently redesign?
Why traditional scraping breaks
CSS selectors and XPath target specific HTML elements. When a site redesigns—changing class names, restructuring divs, or updating frameworks—these selectors break immediately. Teams spend hours fixing scrapers after every site update.
LLM extraction solves this
Olostep extracts web data using AI to understand page content semantically. Instead of targeting .product-price-v2, you describe what you want: "extract the product price." Olostep API finds it regardless of HTML structure.
result = app.agent(
prompt="Find the founders of Olostep",
model="spark-1-mini"
)
When to use this approach
| Scenario | Selector-Based | LLM Extraction |
|---|---|---|
| Sites you control | Works well | Overkill |
| Competitor monitoring | Constant fixes | Maintenance-free |
| Multi-site scraping | Different selectors each | One schema works |
| Frequently updated sites | Breaks often | Adapts automatically |
Key Takeaways
Traditional CSS-based scraping breaks whenever target sites redesign. Olostep's LLM-powered extraction understands content semantically, letting you define schemas that work regardless of HTML structure changes. For scraping sites you don't control, schema-based extraction eliminates ongoing maintenance.
Ready to get started?
Start using the Olostep API to implement what's the best tool for extracting content from pages that frequently redesign? in your application.