import gradio as gr
import os

# Import the model

model = jukebox.make_vqvae(MODELS['5B_LYRICS'], device="cpu")


# Generate music
def generate_music(temperature=1.0, top_k=10, beam_width=5):
  z = torch.randn(1, 1024)
  audio = model.sample(z, temperature=temperature, top_k=top_k, beam_width=beam_width)
  return audio

# Input audio
def input_audio():
  audio_file = input("Enter the path to the audio file: ")
  audio_data = librosa.load(audio_file)
  return audio_data

# Generate music from the input audio
def generate_music_from_audio(audio_data):
  z = model.encode(audio_data)
  audio = model.decode(z)
  return audio

# Save the music
def save_music(audio, filename):
  librosa.output(filename, audio, sr=44100)

# Play the music
def play_music(audio):
  Audio(audio)

# Create the Gradio interface
app = gr.Interface(
  generate_music,
  inputs=[gr.inputs.Slider(label="Temperature", min=0.0, max=1.0, step=0.1),
           gr.inputs.Slider(label="Top K", min=1, max=10, step=1),
           gr.inputs.Slider(label="Beam Width", min=1, max=10, step=1)],
  outputs=gr.outputs.Audio(),
  title="OpenAI Jukebox",
  description="Generate music using OpenAI Jukebox",
  allow_screenshot=True,
  clear_output=True
)

# Run the app
app.launch()