Update app.py

app.py

@@ -3,7 +3,7 @@ from transformers.models.esm.openfold_utils.protein import to_pdb, Protein as OF
 from transformers.models.esm.openfold_utils.feats import atom14_to_atom37
 from proteins_viz import *
 import gradio as gr
-import spaces
+
 
 def convert_outputs_to_pdb(outputs):
     final_atom_positions = atom14_to_atom37(outputs["positions"][-1], outputs)
@@ -40,7 +40,7 @@ torch.backends.cuda.matmul.allow_tf32 = True
 
 model.trunk.set_chunk_size(64)
 
-@spaces.GPU(duration=120)
+
 def fold_protein(test_protein):
     tokenized_input = tokenizer([test_protein], return_tensors="pt", add_special_tokens=False)['input_ids']
     tokenized_input = tokenized_input.cuda()
@@ -55,8 +55,18 @@ def fold_protein(test_protein):
 iface = gr.Interface(
     title="everything-ai-proteinfold",
     fn=fold_protein,
-    inputs="text",
-    outputs="image", 
+    inputs=gr.Textbox(
+            label="Protein Sequence",
+            info="Find sequences examples below, and complete examples with images at: https://github.com/AstraBert/proteinviz/tree/main/examples.md; if you input a sequence, you're gonna get the static image and the HTML file with the 3D model to explore and play with",
+            lines=50,
+            value=f"Paste or write amino-acidic sequence here",
+        ),
+    outputs=[gr.Image(label="Protein static image"), gr.File(label="Protein 3D model HTML")], 
+     examples=[
+        {"sequence": "MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLGAFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVANALAHKYH"},
+        {"sequence": "MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHQYREQIKRVKDSDDVPMVLVGNKCDLAARTVESRQAQDLARSYGIPYIETSAKTRQGVEDAFYTLVREIRQHKLRKLNPPDESGPGCMSCKCVLS"},
+        {"sequence": "MQIFVKTLTGKTITLEVEPSDTIENVKAKIQDKEGIPPDQQRLIFAGKQLEDGRTLSDYNIQKESTLHLVLRLRGG"},
+    ]
 )
 
-iface.launch(server_name="0.0.0.0", share=False)
+iface.launch(server_name="0.0.0.0", share=False)