Update app.py

app.py

@@ -41,30 +41,28 @@ def fold_prot_locally(sequence):
 sample_code = """
 ## Sample usage
 
-```python
-from gradio_client import Client
+    from gradio_client import Client
+    
+    client = Client("https://wwydmanski-esmfold.hf.space/")
+    
+    def fold_huggingface(sequence, fname=None):
+        result = client.predict(
+                    sequence,	# str in 'sequence' Textbox component
+                    api_name="/predict")
+        result = eval(result)[0]
+        if fname is None:
+            with tempfile.NamedTemporaryFile("w", delete=False, suffix=".pdb", prefix="esmfold_") as fp:
+                fp.write(result)
+                fp.flush()
+                return fp.name
+        else:
+            with open(fname, "w") as fp:
+                fp.write(result)
+                fp.flush()
+            return fname
+    
+    pdb_fname = fold_huggingface("MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN")
 
-client = Client("https://wwydmanski-esmfold.hf.space/")
-
-def fold_huggingface(sequence, fname=None):
-    result = client.predict(
-                sequence,	# str in 'sequence' Textbox component
-                api_name="/predict")
-    result = eval(result)[0]
-    if fname is None:
-        with tempfile.NamedTemporaryFile("w", delete=False, suffix=".pdb", prefix="esmfold_") as fp:
-            fp.write(result)
-            fp.flush()
-            return fp.name
-    else:
-        with open(fname, "w") as fp:
-            fp.write(result)
-            fp.flush()
-        return fname
-
-pdb_fname = fold_huggingface("MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN")
-
-```
 """
 
 tokenizer = AutoTokenizer.from_pretrained("facebook/esmfold_v1")