- Introduced `onnx_moge2.py` for MoGe-2 ONNX inference with NumPy post-processing.
- Added `onnx_ben2.py` for BEN2 ONNX inference with Pillow and NumPy preprocessing.
- Created `onnx_da3.py` for Depth Anything 3 inference with ONNX Runtime and NumPy.
- Implemented shared ONNX Runtime session helpers in `onnx_runtime.py`.
- Developed unit tests for server functionalities in `test_server.py`, including model caching and job management.
- Enhanced job server to handle frame extraction without requiring models.
- Implement JobClient for handling HTTP requests to the JobServer.
- Create ModalJobOperatorBase for managing Blender job lifecycle.
- Introduce JobContext and JobServer for job management and state handling.
- Add ServiceConnection and ServiceController for managing service processes.
- Implement job submission, cancellation, and resource management endpoints in the server.
- Ensure proper error handling and job state updates throughout the service.
- Created development.md for development setup and licensing information.
- Added features.md detailing functionalities and usage instructions for developers and users.
- Introduced index.md to serve as a navigation hub for the documentation.
- Developed outputs.md to explain output formats and their specifications.
- Established service.md to describe the AI Service architecture and environment setup.
- Created surface.md to outline the process of converting Image Empty to perspective meshes.
