update the code

app.py

@@ -13,19 +13,11 @@ import os
 from PIL import Image
 import io
 
-# Convert byte strings to images
 def convert_to_image(byte_data):
+    """Convert byte strings to images
+    """
     return Image.open(io.BytesIO(byte_data))
 
-
-# # Load the token from the environment variable
-# hf_token = os.getenv('HF_AUTH_TOKEN')
-# if hf_token:
-#     HfFolder.save_token(hf_token)
-# else:
-#     raise ValueError("HF_AUTH_TOKEN environment variable is not set")
-
-
 # Load the model and dataset
 model = SentenceTransformer('clip-ViT-B-32')
 ds_with_embeddings = load_dataset("kvriza8/clip_microscopy_image_text_embeddings")
@@ -34,11 +26,6 @@ ds_with_embeddings = load_dataset("kvriza8/clip_microscopy_image_text_embeddings
 # Initialize FAISS index once
 ds_with_embeddings['train'].add_faiss_index(column='img_embeddings')
 
-# def get_image_from_text(text_prompt, number_to_retrieve=1):
-#     prompt = model.encode(text_prompt)
-#     scores, retrieved_examples = ds_with_embeddings['train'].get_nearest_examples('img_embeddings', prompt, k=number_to_retrieve)
-#     images, captions = retrieved_examples['images'], retrieved_examples['caption_summary']
-#     return images, captions
 
 def get_image_from_text(text_prompt, number_to_retrieve=1):
     prompt = model.encode(text_prompt)