Remove submit button

app.py

@@ -101,9 +101,6 @@ if "evaluation_submitted" not in st.session_state:
 if "predict_button_clicked" not in st.session_state:
     st.session_state.predict_button_clicked = False
 
-if "eval_selected" not in st.session_state:
-    st.session_state["eval_selected"] = False
-
 if "exp" not in st.session_state:
     st.session_state.exp = None
 
@@ -118,15 +115,19 @@ def hide_expander():
 def show_expander():
     st.session_state.expander_toggle = True
 
-def submit_and_clear():
+def submit_and_clear(evaluation: str):
+    if evaluation == "yes":
+        st.session_state.evaluation_input["result"] = 0 # Agree with the prediction
+    else:
+        desired_output = not predictions[0]
+        st.session_state.evaluation_input["result"] = 1
+        st.session_state.evaluation_input["value"] = {"predictions": [desired_output]}
     try:
         # Call the explain endpoint as it also includes the prediction
         client.evaluate(
             deployment_id, request_log_id, prediction_log_id, st.session_state.evaluation_input
         )
-        st.session_state.eval_selected = False
         st.session_state.evaluation_submitted = True
-        st.session_state.eval_selected = False
         st.session_state.predict_button_clicked = False
         st.session_state.exp = None
         show_expander()
@@ -138,6 +139,9 @@ def submit_and_clear():
             + "Contact Deeploy if the problem persists."
         )
 
+# with st.expander("Debug session state", expanded=False):
+#     st.write(st.session_state)
+
 # Attributes
 st.subheader("Loan Application")
 with st.expander("Application form", expanded=st.session_state.expander_toggle):
@@ -230,8 +234,11 @@ if deployment_token != "my-secret-token" and st.session_state.exp is None:
             )
             st.session_state.exp = exp
 
+if st.session_state.evaluation_submitted:
+    st.success("Evaluation submitted successfully!")
+
 # Show prediction and explanation after predict button is clicked
-if st.session_state.predict_button_clicked and st.session_state.exp is not None:
+elif st.session_state.predict_button_clicked and st.session_state.exp is not None:
     try:
         exp = st.session_state.exp
         # Read explanation to dataframe from json
@@ -283,90 +290,95 @@ if st.session_state.predict_button_clicked and st.session_state.exp is not None:
             f"{feat}: {neg_exp_df_t.loc[feat, 'Feature value']}"
             for feat in neg_feats
         ]
-        if not st.session_state.evaluation_submitted:  
-            if predictions[0]:
-                # Show prediction
-                st.subheader("Loan Decision: :green[Approve]", divider="green")
-                # Format subheader to green
-                st.markdown(
-                    "<style>.css-1v3fvcr{color: green;}</style>", unsafe_allow_html=True
+        if predictions[0]:
+            # Show prediction
+            st.subheader("Loan Decision: :green[Approve]", divider="green")
+            # Format subheader to green
+            st.markdown(
+                "<style>.css-1v3fvcr{color: green;}</style>", unsafe_allow_html=True
+            )
+            col1, col2 = st.columns(2)
+            with col1:
+                # If prediction is positive, first show positive features, then negative features
+                st.success(
+                    "The most important characteristics in favor of loan approval are:  \n - "
+                    + "  \n- ".join(pos_feats)
+                )
+            with col2:
+                st.warning(
+                    "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[Reject]", divider="red")
+            col1, col2 = st.columns(2)
+            with col1:
+                # If prediction is negative, first show negative features, then positive features
+                st.error(
+                    "The most important characteristics in favor of loan rejection are:  \n - "
+                    + "  \n - ".join(neg_feats)
+                )
+            with col2:
+                st.warning(
+                    "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.",
                 )
-                col1, col2 = st.columns(2)
-                with col1:
-                    # If prediction is positive, first show positive features, then negative features
-                    st.success(
-                        "The most important characteristics in favor of loan approval are:  \n - "
-                        + "  \n- ".join(pos_feats)
-                    )
-                with col2:
-                    st.warning(
-                        "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[Reject]", divider="red")
-                col1, col2 = st.columns(2)
-                with col1:
-                    # If prediction is negative, first show negative features, then positive features
-                    st.error(
-                        "The most important characteristics in favor of loan rejection are:  \n - "
-                        + "  \n - ".join(neg_feats)
-                    )
-                with col2:
-                    st.warning(
-                        "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.",
-                    )
-            explanation_expander = st.expander("Show explanation")
-            with explanation_expander:
-                # Show explanation
-                col_pos, col_neg = st.columns(2)
-
-                with col_pos:
-                    st.subheader("Factors :green[in favor] of loan approval")
-                    # st.success("**Factors in favor of loan approval**")
-                    st.dataframe(
-                        pos_exp_df_t,
-                        hide_index=True,
-                        width=600,
-                        column_config={
-                            "Weight": st.column_config.ProgressColumn(
-                                "Weight",
-                                width="small",
-                                format=" ",
-                                min_value=0,
-                                max_value=1,
-                            )
-                        },
-                    )
-
-                with col_neg:
-                    st.subheader("Factors :red[against] loan approval")
-                    # st.error("**Factors against loan approval**")
-                    st.dataframe(
-                        neg_exp_df_t,
-                        hide_index=True,
-                        width=600,
-                        column_config={
-                            "Weight": st.column_config.ProgressColumn(
-                                "Weight",
-                                width="small",
-                                format=" ",
-                                min_value=0,
-                                max_value=1,
-                            )
-                        },
-                    )
-
-            st.divider()
-          
+        explanation_expander = st.expander("Show explanation")
+        with explanation_expander:
+            # Show explanation
+            col_pos, col_neg = st.columns(2)
+
+            with col_pos:
+                st.subheader("Factors :green[in favor] of loan approval")
+                # st.success("**Factors in favor of loan approval**")
+                st.dataframe(
+                    pos_exp_df_t,
+                    hide_index=True,
+                    width=600,
+                    column_config={
+                        "Weight": st.column_config.ProgressColumn(
+                            "Weight",
+                            width="small",
+                            format=" ",
+                            min_value=0,
+                            max_value=1,
+                        )
+                    },
+                )
+
+            with col_neg:
+                st.subheader("Factors :red[against] loan approval")
+                # st.error("**Factors against loan approval**")
+                st.dataframe(
+                    neg_exp_df_t,
+                    hide_index=True,
+                    width=600,
+                    column_config={
+                        "Weight": st.column_config.ProgressColumn(
+                            "Weight",
+                            width="small",
+                            format=" ",
+                            min_value=0,
+                            max_value=1,
+                        )
+                    },
+                )
+
+        st.divider()
+
+        if not st.session_state.evaluation_submitted:
             # Add prediction evaluation
             st.subheader("Evaluation: Do you agree with the loan assessment?")
             st.write(
                 "AI model predictions always come with a certain level of uncertainty. Evaluate the correctness of the assessment based on your expertise and experience."
             )
+            st.session_state.evaluation_input = {}
+            comment = st.text_input("Your assessment:", placeholder="For example: 'Income is too low, given applicant's background'")
+            if comment:
+                st.session_state.evaluation_input["explanation"] = comment
+
             cols = st.columns(4)
             col_yes, col_no = cols[:2]
             with col_yes:
@@ -375,8 +387,11 @@ if st.session_state.predict_button_clicked and st.session_state.exp is not None:
                     key="yes_button",
                     use_container_width=True,
                     help="Click if you agree with the prediction",
+                    on_click=submit_and_clear,
+                    args=["yes"]
                 )
                 ChangeButtonColour("Yes, I agree", "white", "green")
+
             with col_no:
                 no_button = st.button(
                     "No, I disagree",
@@ -384,33 +399,10 @@ if st.session_state.predict_button_clicked and st.session_state.exp is not None:
                     use_container_width=True,
                     help="Click if you disagree with the prediction",
                     type="primary",
+                    on_click=submit_and_clear,
+                    args=["no"]
                 )
-                ChangeButtonColour("No, I disagree", "white", "#DD360C")
-                # ChangeButtonColour("No, I disagree", "#DD360C", "#F0F0F0")
-            
-            if yes_button:
-                st.session_state.eval_selected = True
-                st.session_state.evaluation_input = {
-                    "result": 0  # Agree with the prediction
-                }
-                st.session_state.placeholder = "Income is sufficient, given applicant's background"
-            if no_button:
-                st.session_state.eval_selected = True
-                desired_output = not predictions[0]
-                st.session_state.evaluation_input = {
-                    "result": 1,  # Disagree with the prediction
-                    "value": {"predictions": [desired_output]},
-                }
-                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="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.success("Evaluation submitted successfully!")                    
+                ChangeButtonColour("No, I disagree", "white", "#DD360C") # Red color for disagree button
 
     except Exception as e:
         logging.error(e)