Update app.py

app.py

@@ -5,11 +5,11 @@ import torch
 from PIL import Image
 import base64
 from io import BytesIO
-from decimal import Decimal  # Import the Decimal module
+from decimal import Decimal
 
 # Load the CLIP model
 model, preprocess = clip.load("ViT-B/32")
-device = "cuda" if torch.cuda.is_available() else "cpu"
+device = "cuda" if torch.cuda.isavailable() else "cpu"
 model.to(device).eval()
 
 # Define a function to find similarity
@@ -34,10 +34,10 @@ def find_similarity(base64_image, text_input):
     # Calculate cosine similarity
     similarity = (image_features @ text_features.T).squeeze(0).cpu().numpy()
 
-    # Convert the similarity score to a Decimal
-    similarity_decimal = Decimal(similarity)
+    # Convert each element in the similarity array to Decimal
+    similarity_decimal = [Decimal(score) for score in similarity]
 
-    return similarity_decimal  # Return the similarity score as a Decimal
+    return similarity_decimal
 
 # Create a Gradio interface
 iface = gr.Interface(