app.py

import gradio as gr
from transformers import pipeline

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

# Map model labels to readable labels
label_map = {
    "LABEL_0": "Non-hate speech",
    "LABEL_1": "Political hate speech",
    "LABEL_2": "Offensive language"
}

# Classification function
def classify_text(text):
    result = classifier(text)[0]
    label = result['label']
    return label_map.get(label, "Unknown")

# Example inputs for testing
examples = [
    ["Hii ni ujumbe wa kawaida bila matusi."],
    ["Wanasiasa hawa ni wabaya na lazima waondoke!"],
    ["Unasema upuuzi na wewe ni mjinga kabisa!"]
]

# Gradio Interface
interface = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(lines=4, placeholder="Andika maandishi ya Kiswahili hapa..."),
    outputs="text",
    title="Swahili Hate Speech Classifier",
    examples=examples
)

if __name__ == "__main__":
    interface.launch()