Break the context window barrier with Amazon Bedrock AgentCore
Quick Answer
Amazon Bedrock AgentCore introduces Recursive Language Models (RLM) for processing documents of unlimited length.
Quick Take
This enables persistent working memory for iterative analysis and orchestrates sub- calls in a sandboxed Python environment, enhancing document analysis capabilities significantly.
Key Points
- Implement RLM using Amazon Bedrock AgentCore Code Interpreter and Strands Agents SDK.
- Process documents with no upper limit on context size.
- Use Bedrock AgentCore as persistent memory for iterative analysis.
- Orchestrate sub-LLM calls within a sandboxed Python environment.
Article Excerpt
From source RSS / original summaryIn this post, you will learn how to implement Recursive Language Models (RLM) using Amazon Bedrock AgentCore Code Interpreter and the Strands Agents SDK. By the end, you will know how to process documents of varying lengths, with no upper bound on context size, use Bedrock AgentCore Code Interpreter as persistent working memory for iterative document analysis, and orchestrate sub- (sub-LLM) calls from within a sandboxed Python environment to analyze specific document sections.
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