import gradio as gr
import joblib  # Only for demonstration, use joblib if your model is saved with joblib

# Load your machine learning model
# Replace this with your actual model loading code
# Example with a dummy sentiment analysis model
# model = joblib.load('your_model_path.joblib')
def predict_sentiment(text):
    # Replace this with your actual model prediction code
    # Example with a dummy sentiment analysis model
    model = joblib.load("pipeline_model.joblib")
    prediction = model.predict([text])
    return prediction

# Create a Gradio interface
iface = gr.Interface(
    fn=predict_sentiment,  # Your prediction function
    inputs=gr.Textbox(),   # Text input box
    outputs=gr.Textbox(),  # Display prediction output
    live=True               # Update predictions as you type
)

# Launch the interface on a local server
iface.launch()