app.py

import gradio as gr
from transformers import pipeline

# Load pre-trained sentiment-analysis pipeline
classifier = pipeline('text-classification', model="wcyat/roberta-suicide-detection-hk")

def classify_text(text):
    # Get predictions
    results = classifier(text)
    # Extract and format the results
    output = {result['label']: result['score'] for result in results}
    return output

import gradio as gr

# Define Gradio interface
iface = gr.Interface(
    fn=classify_text,  # function to use for prediction
    inputs="text",     # input type
    outputs="label",   # output type
    title="Text Classification with BERT",
    description="Enter a sentence to classify whether it is suicidal."
)

# Launch the interface
iface.launch()