Design updates

app.py

@@ -23,7 +23,7 @@ logging.basicConfig(level=logging.INFO)
 
 st.set_page_config(layout="wide")
 
-st.title("Credit-Scoring Model Explainability")
+st.title("Loan application model example")
 
 st.markdown(
     """
@@ -104,7 +104,7 @@ def submit_and_clear():
         client.evaluate(
             deployment_id, request_log_id, prediction_log_id, st.session_state.evaluation_input
         )
-        st.toast(":green[Feedback submitted successfully.]", icon="✅")
+        # st.toast(":green-background[Feedback submitted successfully.]", icon="✅")
         st.session_state.eval_selected = False
         st.session_state.evaluation_submitted = True
         st.session_state.eval_selected = False
@@ -115,7 +115,7 @@ def submit_and_clear():
             + "Check whether you are using the right model URL and token for evaluations. "
             + "Contact Deeploy if the problem persists."
         )
-        st.toast(f"Failed to submit feedback: {e}")
+        # st.toast(f"Failed to submit feedback: {e}")
 
 
 def hide_expander():
@@ -275,7 +275,7 @@ if st.session_state.predict_button_clicked:
 
         if predictions[0]:
             # Show prediction
-            st.subheader("Loan Decision: :green[POSITIVE]", divider="green")
+            st.subheader("Loan Decision: :green[Approve]", divider="green")
             # Format subheader to green
             st.markdown(
                 "<style>.css-1v3fvcr{color: green;}</style>", unsafe_allow_html=True
@@ -283,23 +283,23 @@ if st.session_state.predict_button_clicked:
 
             # If prediction is positive, first show positive features, then negative features
             st.success(
-                "**Positive creditworthiness**. This is primarily attributed to:  \n - "
+                "**Positive creditworthiness**. The most important characteristics in favor of loan approval are:  \n - "
                 + "  \n- ".join(pos_feats)
             )
             st.warning(
-                "However, the following features weight ***against*** the loan application:  \n - "
+                "However, the following features weight against the loan applicant:  \n - "
                 + "  \n- ".join(neg_feats)
                 + "  \n For more details, see full explanation of the credit assessment below.",
             )
         else:
-            st.subheader("Loan Decision: :red[NEGATIVE]", divider="red")
+            st.subheader("Loan Decision: :red[Reject]", divider="red")
             # If prediction is negative, first show negative features, then positive features
             st.error(
-                "**Negative creditworthiness**. This is primarily attributed to:  \n - "
+                "**Negative creditworthiness**. The most important characteristics in favor of loan rejection are:  \n - "
                 + "  \n - ".join(neg_feats)
             )
             st.warning(
-                "However, the following factors weigh ***in favor*** of the loan applicant:  \n - "
+                "However, the following factors weigh in favor of the loan applicant:  \n - "
                 + "  \n - ".join(pos_feats)
                 + "  \n For more details, see full explanation of the credit assessment below.",
             )
@@ -348,7 +348,7 @@ if st.session_state.predict_button_clicked:
 
         if not st.session_state.evaluation_submitted:            
             # Add prediction evaluation
-            st.subheader("Evaluation: Do you agree with the predicted creditworthiness?")
+            st.subheader("Evaluation: Do you agree with the loan assessment?")
             st.info(
                 "AI model predictions always come with a certain level of uncertainty.  \nEvaluate the correctness of the prediction based on your expertise and experience."
             )
@@ -390,13 +390,13 @@ if st.session_state.predict_button_clicked:
                 st.session_state.placeholder = "Income is too low, given applicant's background"
 
             if st.session_state.eval_selected:
-                comment = st.text_input("Would you like to add a comment?", placeholder=st.session_state.placeholder)
+                comment = st.text_input("Would you like to add a comment?", placeholder="For example: '" + st.session_state.placeholder + "'")
                 if comment:
                     st.session_state.evaluation_input["explanation"] = comment
 
                 st.button("Submit", key="submit_button", on_click=submit_and_clear)
         else:
-            st.write("Loan application already evaluated - send another loan application to evaluate again.")                    
+            st.success("Evaluation submitted successfully!")                    
 
     except Exception as e:
         logging.error(e)