app.py

import os

import numpy as np

import gradio as gr
# Use a pipeline as a high-level helper
import requests
from genai_chat_ai import AI,create_chat_session
API_URL = "https://api-inference.huggingface.co/models/asg2024/vits-ar-sa"
api_key = os.environ.get("Id_mode_vits") 
headers = {"Authorization": f"Bearer {api_key}"}

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

def   get_answer_ai(text):
      try:
          response = AI.send_message(text)
          return response.text

          
      except error:
          return text
          
def reverse_audio(text):
    text_answer=get_answer_ai(text)
    
    data = query(text_answer)
    return data#(16000, np.flipud(data))


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

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