import gradio as gr
import pandas as pd

def predict_benefit(plan_type, drug_tier, member_age):
    """
    Simple demo logic: mock Drug Benefit Management score calculator.
    Replace this with your model or logic.
    """
    base_cost = 100
    tier_factor = {"Tier 1": 0.8, "Tier 2": 1.0, "Tier 3": 1.3}.get(drug_tier, 1.0)
    plan_factor = {"Basic": 1.1, "Standard": 1.0, "Premium": 0.9}.get(plan_type, 1.0)
    age_factor = 1.2 if member_age > 65 else 1.0

    total_cost = base_cost * tier_factor * plan_factor * age_factor
    benefit_score = round(100 - total_cost / 2, 2)

    return f"Estimated Benefit Score: {benefit_score}"

# Gradio UI
with gr.Blocks(title="Drug Benefit Management") as demo:
    gr.Markdown("## 💊 Drug Benefit Management Model")
    plan_type = gr.Dropdown(["Basic", "Standard", "Premium"], label="Plan Type")
    drug_tier = gr.Dropdown(["Tier 1", "Tier 2", "Tier 3"], label="Drug Tier")
    member_age = gr.Slider(18, 90, 45, label="Member Age")

    output = gr.Textbox(label="Predicted Benefit Score")
    submit = gr.Button("Calculate Benefit")

    submit.click(predict_benefit, [plan_type, drug_tier, member_age], output)

demo.launch(share=True)