app.py

import gradio as gr
import joblib
import numpy as np

# Load trained model
model = joblib.load("pharmacy_inventory_model.pkl")

# Prediction function
def predict_demand(year, month, hour, weekday):

    data = np.array([[year, month, hour, weekday]])

    prediction = model.predict(data)

    return f"Predicted Total Medicine Demand: {prediction[0]:.2f}"


# Gradio Interface
interface = gr.Interface(
    fn=predict_demand,
    inputs=[
        gr.Number(label="Year"),
        gr.Number(label="Month (1-12)"),
        gr.Number(label="Hour (0-276)"),
        gr.Number(label="Weekday (0=Mon, 6=Sun)")
    ],
    outputs="text",
    title="Pharmacy Inventory Prediction System",
    description="AI model to predict pharmacy medicine demand based on date and time."
)

interface.launch()