Validating if cache file exist or not and accordingly runs caching.

app.py

@@ -1,9 +1,17 @@
 import gradio as gr
 import numpy as np
 from PIL import Image
+from pathlib import Path
 from sentence_transformers import SentenceTransformer
 
-model = SentenceTransformer('clip-ViT-B-32', cache_folder='/app/cache')
+cache_path = Path('/app/cache')
+
+if cache_path.exists():
+    print('Cache folder exists, loading from cache')
+    model = SentenceTransformer('clip-ViT-B-32', cache_folder=cache_path)
+else:
+    print('Cache folder does not exist, loading from web')
+    model = SentenceTransformer('clip-ViT-B-32')
 
 
 def image_to_embedding(img: np.ndarray = None, txt: str = None) -> np.ndarray: