Create app.py

app.py

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+import gradio as gr
+import torch
+import numpy as np
+from transformers import MusicgenForConditionalGeneration, AutoProcessor
+import scipy.io.wavfile
+
+def generate_music(prompt, unconditional=False):
+    model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-small")
+    device = "cuda:0" if torch.cuda.is_available() else "cpu"
+    model.to(device)
+
+    # Generate music
+    if unconditional:
+        unconditional_inputs = model.get_unconditional_inputs(num_samples=1)
+        audio_values = model.generate(**unconditional_inputs, do_sample=True, max_new_tokens=256)
+    else:
+        processor = AutoProcessor.from_pretrained("facebook/musicgen-small")
+        inputs = processor(text=prompt, padding=True, return_tensors="pt")
+        audio_values = model.generate(**inputs.to(device), do_sample=True, guidance_scale=3, max_new_tokens=256)
+
+    sampling_rate = model.config.audio_encoder.sampling_rate
+    audio_file = "musicgen_out.wav"
+    
+    # Ensure audio_values is 1D and scale if necessary
+    audio_data = audio_values[0].cpu().numpy()
+    
+    # Check if audio_data is in the correct format
+    if audio_data.ndim > 1:
+        audio_data = audio_data[0]  # Take the first channel if stereo
+
+    # Scale audio data to 16-bit PCM format
+    audio_data = np.clip(audio_data, -1.0, 1.0)  # Ensure values are in the range [-1, 1]
+    audio_data = (audio_data * 32767).astype(np.int16)  # Scale to int16
+
+    # Save the generated audio
+    scipy.io.wavfile.write(audio_file, sampling_rate, audio_data)
+    
+    return audio_file
+
+def interface(prompt, unconditional):
+    audio_file = generate_music(prompt, unconditional)
+    return audio_file
+
+with gr.Blocks() as demo:
+    gr.Markdown("# AI-Powered Music Generation")
+    
+    with gr.Row():
+        prompt_input = gr.Textbox(label="Enter the Music Prompt")
+        unconditional_checkbox = gr.Checkbox(label="Generate Unconditional Music")
+
+    generate_button = gr.Button("Generate Music")
+    output_audio = gr.Audio(label="Output Music")
+
+    generate_button.click(
+        interface,
+        inputs=[prompt_input, unconditional_checkbox],
+        outputs=output_audio,
+        show_progress=True
+    )
+
+demo.launch(share=True)