app.py

import gradio as gr
from transformers import pipeline

# Load the model from Hugging Face Hub
classifier = pipeline("text-classification", model="sandbox338/hatespeech")

# Define the function for the interface
def classify_text(text):
    results = classifier(text)
    # Sort by score and show top result
    return f"{results[0]['label']} ({results[0]['score']:.2f})"

# Create the interface
interface = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(lines=4, placeholder="Enter Swahili text here..."),
    outputs="text",
    title="Swahili Hate Speech Classifier",
    description="Classifies text as Non-hate speech, Political hate speech, or Offensive language."
)

# Launch the interface (only used if running locally)
if __name__ == "__main__":
    interface.launch()