Update app.py

app.py

@@ -4,7 +4,7 @@ from transformers import pipeline
 import gradio as gr
 
 model_checkpoint = "yzimmermann/FART"
-classifier = pipeline("text-classification", model=model_checkpoint, return_all_scores=True)
+classifier = pipeline("text-classification", model=model_checkpoint, top_k=None)
 
 def process_smiles(smiles):
     # Validate and canonicalize SMILES
@@ -26,14 +26,13 @@ def process_smiles(smiles):
     
     return prediction_dict, img_path, canonical_smiles
 
-# Set up the Gradio interface
 iface = gr.Interface(
     fn=process_smiles,
-    inputs=gr.inputs.Textbox(label="Input SMILES"),
+    inputs=gr.Textbox(label="Input SMILES"),
     outputs=[
-        gr.outputs.Label(num_top_classes=3, label="Classification Probabilities"),
-        gr.outputs.Image(type="file", label="Molecule Image"),
-        gr.outputs.Textbox(label="Canonical SMILES")
+        gr.Label(num_top_classes=3, label="Classification Probabilities"),
+        gr.Image(type="file", label="Molecule Image"),
+        gr.Textbox(label="Canonical SMILES")
     ],
     title="FART",
     description="Enter a SMILES string to get the taste classification probabilities."