refactor(ml): modularization and styling (#2835)

* basic refactor and styling

* removed batching

* module entrypoint

* removed unused imports

* model superclass,  model cache now in app state

* fixed cache dir and enforced abstract method

---------

Co-authored-by: Alex Tran <alex.tran1502@gmail.com>

machine-learning/app/config.py

@@ -1,5 +1,10 @@
+from pathlib import Path
+
 from pydantic import BaseSettings
 
+from .schemas import ModelType
+
+
 class Settings(BaseSettings):
     cache_folder: str = "/cache"
     classification_model: str = "microsoft/resnet-50"
@@ -15,8 +20,12 @@ class Settings(BaseSettings):
     min_face_score: float = 0.7
 
     class Config(BaseSettings.Config):
-        env_prefix = 'MACHINE_LEARNING_'
+        env_prefix = "MACHINE_LEARNING_"
         case_sensitive = False
 
 
+def get_cache_dir(model_name: str, model_type: ModelType) -> Path:
+    return Path(settings.cache_folder, model_type.value, model_name)
+
+
 settings = Settings()