Update main.py

main.py

@@ -43,7 +43,7 @@ def predict(item: Item):
     opened_images = [Image.open(image_stream) for image_stream in image_streams]
     
     # Assuming 'model' is your pre-trained model that encodes the images
-    encoded_images = model.encode(opened_images, batch_size=128, convert_to_tensor=True, show_progress_bar=True)
+    encoded_image = model.encode(opened_images, batch_size=128, convert_to_tensor=True, show_progress_bar=True)
     
     # Now we run the clustering algorithm. This function compares images aganist 
     # all other images and returns a list with the pairs that have the highest