Update app.py

app.py

@@ -7,11 +7,15 @@ model = joblib.load('logistic_regression_model.pkl')
 scaler = joblib.load('scaler.pkl')
 
 def initial_risk_check(features):
+    # Scale and predict risk based on the features
     features_scaled = scaler.transform([features])
     prediction = model.predict_proba(features_scaled)[:, 1]
+    
+    # Define risk thresholds
     high_risk_threshold = 0.75
     moderate_risk_threshold = 0.5
     
+    # Determine risk level and recommendation
     if prediction >= high_risk_threshold:
         return "High risk. Please consult a doctor immediately.", prediction
     elif prediction >= moderate_risk_threshold:
@@ -20,7 +24,7 @@ def initial_risk_check(features):
         return "Low risk. Maintain a healthy lifestyle and schedule routine check-ups.", prediction
 
 def launch_interface():
-    with gr.Blocks(css=\"
+    with gr.Blocks(css="""
         .gradio-container {
             font-family: Arial, sans-serif;
             background-color: #f9f9f9;
@@ -36,13 +40,13 @@ def launch_interface():
         .gr-textbox {
             margin-bottom: 1em;
         }
-    \") as app:
+    """) as app:
         
-        gr.Markdown(\"
+        gr.Markdown("""
             # Gestational Diabetes Risk Calculator
             This calculator helps you assess your risk for gestational diabetes. Enter your details below and get an initial risk assessment. 
             If you are above medium risk, please provide more detailed information for a more accurate assessment.
-        \")
+        """)
         
         with gr.Row():
             pregnancies = gr.Number(label="Number of Pregnancies")
@@ -53,7 +57,7 @@ def launch_interface():
         with gr.Row():
             ogtt = gr.Number(label="OGTT", visible=False)
             sys_bp = gr.Number(label="Systolic Blood Pressure", visible=False)
-            hdl = gr.Number(label="HDL", visible=False)
+            hdl = gr.Number(label="HDL", visible=False)  # Assuming HDL is used for DPF
 
         submit_button = gr.Button("Submit")
         output = gr.Textbox(label="Result")
@@ -62,7 +66,7 @@ def launch_interface():
             if detailed:
                 features = [pregnancies, ogtt, sys_bp, bmi, hdl, age]
             else:
-                features = [pregnancies, 120, 120, bmi, 0.5, age]
+                features = [pregnancies, 120, 120, bmi, 0.5, age]  # Default values for detailed inputs
             result, prediction = initial_risk_check(features)
             return result