Update my_pages/information_loss.py

my_pages/information_loss.py

@@ -3,18 +3,44 @@ import streamlit as st
 from utils import go_to
 
 ALL_FEATURES = [
-    "Credit Score", "Annual Income", "Loan Amount Requested",
-    "Number of Previous Loans", "Debt-to-Income Ratio",
-    "Employment Stability", "Length of Credit History",
-    "Collateral Value", "Marital Status", "Number of Dependents"
+    ("Liquid Assets", "Liquid Assets", None), 
+    ("Illiquid Assets", "Property appraisals, Insurance valuations, etc.", 
+     "Sorry, it is not possible to get the precise value of illiquid assets. We will use some approximate alternatives instead."),
+    ("Current Debts", "Current Debts", None),
+    ("Income Stability", "Past Income Stability",
+     "Sorry, it is not possible to know precisely how stable someone's income will be in future. Until someone invents a time machine (we're hopeful!), we will instead use past income stability."),
+    ("Health Trajectory", "Current Health Indicators", 
+     "Sorry, it is not possible to know precisely how will someone's health change in the future. Until someone invents a time machine (we're hopeful!), we will instead use current health indicators."),
+    ("Financial Discipline", "Credit Score", 
+     "Sorry, financial discipline is not a directly measurable quality. We will use credit score as an approximation instead.")
 ]
 
 def render():
-    st.title("Information Loss")
+    st.markdown(
+        """
+        <style>
+        button[kind="selected"] {
+            background: green!important;
+        }
+        </style>
+        """,
+        unsafe_allow_html=True,
+    )
+    
+    st.markdown(
+        """
+        <div style='text-align: center; font-size:18px; color:gray;'>
+        Consider the automation of loan approval using AI models. <br>
+        Choose the features below that you would like to collect to train your AI model. <br><br>
+        </div>
+        ---
+        """,
+        unsafe_allow_html=True
+    )
 
     # Session state init
-    if "available_features" not in st.session_state:
-        st.session_state.available_features = ALL_FEATURES.copy()
+    # if "available_features" not in st.session_state:
+    #     st.session_state.available_features = ALL_FEATURES.copy()
 
     if "selected_features" not in st.session_state:
         st.session_state.selected_features = []
@@ -25,21 +51,24 @@ def render():
     with top_left:
         st.image(
             "https://cdn-icons-png.flaticon.com/512/1048/1048949.png",
-            caption="Loan Applicant",
+            # caption="Loan Applicant",
             width=260,
         )
 
     # Top right: simple clickable list of features
     with top_right:
-        st.markdown("**Available Features**")
-        for feature in st.session_state.available_features.copy():
-            if st.button(feature, key=feature):
-                st.session_state.selected_features.append(f"{feature} (approx)")
-                st.session_state.available_features.remove(feature)
-                st.session_state.show_message = (
-                    f"Sorry, '{feature}' cannot be precisely collected. Adding approximation instead."
-                )
-                st.rerun()
+        st.markdown("**All Features**")
+        for feature in ALL_FEATURES.copy():
+            if feature in st.session_state.selected_features:
+                feature_name = feature[1]
+                _ = st.button(feature_name, key=feature_name, type="selected")
+            else:
+                feature_name = feature[0]
+                if st.button(feature_name, key=feature_name):
+                    st.session_state.selected_features.append(feature)
+                    if feature[2] is not None:
+                        st.session_state.show_message = (feature[2])
+                    st.rerun()
 
     # Centered message
     if "show_message" in st.session_state:
@@ -49,16 +78,16 @@ def render():
         )
         del st.session_state.show_message
 
-    st.markdown("---")
+    # st.markdown("---")
 
-    # Bottom half: dataset table
-    st.markdown("### Current Dataset")
-    if st.session_state.selected_features:
-        cols = st.session_state.selected_features + ["Target Label"]
-        df = pd.DataFrame(columns=cols)
-        st.dataframe(df, use_container_width=True)
-    else:
-        st.info("No features added yet. Click a feature above to add it to the dataset.")
+    # # Bottom half: dataset table
+    # st.markdown("### Current Dataset")
+    # if st.session_state.selected_features:
+    #     cols = st.session_state.selected_features + ["Target Label"]
+    #     df = pd.DataFrame(columns=cols)
+    #     st.dataframe(df, use_container_width=True)
+    # else:
+    #     st.info("No features added yet. Click a feature above to add it to the dataset.")
 
     st.markdown("---")
     col1, col2, col3, col4 = st.columns([2, 1, 1, 1])