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.

main.py

@@ -7,7 +7,7 @@ from concurrent.futures import ThreadPoolExecutor
 from typing import Optional
 
 import requests as http_requests
-from fastapi import FastAPI, UploadFile, File, HTTPException, Request
+from fastapi import FastAPI, UploadFile, File, Form, HTTPException, Request
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 
@@ -129,25 +129,25 @@ def health() -> HealthResponse:
         status = inf.ai_availability_status
         status_str = str(status).split()[0] if str(status).strip() else "None"
         error_msg = status.error_message if hasattr(status, 'error_message') else None
-        engine_type = inf.engine.engine_name if inf.engine is not None else None
+        engine_type = inf.engine_name
         return HealthResponse(
             status="healthy",
             aiAvailability=status_str,
             engineType=engine_type,
             errorMessage=error_msg,
         )
-    except Exception:
+    except Exception as e:
         return HealthResponse(
             status="healthy",
             aiAvailability="None",
-            errorMessage=None,
+            errorMessage=str(e),
         )
 
 
 @app.post("/detect")
 async def detect_image(
     file: UploadFile = File(...),
-    config: Optional[str] = None,
+    config: Optional[str] = Form(None),
 ):
     image_bytes = await file.read()
     if not image_bytes: