import gradio as gr
import pickle
import pandas as pd

# Load the saved model (from the Colab notebook)
with open("/content/logistic_model_pipeline.pkl2", "rb") as f:
    model = pickle.load(f)

# Define the prediction function (from the Colab notebook)
def predict_heart_disease(age, sex_male, cigs_per_day, tot_chol, sys_bp, glucose):
    # Create a DataFrame for the input
    input_data = pd.DataFrame({
        'age': [age],
        'Sex_male': [sex_male],
        'cigsPerDay': [cigs_per_day],
        'totChol': [tot_chol],
        'sysBP': [sys_bp],
        'glucose': [glucose]
    })
    
    # Convert DataFrame to NumPy array
    input_data_array = input_data.values  

    # Make prediction using the loaded model (replace with your model's prediction logic)
    prob = model.predict_proba(input_data_array)[0, 1]  # Assuming a probability prediction
    return f"The probability of having heart disease is: {prob * 100:.2f}%"

# Create the Gradio interface
with gr.Blocks() as interface:
    gr.Markdown("## Heart Disease Risk Prediction")
    gr.Markdown("Enter your details below to check the probability of having heart disease.")

    # Age input with helper text
    age = gr.Slider(label="Age", minimum=20, maximum=100, value=50, step=1, info="Enter your age (20-100).")

    # Sex input with helper text
    sex_male = gr.Radio(label="Sex", choices=[1, 0], value=1, info="Select your sex: 1 for Male, 0 for Female.")

    # Cigarettes per day input with helper text
    cigs_per_day = gr.Slider(label="Cigarettes per Day", minimum=0, maximum=60, value=10, step=1, info="Enter the number of cigarettes you smoke per day (0-60).")

    # Total cholesterol input with helper text
    tot_chol = gr.Slider(label="Total Cholesterol (mg/dL)", minimum=100, maximum=400, value=200, step=1, info="Enter your total cholesterol level (100-400 mg/dL).")

    # Systolic blood pressure input with helper text
    sys_bp = gr.Slider(label="Systolic Blood Pressure (mmHg)", minimum=90, maximum=200, value=120, step=1, info="Enter your systolic blood pressure (90-200 mmHg).")

    # Glucose input with helper text
    glucose = gr.Slider(label="Glucose Level (mg/dL)", minimum=50, maximum=300, value=100, step=1, info="Enter your glucose level (50-300 mg/dL).")

    # Predict button and output
    predict_btn = gr.Button("Predict")
    output = gr.Textbox(label="Prediction")

    # Set up the prediction process
    predict_btn.click(predict_heart_disease, inputs=[age, sex_male, cigs_per_day, tot_chol, sys_bp, glucose], outputs=output)

# Launch the interface
interface.launch(share=True)