Update app.py

app.py

@@ -1,5 +1,12 @@
+pip install streamlit-option-menu
+
 import torch.utils.data as _tud
 from pytorch_tabular.tabular_datamodule import TabularDatamodule
+from streamlit_option_menu import option_menu
+import google.generativeai as genai
+import os
+
+genai.configure(api_key=os.getenv("AIzaSyD7x66J1Bvs3CclxROPsC6QWnXcQiBGYBg"))
 
 _OriginalDataLoader = _tud.DataLoader
 class SafeDataLoader(_OriginalDataLoader):
@@ -43,49 +50,81 @@ with open("FTTransformerModel/threshold.json", "r") as f:
 
 
 # User input
-st.title("Cardiovascular Disease Risk Prediction")
-st.write("Please enter the following health information:")
-
-age = st.number_input("Age", min_value=18, max_value=100, value=50)
-height = st.number_input("Height (cm)", min_value=100, max_value=250, value=170)
-weight = st.number_input("Weight (kg)", min_value=30, max_value=200, value=70)
-systolic = st.number_input("Systolic BP", min_value=80, max_value=250, value=120)
-diastolic = st.number_input("Diastolic BP", min_value=40, max_value=150, value=80)
-cholesterol = st.selectbox("Cholesterol", [0, 1, 2], format_func=lambda x: {0: "Normal", 1: "High", 2: "Very High"}[x])
-gluc = st.selectbox("Glucose", [0, 1, 2], format_func=lambda x: {0: "Normal", 1: "High", 2: "Very High"}[x])
-gender = st.selectbox("Gender", [0, 1], format_func=lambda x: {0: "Female", 1: "Male"}[x])
-smoke = st.selectbox("Do you smoke?", [0, 1], format_func=lambda x: "Yes" if x else "No")
-alco = st.selectbox("Do you drink alcohol?", [0, 1], format_func=lambda x: "Yes" if x else "No")
-active = st.selectbox("Are you physically active?", [0, 1], format_func=lambda x: "Yes" if x else "No")
-
-input_data = pd.DataFrame([{
-    "age": age * 365,
-    "height": height,
-    "weight": weight,
-    "ap_hi": systolic,
-    "ap_lo": diastolic,
-    "cholesterol": cholesterol,
-    "gluc": gluc,
-    "gender": gender,
-    "smoke": smoke,
-    "alco": alco,
-    "active": active
-}])
-
-
-input_data["bmi"] = input_data["weight"] / ((input_data["height"]/100)**2)
-
-input_data["pulse_pressure"] = input_data["ap_hi"] - input_data["ap_lo"]
-
-input_data["hypertension"] = (
-    (input_data["ap_hi"] > 140) | (input_data["ap_lo"] > 90)
-).astype(int)
-
-if st.button("Predict CVD Risk"):
-    preds = model.predict(input_data)
-    # 直接取 CVD（label=1）的概率
-    proba = preds["cardio_1_probability"].iloc[0]
-
-    result = "❌ At Risk of CVD" if proba >= threshold else "✅ Not at Risk"
-    st.subheader("Prediction Result")
-    st.write(f"**{result}** (Probability: {proba:.2%}, Threshold: {threshold:.2f})")
+with st.sidebar:
+    selected = option_menu(
+        menu_title="Navigation",
+        options=["Prediction", "CVD Knowledge"],
+        icons=["activity", "book"],
+        menu_icon="cast",
+        default_index=0,
+    )
+
+if selected == "Prediction":
+    col1, col2, col3 = st.columns([2, 1, 2])
+
+    with col1:
+        st.title("Cardiovascular Disease Risk Prediction")
+        st.write("Please enter the following health information:")
+
+        age = st.number_input("Age", min_value=18, max_value=100, value=50)
+        height = st.number_input("Height (cm)", min_value=100, max_value=250, value=170)
+        weight = st.number_input("Weight (kg)", min_value=30, max_value=200, value=70)
+        systolic = st.number_input("Systolic BP", min_value=80, max_value=250, value=120)
+        diastolic = st.number_input("Diastolic BP", min_value=40, max_value=150, value=80)
+        cholesterol = st.selectbox("Cholesterol", [0, 1, 2], format_func=lambda x: {0: "Normal", 1: "High", 2: "Very High"}[x])
+        gluc = st.selectbox("Glucose", [0, 1, 2], format_func=lambda x: {0: "Normal", 1: "High", 2: "Very High"}[x])
+        gender = st.selectbox("Gender", [0, 1], format_func=lambda x: {0: "Female", 1: "Male"}[x])
+        smoke = st.selectbox("Do you smoke?", [0, 1], format_func=lambda x: "Yes" if x else "No")
+        alco = st.selectbox("Do you drink alcohol?", [0, 1], format_func=lambda x: "Yes" if x else "No")
+        active = st.selectbox("Are you physically active?", [0, 1], format_func=lambda x: "Yes" if x else "No")
+
+        input_data = pd.DataFrame([{
+            "age": age * 365,
+            "height": height,
+            "weight": weight,
+            "ap_hi": systolic,
+            "ap_lo": diastolic,
+            "cholesterol": cholesterol,
+            "gluc": gluc,
+            "gender": gender,
+            "smoke": smoke,
+            "alco": alco,
+            "active": active
+        }])
+
+        input_data["bmi"] = input_data["weight"] / ((input_data["height"]/100)**2)
+        input_data["pulse_pressure"] = input_data["ap_hi"] - input_data["ap_lo"]
+        input_data["hypertension"] = ((input_data["ap_hi"] > 140) | (input_data["ap_lo"] > 90)).astype(int)
+
+        if st.button("Predict CVD Risk"):
+            preds = model.predict(input_data)
+            proba = preds["cardio_1_probability"].iloc[0]
+            result = "❌ At Risk of CVD" if proba >= threshold else "✅ Not at Risk"
+
+            with col2:
+                st.markdown("### 🎯 Prediction Result")
+                st.markdown(f"**<div style='text-align: center; font-size: 24px'>{result}</div>**", unsafe_allow_html=True)
+                st.write(f"(Probability: {proba:.2%}, Threshold: {threshold:.2f})")
+
+            st.markdown("---")
+            st.markdown("### 🤖 Gemini Suggestion")
+            instruction = st.text_area("Custom Gemini Instruction", value="Give detailed lifestyle advice for this risk level")
+
+            if st.button("Get Gemini Advice"):
+                prompt = f"{instruction}. The predicted CVD risk is: {result}. Probability: {proba:.2%}."
+                model_gemini = genai.GenerativeModel("gemini-pro")
+                response = model_gemini.generate_content(prompt)
+                st.markdown("### Gemini's Advice:")
+                st.write(response.text)
+
+elif selected == "CVD Knowledge":
+    st.title("Understanding Cardiovascular Disease")
+    st.markdown("""
+    - **What is CVD?** A group of heart and blood vessel disorders like heart attack and stroke.
+    - **Major Risk Factors:** Age, high blood pressure, high cholesterol, smoking, inactivity, obesity.
+    - **Prevention Tips:**
+        - Exercise regularly (30 mins/day)
+        - Eat low-sodium and low-fat diets
+        - Avoid tobacco and limit alcohol
+        - Monitor blood pressure and sugar
+    """)