spaces

app.py

@@ -1,3 +1,4 @@
+import spaces
 import logging
 import gradio as gr
 import os
@@ -19,7 +20,6 @@ import tempfile
 import shutil
 from Bio import PDB
 from gradio_molecule3d import Molecule3D
-#import spaces  # Import spaces for ZeroGPU compatibility
 
 EXAMPLE_PATH = './examples/example.json'
 example_json=[{'sequences': [{'proteinChain': {'sequence': 'MAEVIRSSAFWRSFPIFEEFDSETLCELSGIASYRKWSAGTVIFQRGDQGDYMIVVVSGRIKLSLFTPQGRELMLRQHEAGALFGEMALLDGQPRSADATAVTAAEGYVIGKKDFLALITQRPKTAEAVIRFLCAQLRDTTDRLETIALYDLNARVARFFLATLRQIHGSEMPQSANLRLTLSQTDIASILGASRPKVNRAILSLEESGAIKRADGIICCNVGRLLSIADPEEDLEHHHHHHHH', 'count': 2}}, {'dnaSequence': {'sequence': 'CTAGGTAACATTACTCGCG', 'count': 2}}, {'dnaSequence': {'sequence': 'GCGAGTAATGTTAC', 'count': 2}}, {'ligand': {'ligand': 'CCD_PCG', 'count': 2}}], 'name': '7pzb_need_search_msa'}]
@@ -210,7 +210,7 @@ def create_protenix_json(input_data: Dict) -> List[Dict]:
 
 
 #@torch.inference_mode()
-#@spaces.GPU(duration=120)  # Specify a duration to avoid timeout
+@spaces.GPU(duration=120)  # Specify a duration to avoid timeout
 def predict_structure(input_collector: dict):
         """Handle both input types"""
         os.makedirs("./output", exist_ok=True)
@@ -451,7 +451,7 @@ with gr.Blocks(title="FoldMark", css=custom_css) as demo:
             outputs=[view3d, confidence_plot_image, cif_file]
         )
 
-    #@spaces.GPU
+    @spaces.GPU
     def is_watermarked(file):
         # Generate a unique subdirectory and filename
         unique_id = str(uuid.uuid4().hex[:8])