Update app.py

app.py

@@ -1,41 +1,26 @@
 import gradio as gr
 import numpy as np
 
-# Load trained model parameters (assumed to be saved as .npy file)
-theta_final = np.load("theta_final.npy")  # Save your trained theta and upload it to HF Spaces
-
-# Mean and standard deviation for normalization (precomputed from dataset)
-mu = np.array([...])  # Replace with actual values
-sigma = np.array([...])  # Replace with actual values
-sigma = np.where(sigma == 0, 1, sigma)  # Prevent division by zero
+# Load trained model parameters
+theta = np.load("theta_final.npy")
 
+# Define prediction function
 def predict_stroke_risk(*symptoms):
-    user_input = np.array([symptoms])
-    normalized_input = (user_input - mu) / sigma
-    normalized_input = np.c_[np.ones((normalized_input.shape[0], 1)), normalized_input]  # Add bias term
-    y_pred = normalized_input @ theta_final
-    return f"Predicted Stroke Risk: {y_pred[0][0]:.2f}%"
+    symptoms_array = np.array(symptoms).astype(float)
+    risk = np.dot(symptoms_array, theta) * 100  # Convert to percentage
+    return round(risk, 2)
+
+# Define UI
+symptoms_list = ["Symptom 1", "Symptom 2", "Symptom 3", "Symptom 4", "Symptom 5"]
+with gr.Blocks() as demo:
+    gr.Markdown("# 🏥 Stroke Risk Predictor 🚑")
+    gr.Markdown("Select symptoms and get your stroke risk percentage.")
 
-# Symptoms list
-symptoms = [
-    "Chest Pain", "Shortness of Breath", "Irregular Heartbeat", "Fatigue/Weakness", "Dizziness", "Swelling/Edema", 
-    "Pain in Neck/Jaw/Shoulder/Back", "Excessive Sweating", "Persistent Cough", "Nausea/Vomiting", 
-    "High Blood Pressure", "Chest Discomfort During Activity", "Cold Hands/Feet", "Snoring/Sleep Apnea", 
-    "Anxiety/Feeling of Doom", "Age > 50"
-]
+    checkboxes = [gr.Checkbox(label=s) for s in symptoms_list]
+    submit = gr.Button("Predict")
 
-# Creating grid layout
-inputs = []
-for symptom in symptoms:
-    inputs.append(gr.Row([gr.Markdown(f"**{symptom}**"), gr.Checkbox(label="")]))
+    output = gr.Textbox(label="Stroke Risk %")
 
-demo = gr.Interface(
-    fn=predict_stroke_risk,
-    inputs=[inp[1] for inp in inputs],
-    outputs="text",
-    title="Stroke Predictor",
-    description="Tick the symptoms you have",
-    layout="vertical"
-)
+    submit.click(predict_stroke_risk, checkboxes, output)
 
-demo.launch()
+demo.launch()