update

app.py

@@ -38,38 +38,39 @@ elif model_type == 'Linear B-Cell':
         model = TFAutoModelForSequenceClassification.from_pretrained('bcell')
     except:
         st.warning("We're experiencing server issues. Please try again later!", icon="⚠️")
-else:
-    st.warning("We're experiencing server issues. Please try again later!", icon="⚠️")
-# submit button
-if st.button('Submit'):
-    locations = []
-    peptide_name = sequence
-    peptide = tokenizer(peptide_name, return_tensors="tf")
-    output = model(peptide)
-    locations.append([peptide_name, output.logits.numpy()[0][0]])
+try:
+    # submit button
+    if st.button('Submit'):
+        locations = []
+        peptide_name = sequence
+        peptide = tokenizer(peptide_name, return_tensors="tf")
+        output = model(peptide)
+        locations.append([peptide_name, output.logits.numpy()[0][0]])
 
-    locations = pd.DataFrame(locations, columns = ['Peptide', 'Probability'])
+        locations = pd.DataFrame(locations, columns = ['Peptide', 'Probability'])
 
-    # display table with sequence and probability as the headers
-    def color_survived(x: float): # x between 0 and 1
-        # red to green scale based on x
-        # 0 -> red
-        # 0.5 -> clear
-        # 1 -> green
+        # display table with sequence and probability as the headers
+        def color_survived(x: float): # x between 0 and 1
+            # red to green scale based on x
+            # 0 -> red
+            # 0.5 -> clear
+            # 1 -> green
 
-        # red
-        if x < threshold:
-            r = 179
-            g = 40
-            b = 2
-        # green
-        else:
-            r = 18
-            g = 150
-            b = 6
+            # red
+            if x < threshold:
+                r = 179
+                g = 40
+                b = 2
+            # green
+            else:
+                r = 18
+                g = 150
+                b = 6
 
-        return f'background-color: rgb({r}, {g}, {b})'
+            return f'background-color: rgb({r}, {g}, {b})'
 
-    st.table(locations.style.applymap(color_survived, subset=['Probability']))
+        st.table(locations.style.applymap(color_survived, subset=['Probability']))
+except NameError:
+    st.warning("We're experiencing server issues. Please try again later!", icon="⚠️")
 # except InvalidArgumentError:
 #     st.warning("We're experiencing server issues. Please try again later!", icon="⚠️")