import os

import numpy as np

import gradio as gr
# Use a pipeline as a high-level helper
import requests

API_URL = "https://api-inference.huggingface.co/models/asg2024/vits-ar-sa"

def query(text):
  payload={"inputs": text}
  response = requests.post(API_URL, json=payload)
  return response.content


def reverse_audio(text):
    data = query(text)
    return (16000, np.flipud(data))


demo = gr.Interface(
    fn=reverse_audio,
    inputs="text",
    outputs="audio"
)

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