Crawl4AI

Overview

Crawl4AI is the open-source answer to web data extraction for AI. It crawls websites, renders JavaScript, extracts clean content, and outputs LLM-ready formats — all without API keys or usage limits. Built-in chunking strategies make it ideal for RAG pipelines.

How It Works

1. Install — pip install crawl4ai
2. Configure — Set extraction strategy and output format
3. Crawl — Process single pages or entire sites
4. Extract — Get clean markdown, structured data, or chunked content

Use Cases

• RAG data ingestion — Convert websites to embeddable chunks
• Documentation indexing — Index entire documentation sites
• Content aggregation — Gather content from multiple sources
• Knowledge bases — Build AI knowledge bases from web content

Getting Started

from crawl4ai import AsyncWebCrawler

async with AsyncWebCrawler() as crawler:
    result = await crawler.arun(url="https://example.com")
    print(result.markdown)

Example

from crawl4ai.extraction_strategy import LLMExtractionStrategy

strategy = LLMExtractionStrategy(
    instruction="Extract all product names and prices"
)
async with AsyncWebCrawler() as crawler:
    result = await crawler.arun(url="https://shop.example.com", extraction_strategy=strategy)

Alternatives

• Firecrawl — Managed web data API (faster, paid)
• Scrapling — Anti-bot focused scraping
• Beautiful Soup — Traditional HTML parsing (no JS)