app.py

import gradio as gr
from joblib import load
import numpy as np

# Load the trained model
model = load("ML_Model_CallCorr.joblib")

def predict_corrected_calcium(total_calcium, total_protein, albumin):
    # Calculate Albumin to Total Protein Ratio
    atr = albumin / total_protein
    
    # Predict the actual calcium value using the model
    predicted_value = model.predict([[total_calcium, atr]])[0]
    
    # Return the result string
    return f"The Actual Calcium value with Correction is {predicted_value:.2f}. The model is a RDF Regression Model with a MSE of 0.06 and R-squared of 0.931."

# Define the Gradio interface
interface = gr.Interface(fn=predict_corrected_calcium, 
                         inputs=[gr.inputs.Number(label="Total Calcium in mg/dL"),
                                 gr.inputs.Number(label="Total Protein in g/dL"),
                                 gr.inputs.Number(label="Albumin in g/dL")],
                         outputs=gr.outputs.Textbox())

interface.launch()