Upload app.py

app.py

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+
+
+# Commented out IPython magic to ensure Python compatibility.
+# %%capture
+# ! pip install git+https://github.com/facebookresearch/audiocraft
+# ! pip install torchvision==0.16.0
+# ! pip install hf-transfer
+# ! pip install gradio
+
+import os
+import gradio as gr
+import torchaudio
+from audiocraft.models import MusicGen
+from audiocraft.data.audio import audio_write
+from huggingface_hub import hf_hub_download
+
+os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "1"
+model = MusicGen.get_pretrained('nateraw/musicgen-songstarter-v0.2')
+
+def generate_music(description, melody_path):
+    model.set_generation_params(duration=5)
+    wav = model.generate([description])
+    for idx, one_wav in enumerate(wav):
+        audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)
+    return f'{idx}.wav'
+
+def remix_music(description, melody_path):
+    melody, sr = torchaudio.load(melody_path)
+    wav = model.generate_with_chroma([description], melody[None].expand(1, -1, -1), sr)
+    for idx, one_wav in enumerate(wav):
+        audio_write(f'{idx}_bach', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)
+    return f'{idx}_bach.wav'
+
+examples = [
+    ["acoustic, guitar, melody, trap, d minor, 90 bpm", None],
+    ["piano, jazz, upbeat, c major, 120 bpm"],
+    ["cinematic, orchestra, epic", None]
+]
+
+demo = gr.Interface(
+    fn=lambda description, melody_path: remix_music(description, melody_path) if melody_path else generate_music(description, None),
+    inputs=[
+        gr.Textbox(label="Enter Description"),
+        gr.File(label="Upload Melody")
+    ],
+    outputs=gr.Audio(label="Generated Music"),
+    examples=examples,
+    title="Music Generation SongStarter App"
+)
+
+demo.launch(debug=True)