app.py

import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification  # ✅ required

# Load model
model_id = "Rerandaka/Cild_safety_bigbird"
tokenizer = AutoTokenizer.from_pretrained(model_id, use_fast=False)
model = AutoModelForSequenceClassification.from_pretrained(model_id)

# Inference function
def classify(text):
    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=512)
    with torch.no_grad():
        logits = model(**inputs).logits
        predicted_class = torch.argmax(logits, dim=1).item()
    return str(predicted_class)

# API-ready Gradio Interface
demo = gr.Interface(
    fn=classify,
    inputs=gr.Textbox(label="Enter text"),
    outputs=gr.Textbox(label="Prediction")
)

# ✅ Enable API and queue
demo.queue()
demo.launch(show_api=True)