Implement AI Host functionality with model caching and job management

- Added ai_host.py to handle AI tasks with FastAPI integration.
- Introduced HostState and ModelCache classes for managing client connections and model loading.
- Implemented job submission and cancellation endpoints in the AI host.
- Enhanced tests for AI host functionality, including client tracking and job cancellation.
- Updated existing tests to accommodate changes in the operator and command structure.
- Refactored runtime commands to use request-based architecture instead of command-line arguments.
- Improved model loading logic to handle CUDA memory management and reuse models efficiently.

src/snapform/blender_manifest.toml

@@ -12,7 +12,7 @@ platforms = ["windows-x64"]
 license = ["SPDX:GPL-3.0-or-later"]
 
 [permissions]
-network = "Download DA3 runtime dependencies and model weights"
+network = "Access the local AI Host and download runtime dependencies and model weights"
 files = "Read source images and store runtime data"
 
 [build]