* Run tests
* Run tests
* Run tests
* Run tests
* Added rebuild
* Added files for e2e tests
* Added rebuild
* Added rebuild
* Added biuld TensorRT flag
* Changed to use NumPy 1.x for Jetson
* Make universal invocation
* Make Cython constans
* Changed to prepare onnx
* Changed smoke-test to wait AI conversion
* Added step for model conversion
* Changed to not run step in parallel
* Push model to docker registry
* Push model to docker registry
* Push model to docker registry
- Introduced `AIAvailabilityStatus` class to manage the availability status of AI models, including methods for setting status and logging messages.
- Added `AIRecognitionConfig` class to encapsulate configuration parameters for AI recognition, with a static method for creating instances from dictionaries.
- Implemented enums for AI availability states to enhance clarity and maintainability.
- Updated related Cython files to support the new classes and ensure proper type handling.
These changes aim to improve the structure and functionality of the AI model management system, facilitating better status tracking and configuration handling.
Roman Meshko