import gradio as gr
from transformers import pipeline

# Load the BERT-Emotions-Classifier model
classifier = pipeline("text-classification", model="ayoubkirouane/BERT-Emotions-Classifier")

# Define the prediction function for emotion classification
def classify_emotion(text):
    result = classifier(text)
    return result[0]['label'], result[0]['score']

# Define the Gradio interface
iface = gr.Interface(
    fn=classify_emotion,          # function that will classify emotion
    inputs=gr.Textbox(),          # input text box
    outputs=[gr.Textbox(), gr.Textbox()],  # output emotion label and score
    live=True                      # Enable live mode (optional)
)

# Launch the Gradio interface as an API
iface.launch(share=True)