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Amazon Bedrock AgentCore Introduces Dataset Management for Agent Evaluation
Amazon Bedrock AgentCore now includes dataset management to improve agent evaluation, allowing versioned test scenarios with stable inputs and ground truth assertions.
Amazon Bedrock AgentCore now includes dataset management to enhance agent evaluation processes. The feature enables users to create and maintain versioned test scenarios that provide stable inputs and ground truth assertions. By treating test cases as datasets, developers can ensure consistent measurement across evaluations, which is crucial for determining if an agent's improvements are genuine. This approach allows for both predefined scenarios and user simulation scenarios, catering to different evaluation needs. The system supports predefined scenarios where specific inputs and expected outputs are defined, and user simulation scenarios where interactions are generated based on user personas. This method helps in capturing real-world interactions and ensuring that the agent's responses meet the required standards. The integration of dataset management in Amazon Bedrock AgentCore aims to streamline the evaluation process, making it more efficient and reliable. *Source: [awsml](https://aws.amazon.com/blogs/machine-learning/build-a-test-suite-that-grows-with-your-agent-with-dataset-management-in-amazon-bedrock-agentcore/)*
Viktiga punkter
- Amazon Bedrock AgentCore includes dataset management to improve agent evaluation
- Test scenarios are treated as datasets with stable inputs and ground truth assertions
- Predefined scenarios define specific inputs and expected outputs
- User simulation scenarios generate interactions based on user personas
- Dataset management helps in capturing real-world interactions
- The system supports both predefined and user simulation scenarios
- Integration of dataset management streamlines the evaluation process