Prepare web content for Amazon Bedrock Knowledge Bases with Crawl4AI
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This article outlines a method for preparing web content for Amazon Bedrock Knowledge Bases using Crawl4AI, an open-source Python crawler. While the native Amazon Bedrock Web Crawler is suitable for most public websites, this custom approach offers greater control over content extraction and metadata attachment. The solution employs a scheduled AWS Fargate task to crawl authorized sites, generating Markdown files and JSON metadata sidecars that are uploaded to Amazon S3. These prepared documents are then ingested into the knowledge base, where Amazon Bedrock handles parsing, chunking, embedding, and indexing. The workflow supports bounded crawling strategies and allows for custom metadata filtering to improve retrieval precision. Authors emphasize the importance of validating retrieval quality and implementing Responsible AI guardrails before production deployment. Finally, the guide provides detailed instructions for deploying the infrastructure via AWS CDK and cleaning up resources to avoid unnecessary charges.
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