Initial pipeline setup

pipeline.py

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+import base64
+from io import BytesIO
+from typing import Any, Dict, List
+
+from fashion_clip.fashion_clip import FashionCLIP
+from PIL import Image
+
+
+class PreTrainedPipeline:
+    def __init__(self, path=""):
+        self.model = FashionCLIP("fashion-clip")
+
+    def __call__(self, inputs: str) -> List[float]:
+        """
+        Args:
+            inputs (:obj:`str`):
+                a string to get the features from.
+        Return:
+            A :obj:`list` of floats: The features computed by the model.
+        """
+        image = Image.open(BytesIO(base64.b64decode(inputs)))
+        return self.model.encode_images([image], batch_size=1)[0].tolist()

requirements.txt

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+fashion-clip==0.2.1
+Pillow==10.0.0