Update app.py with transformer embeddings and prediction pipeline

app.py

@@ -150,7 +150,10 @@ print("Creating Gradio interface...")
 interface = gr.Interface(
     fn=predict,
     inputs=[
-        gr.Textbox(label="Input Protein Sequence"),  # Input: Text box for sequence
+        gr.Textbox(label="Input Protein Sequence",
+                   value="MSPQTETKASVGFKAGVKEYKLTYYTPEYETKDTDILAAFRVTPQPGVPPEEAGAAVAAESSTGTWTTVWTDGLTSLDRYKGRCYHIEPVPGEETQFIAYVAYPLDLFEEGSVTNMFTSIVGNVFGFKALAALRLEDLRIPPAYTKTFQGPPHGIQVERDKLNKYGRPLLGCTIKPKLGLSAKNYGRAVYECLRGGLDFTKDDENVNSQPFMRWRDRFLFCAEAIYKSQAETGEIKGHYLNATAGTCEEMIKRAVFARELGVPIVMHDYLTGGFTANTSLSHYCRDNGLLLHIHRAMHAVIDRQKNHGMHFRVLAKALRLSGGDHIHAGTVVGKLEGDRESTLGFVDLLRDDYVEKDRSRGIFFTQDWVSLPGVLPVASGGIHVWHMPALTEIFGDDSVLQFGGGTLGHPWGNAPGAVANRVALEACVQARNEGRDLAVEGNEIIREACKWSPELAAACEVWKEITFNFPTIDKLDGQE",
+            lines=10, 
+                  ),  # Input: Text box for sequence
         gr.Radio(choices=["Plant-Specific", "General"], label="Prediction Type", value="Plant-Specific"),  # Dropdown for selection
     ],
     outputs=gr.Dataframe(