Refactor inference and AI configuration handling

- Updated the `Inference` class to replace the `get_onnx_engine_bytes` method with `download_model`, allowing for dynamic model loading based on a specified filename.
- Modified the `convert_and_upload_model` method to accept `source_bytes` instead of `onnx_engine_bytes`, enhancing flexibility in model conversion.
- Introduced a new property `engine_name` to the `Inference` class for better access to engine details.
- Adjusted the `AIRecognitionConfig` structure to include a new method pointer `from_dict`, improving configuration handling.
- Updated various test cases to reflect changes in model paths and timeout settings, ensuring consistency and reliability in testing.

engines/inference_engine.pyx

@@ -11,8 +11,12 @@ cdef class InferenceEngine:
         return None
 
     @staticmethod
-    def convert_from_onnx(bytes onnx_bytes):
-        return onnx_bytes
+    def get_source_filename():
+        return None
+
+    @staticmethod
+    def convert_from_source(bytes source_bytes):
+        return source_bytes
 
     cdef tuple get_input_shape(self):
         raise NotImplementedError("Subclass must implement get_input_shape")