Update app.py

app.py

@@ -1,21 +1,32 @@
+import torch
 import gradio as gr
-from transformers import pipeline
+from transformers import AutoProcessor, MusicgenForConditionalGeneration
+import scipy
 
-# Load the MusicGen model
-musicgen = pipeline("text-to-audio", model="facebook/musicgen-small")
+device = "cpu"
+model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-stereo-32khz").to(device)
+processor = AutoProcessor.from_pretrained("facebook/musicgen-stereo-32khz")
 
-def text_to_music(prompt):
-    output = musicgen(prompt)
-    return output["audio"]
+def generate_music(prompt):
+    inputs = processor(text=[prompt], return_tensors="pt").to(device)
+    audio_values = model.generate(**inputs, max_new_tokens=256)  # Adjust length
+    audio_array = audio_values[0].cpu().numpy()
+    sample_rate = model.config.audio_encoder.sampling_rate
 
-# Create Gradio interface
+    # Save as WAV file
+    output_path = "generated_music.wav"
+    scipy.io.wavfile.write(output_path, sample_rate, audio_array.T)
+    return output_path
+
+# Gradio UI
 iface = gr.Interface(
-    fn=text_to_music,
-    inputs=gr.Textbox(label="Enter a music description"),
+    fn=generate_music,
+    inputs=gr.Textbox(label="Enter a music prompt (e.g., 'calm piano melody')"),
     outputs=gr.Audio(label="Generated Music"),
     title="AI Music Generator",
-    description="Enter a description (e.g., 'happy jazz melody') and generate AI music."
+    description="Describe the music style and let AI generate it."
 )
 
 if __name__ == "__main__":
     iface.launch()
+