app.py

import gradio as gr
from transformers import pipeline

print("Loading SiftAI RoBERTa model...")
classifier = pipeline(
    "text-classification",
    model="KakoSan/siftai-roberta-final",
    top_k=None,
)
print("Model loaded.")


def classify_text(text: str):
    if not text or not text.strip():
        return []
    return classifier(text[:512])


demo = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(label="Input Text"),
    outputs=gr.JSON(label="Results"),
    title="SiftAI Text Classifier",
    description="Misinformation detection via fine-tuned RoBERTa.",
    api_name="predict",
)

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