Update app.py

app.py

@@ -1,13 +1,51 @@
 import gradio as gr
+import jukebox
+import torch as t
+import librosa
+import os
+from IPython.display import Audio
 
-def greet(name):
-  return "Hello " + name + "!"
+# Import the model
+model = jukebox.make_vqvae(MODELS.5B_LYRICS)
 
-def add(a, b):
-  return a + b
+# 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
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Input audio
+def input_audio():
+  audio_file = input("Enter the path to the audio file: ")
+  audio_data = librosa.load(audio_file)
+  return audio_data
 
-demo2 = gr.Interface(fn=add, inputs=["number", "number"], outputs="number")
-demo2.launch()
+# 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()