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/clip.py

@@ -0,0 +1,37 @@
+from pathlib import Path
+
+from PIL.Image import Image
+from sentence_transformers import SentenceTransformer
+
+from ..schemas import ModelType
+from .base import InferenceModel
+
+
+class CLIPSTEncoder(InferenceModel):
+    _model_type = ModelType.CLIP
+
+    def __init__(
+        self,
+        model_name: str,
+        cache_dir: Path | None = None,
+        **model_kwargs,
+    ):
+        super().__init__(model_name, cache_dir)
+        self.model = SentenceTransformer(
+            self.model_name,
+            cache_folder=self.cache_dir.as_posix(),
+            **model_kwargs,
+        )
+
+    def predict(self, image_or_text: Image | str) -> list[float]:
+        return self.model.encode(image_or_text).tolist()
+
+
+# stubs to allow different behavior between the two in the future
+# and handle loading different image and text clip models
+class CLIPSTVisionEncoder(CLIPSTEncoder):
+    _model_type = ModelType.CLIP_VISION
+
+
+class CLIPSTTextEncoder(CLIPSTEncoder):
+    _model_type = ModelType.CLIP_TEXT