Remove expander

app.py

@@ -29,12 +29,12 @@ st.markdown(
     """
     <style>
         section[data-testid="stSidebar"] {
-            width: 300px !important; # Set the width to your desired value
+            width: 300px !important;
         }
     </style>
     """,
     unsafe_allow_html=True,
-)
+)  # Set the side bar width to fit the Deeploy logo
 
 
 def get_model_url():
@@ -123,7 +123,6 @@ def submit_and_clear(evaluation: str):
         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
         )
@@ -323,49 +322,46 @@ elif st.session_state.predict_button_clicked and st.session_state.exp is not Non
                 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")
         try:
-            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,
-                            )
-                        },
-                    )
+            # 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,
+                        )
+                    },
+                )
         except Exception as e:
             logging.error(e)
             st.error(