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/models/base.py

@@ -0,0 +1,52 @@
+from __future__ import annotations
+
+from abc import abstractmethod, ABC
+from pathlib import Path
+from typing import Any
+
+from ..config import get_cache_dir
+from ..schemas import ModelType
+
+
+class InferenceModel(ABC):
+    _model_type: ModelType
+
+    def __init__(
+        self,
+        model_name: str,
+        cache_dir: Path | None = None,
+    ):
+        self.model_name = model_name
+        self._cache_dir = (
+            cache_dir
+            if cache_dir is not None
+            else get_cache_dir(model_name, self.model_type)
+        )
+
+    @abstractmethod
+    def predict(self, inputs: Any) -> Any:
+        ...
+
+    @property
+    def model_type(self) -> ModelType:
+        return self._model_type
+
+    @property
+    def cache_dir(self) -> Path:
+        return self._cache_dir
+
+    @cache_dir.setter
+    def cache_dir(self, cache_dir: Path):
+        self._cache_dir = cache_dir
+
+    @classmethod
+    def from_model_type(
+        cls, model_type: ModelType, model_name, **model_kwargs
+    ) -> InferenceModel:
+        subclasses = {
+            subclass._model_type: subclass for subclass in cls.__subclasses__()
+        }
+        if model_type not in subclasses:
+            raise ValueError(f"Unsupported model type: {model_type}")
+
+        return subclasses[model_type](model_name, **model_kwargs)