app.py

import gradio as gr
import joblib

# Load the trained model
model = joblib.load("model.pkl")  # Ensure the filename matches exactly

# Define a function to make predictions
def predict(input_data):
    try:
        input_data = [float(i) for i in input_data.split(',')]  # Convert input string to a list of numbers
        prediction = model.predict([input_data])  # Make prediction
        return str(prediction[0])  # Convert output to string
    except Exception as e:
        return f"Error: {str(e)}"

# Create Gradio API
interface = gr.Interface(
    fn=predict, 
    inputs=gr.Textbox(placeholder="Enter comma-separated numbers (e.g., 1.5, 2.3, 3.1)"), 
    outputs="text"
)

# Launch the API
interface.launch()