Version updated for https://github.com/CopilotKit/aimock to version v1.14.3. This action is used across all versions by 21 repositories. Action Type This is a Composite action. Go to the GitHub Marketplace to find the latest changes. Action Summary The aimock GitHub Action provides a comprehensive mocking framework for testing AI applications by simulating interactions with various APIs and services, including LLMs, multimedia tools, vector databases, and agent protocols. It automates the testing process by enabling deterministic mock responses, chaos testing, drift detection, and streaming simulations, eliminating the need for actual API dependencies. This tool is ideal for developers seeking to validate AI workflows efficiently and reliably in both local and CI/CD environments.

Version updated for https://github.com/CopilotKit/aimock to version v1.14.0. This action is used across all versions by 7 repositories. Action Type This is a Composite action. Go to the GitHub Marketplace to find the latest changes. Action Summary The aimock GitHub Action provides a comprehensive framework for mocking and testing AI applications by simulating various AI-related APIs, protocols, and services, such as LLMs, multimedia APIs, vector databases, and agent-to-agent communication. It streamlines testing by enabling deterministic response playback, chaos testing, and drift detection, while supporting integration with CI/CD pipelines and test frameworks. This action is designed to simplify the development and validation of AI applications by offering a unified, dependency-free, and configurable testing environment.

Version updated for https://github.com/CopilotKit/aimock to version v1.13.0. This action is used across all versions by 6 repositories. Action Type This is a Composite action. Go to the GitHub Marketplace to find the latest changes. Action Summary The aimock GitHub Action provides a comprehensive mocking framework for testing AI applications by simulating various AI-related services and protocols, such as LLM APIs, multimedia processing, vector databases, and agent-to-agent interactions. It automates the creation of controlled testing environments, enabling deterministic responses, chaos testing, drift detection, and real-time protocol simulation, all while running on a single port with zero dependencies. This action simplifies and enhances the testing process by offering extensive support for recording/replaying API interactions, customizable streaming behavior, and integration with CI/CD pipelines.