# import gradio as gr
# import requests
# import os

# def function1(prompt):
#     response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={
#       "data": [
#         prompt,
#     ]}).json()
#     message = response["data"][0]
#     url = 'https://api.elevenlabs.io/v1/text-to-speech/pNInz6obpgDQGcFmaJgB'

#     headers = {
#         'accept': 'audio/mpeg',
#         'xi-api-key': os.environ.get("test2"),
#         'Content-Type': 'application/json'
#     }

#     data = {
#         "text": message,
#         "voice_settings": {
#             "stability": 0,
#             "similarity_boost": 0
#         }
#     }

#     response = requests.post(url, headers=headers, json=data)
#     if response.status_code == 200:
#         file_path = 'test.mp3'
#         if os.path.isfile(file_path):
#             os.remove(file_path)
#         with open(file_path, 'wb') as f:
#             f.write(response.content)
#     return "test.mp3"

# iface = gr.Interface(fn=function1, inputs="text", outputs=[gr.Audio(label="Audio",type="numpy")])
# iface.launch()


import gradio as gr
import requests
import urllib.request
from pydub import AudioSegment
import numpy as np
import os

def function1(prompt):
    response = requests.post("https://tommy24-testing3.hf.space/run/predict", json={
      "data": [
        prompt,
    ]}).json()
    data = response["data"][0]
    response = requests.post("https://matthijs-speecht5-tts-demo.hf.space/run/predict", json={
        "data": [
            data,
            "KSP (male)",
        ]
    }).json()
    data = response["data"][0]["name"]
    data = "https://matthijs-speecht5-tts-demo.hf.space/file="+data
    file_name, headers = urllib.request.urlretrieve(data, "speech.mp3")
    # code = random.randint(1,1000)
    # generated_file = f"output{code}"
    filename = "output.mp3"
    
    if os.path.exists(filename):
        os.remove(filename)
    else:
        pass
    command = f"ffmpeg -i {file_name} -vn -ar 44100 -ac 2 -b:a 192k output.mp3"
    os.system(command)
    return "output.mp3"

iface = gr.Interface(fn=function1, inputs="text", outputs=[gr.Audio(label="Audio",type="numpy")])
iface.launch()