interface EvaluatorInferenceConfig 🔹

Language	Type name
.NET	`Amazon.CDK.AWS.Bedrock.Agentcore.Alpha.EvaluatorInferenceConfig`
Go	`github.com/aws/aws-cdk-go/awsbedrockagentcorealpha/v2#EvaluatorInferenceConfig`
Java	`software.amazon.awscdk.services.bedrock.agentcore.alpha.EvaluatorInferenceConfig`
Python	`aws_cdk.aws_bedrock_agentcore_alpha.EvaluatorInferenceConfig`
TypeScript (source)	`@aws-cdk/aws-bedrock-agentcore-alpha` » `EvaluatorInferenceConfig`

Inference configuration for a custom LLM-as-a-Judge evaluator.

Controls how the foundation model generates evaluation responses.

Example

// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import * as bedrock_agentcore_alpha from '@aws-cdk/aws-bedrock-agentcore-alpha';
const evaluatorInferenceConfig: bedrock_agentcore_alpha.EvaluatorInferenceConfig = {
  maxTokens: 123,
  temperature: 123,
  topP: 123,
};

Properties

Name	Type	Description
maxTokens?🔹	`number`	The maximum number of tokens to generate in the model response.
temperature?🔹	`number`	The temperature value that controls randomness in the model's responses.
topP?🔹	`number`	The top-p sampling parameter that controls the diversity of the model's responses.

maxTokens?🔹

Type: number (optional, default: The foundation model's default maximum token limit is used)

The maximum number of tokens to generate in the model response.

temperature?🔹

Type: number (optional, default: The foundation model's default temperature is used)

The temperature value that controls randomness in the model's responses.

Higher values produce more diverse outputs. Range: 0.0 to 1.0.

topP?🔹

Type: number (optional, default: The foundation model's default top-p value is used)

The top-p sampling parameter that controls the diversity of the model's responses.

Range: 0.0 to 1.0.

AWS CDK