Testing Framework

Comprehensive tools for validating your AI model deployments.

Overview

Centrify's testing framework provides a comprehensive set of tools for validating your AI model deployments. These tools help ensure that your models meet your requirements for functionality, performance, safety, and reliability.

Key Components

• Test Runner: Execute test cases against your deployed models in a controlled environment.
• Assertion Library: Define expected behaviors and validate model outputs against them.
• Test Data Management: Organize and manage test inputs and expected outputs.
• Reporting Tools: Generate detailed reports on test results and model performance.

Testing Capabilities

• Functional Testing: Verify that your models produce the expected outputs for given inputs.
• Performance Testing: Measure latency, throughput, and resource utilization under various conditions.
• Safety Testing: Validate that your content filters and other guardrails are working as expected.
• Regression Testing: Ensure that new versions of your models maintain or improve upon the behavior of previous versions.

Getting Started

To start using Centrify's testing framework, navigate to the Testing Framework section in your project dashboard. From there, you can create test cases, organize them into test suites, and run them against your deployed models.