app.py

import gradio as gr
import pandas as pd
import numpy as np
import joblib

import logging
from pathlib import Path
import uuid

# Create a logs directory if it doesn't exist
Path("logs").mkdir(exist_ok=True)
log_file_path = "logs/predictions.log"

# Configure logging to write to a log file
logging.basicConfig(
    filename=log_file_path,
    level=logging.WARNING,
    # format="%(asctime)s - ID: %(uuid)s - age: %age()s"
)


# Load your model
model = joblib.load("model.joblib")

# Define the function to process inputs
def predict_charges(i_age, i_sex, i_bmi, i_children, i_smoker, i_region):
    # Create a DataFrame with the inputs
    input_data = pd.DataFrame({
        "age": [i_age],
        "sex": [i_sex],
        "bmi": [i_bmi],
        "children": [i_children],
        "smoker": [i_smoker],
        "region": [i_region]
    })
    # Model the data to predict the output. Then 'Return' the output.
    prediction = model.predict(input_data)[0]

    # Log the inputs and the prediction
    logging.warning(
        # f"ID: {uuid.uuid4()} | age: {i_age} | sex: {i_sex} | bmi: {i_bmi} | children: {i_children} | smoker: {i_smoker} | region: {i_region} | prediction: {prediction}"
        # f"{uuid.uuid4()} | {i_age} | {i_sex} | {i_bmi} | {i_children} | {i_smoker} | {i_region} | {prediction}"
        f"{prediction}"
    )
        
    return prediction


# Function to download the log file
def download_log_file():
    return log_file_path
    
# def download_log_file():
#     log_file_path = Path("logs/predictions.log")
#     if log_file_path.exists():
#         return log_file_path
#     else:
#         # If log file doesn't exist, create a placeholder to download
#         log_file_path.write_text("No logs available yet.")
#         return log_file_path

    
# Gradio interface setup
ageIn      = gr.Number(label="Enter Age")
sexIn      = gr.Radio(["female","male"], label="Select Sex")
bmiIn      = gr.Number(label="Enter BMI")
childrenIn = gr.Number(label="Enter Children")
smokerIn   = gr.Radio(["yes", "no"], label="Is Smoker?")
regionIn   = gr.Dropdown(["northeast","northwest","southeast","southwest"], label="Select Region")
chargesOut = gr.Number(label="Predicted Charges")

downloadOut = gr.File(label="Download Prediction Logs")


# Initialize the Gradio interface
iface1 = gr.Interface(
    fn=predict_charges,
    inputs=[ageIn, sexIn, bmiIn, childrenIn, smokerIn, regionIn],
    outputs=chargesOut,
    title="HealthyLife Insurance Charge Prediction",
    description="Enter the details to estimate health insurance charges based on input parameters."
)

# Add a download button for the log file
iface2 = gr.Interface(
    fn=download_log_file,
    inputs=None,
    outputs=downloadOut,
    description="Download the log file of inputs and predictions"
)


# Combine main app and download button in a single interface
iface = gr.TabbedInterface([iface1, iface2], ["Predict Charges", "Download Logs"])


# Launch the app
iface.launch()