Normalize the embedding

handler.py

@@ -89,8 +89,8 @@ class EndpointHandler:
                 image_tensor = self.preprocess(image).unsqueeze(0).to(self.device)
                 text_tensor = self._tokenize_text(text)
 
-                image_features = self.model.encode_image(image_tensor, normalize=False)
-                text_features = self.model.encode_text(text_tensor, normalize=False)
+                image_features = self.model.encode_image(image_tensor, normalize=True)
+                text_features = self.model.encode_text(text_tensor, normalize=True)
 
                 response = {"image_embedding": image_features[0].cpu().tolist()}
                 if isinstance(text, list):
@@ -100,11 +100,11 @@ class EndpointHandler:
                 return response
             elif image is not None:
                 image_tensor = self.preprocess(image).unsqueeze(0).to(self.device)
-                image_features = self.model.encode_image(image_tensor, normalize=False)
+                image_features = self.model.encode_image(image_tensor, normalize=True)
                 return {"image_embedding": image_features[0].cpu().tolist()}
             elif text is not None:
                 text_tensor = self._tokenize_text(text)
-                text_features = self.model.encode_text(text_tensor, normalize=False)
+                text_features = self.model.encode_text(text_tensor, normalize=True)
                 if isinstance(text, list):
                     return {"text_embeddings": text_features.cpu().tolist()}
                 return {"text_embedding": text_features[0].cpu().tolist()}