The architecture deploys Crawl4AI as a scheduled Amazon ECS task on AWS Fargate using Amazon EventBridge. The crawler converts web pages into structured Markdown documents and creates metadata sidecars before uploading them to Amazon S3. Once stored, Amazon Bedrock Knowledge Bases initiates an ingestion job to handle the parsing, chunking, embedding, and indexing phases. This solution supports both managed and customer-managed knowledge bases that utilize Amazon S3 data sources.
Key points
Custom crawling pipelines allow teams to attach detailed metadata required for downstream…: Custom crawling pipelines allow teams to attach detailed metadata required for downstream filtered retrieval.
Amazon Bedrock Knowledge Bases manages data ingestion, chunking, embedding, and storage o…: Amazon Bedrock Knowledge Bases manages data ingestion, chunking, embedding, and storage once prepared files reach Amazon S3.
The preparation framework works with both managed and customer-managed knowledge bases co…: The preparation framework works with both managed and customer-managed knowledge bases connected to S3 data sources.
Sources checked by our analysis pipeline: 1
Artificial Intelligence
Prepare web content for Amazon Bedrock Knowledge Bases with Crawl4AI
When you build Retrieval Augmented Generation (RAG) applications, answer quality depends on the data that you ingest. Amazon Bedrock Knowledge Bases is the fully managed RAG capability of Amazon Bedrock. With Amazon Bedrock Managed Knowledge Base, you connect your data sources, and Amazon Bedrock manages ingestion, storage, indexing, and retrieval for you. You don’t provision or scale a vector store, and embedding and reranking use service-managed models by default.
For web content, start with the Amazon Bedrock Web Crawler data source connector for managed knowledge bases. You give it the seed URLs or sitemaps that you’re authorized to crawl, and it crawls within the scope and rate limits that you set. Scheduled syncs keep your knowledge base current as pages change, and the connector can wait for content that loads with JavaScript. There’s no crawler for you to build, host, or operate, so this connector is the starting point for most public website content.
Some sources need more control over what reaches the knowledge base. You might want…
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