Use decision models with Amazon Bedrock AgentCore Evaluations
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This article explains how to integrate decision models into Amazon Bedrock AgentCore Evaluations using custom code-based evaluators. Decision models provide calibrated probabilities for fixed-choice questions, offering a reliable alternative to free-form LLM outputs for narrow evaluation tasks. The post demonstrates connecting two specific backends, Jev and Strands Decider 2B, to assess agent responses through Lambda functions. These models support yes/no, choice, and score question types, enabling precise thresholding and aggregation of results. The authors recommend using decision models as a screening layer that flags turns requiring deeper investigation by built-in LLM-as-a-judge evaluators. A validation process is outlined to ensure these new measurements align with human reference labels before deployment. This approach allows developers to maintain broad assessment capabilities while adding efficient, deterministic checks for specific policy or factual adherence.
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