[ADD] add button and separator

app.py

@@ -161,9 +161,11 @@ if factchecking_demo == "Preloaded examples":
     ex_claim = selected_row1["claim"].values[0]
     ex_evidence = selected_row1["evidence"].values[0]
     ex_label = selected_row1["label"].values[0]
-    ex_pred = factcheck(
-        selected_row1["claim"].values[0], selected_row1["evidence"].values[0]
-    )
+    if st.button("Run"):
+        ex_pred = factcheck(
+            selected_row1["claim"].values[0],
+            selected_row1["evidence"].values[0],
+        )
     st.markdown(f"**Claim**: {ex_claim}")
     st.markdown(f"**Evidence**: {ex_evidence}")
     st.markdown(f"**Label**: {ex_label}")
@@ -174,10 +176,11 @@ else:
     st.markdown("Or enter your own claim and evidence below:")
     custom_claim = st.text_input(label="Enter your claim.")
     custom_evidence = st.text_input(label="Enter your evidence.")
-    if custom_claim != "" and custom_evidence != "":
-        st.markdown(
-            f"**Prediction**: {factcheck(custom_claim, custom_evidence)}"
-        )
+    if st.button("Run"):
+        if custom_claim != "" and custom_evidence != "":
+            st.markdown(
+                f"**Prediction**: {factcheck(custom_claim, custom_evidence)}"
+            )
 
 st.markdown("---")
 
@@ -197,7 +200,8 @@ if tcfd_demo == "Preloaded examples":
 
     ex_text = selected_row2["text"].values[0]
     ex_label2 = selected_row2["label"].values[0]
-    ex_pred2 = tcfd_classify(selected_row2["text"].values[0])
+    if st.button('Run'):
+        ex_pred2 = tcfd_classify(selected_row2["text"].values[0])
 
     st.markdown(f"**Text**: {ex_text}")
     st.markdown(f"**Label**: {ex_label2}")
@@ -209,5 +213,12 @@ else:
         "Or enter your own sentence to see if it belongs to any specific TCFD disclosure category:"
     )
     custom_text = st.text_input(label="Enter your text.")
-    if custom_text != "":
-        st.markdown(f"**Prediction**: {tcfd_classify(custom_text)}")
+    if st.button("Run"):
+        if custom_text != "":
+            st.markdown(f"**Prediction**: {tcfd_classify(custom_text)}")
+
+st.markdown("""
+            ---
+
+            🌦️
+            """)