Create generativemusiccreator.py

generativemusiccreator.py

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+import subprocess
+import sys
+
+# audiocraft's pinned torchaudio<2.1 would drag torch back; install without deps.
+subprocess.run(
+    [sys.executable, "-m", "pip", "install", "--no-deps", "audiocraft==1.3.0", "demucs"],
+    check=True,
+)
+
+import spaces
+import gradio as gr
+import torchaudio
+from audiocraft.models import AudioGen
+from audiocraft.data.audio import audio_write
+
+model = AudioGen.get_pretrained('facebook/audiogen-medium')
+
+
+@spaces.GPU
+def infer(prompt, duration):
+    
+    model.set_generation_params(duration=duration)  # generate 5 seconds.
+    descriptions = [prompt]
+    wav = model.generate(descriptions)  # generates n samples (referring to the number n of prompts in descriptions)
+
+    for idx, one_wav in enumerate(wav):
+        # Will save under {idx}.wav, with loudness normalization at -14 db LUFS.
+        audio_write(f'{idx}', one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True)
+
+    return "0.wav"
+
+css="""
+#col-container{
+    margin: 0 auto;
+    max-width: 640px;
+}
+"""
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML("""
+        <h2 style="text-align: center;">
+            Generative Music Creation: Textually-guided music generation
+        </h2>
+        <p style="text-align: center;">   
+        </p>
+        """)
+
+        prompt_in = gr.Textbox(label="music prompt")
+        with gr.Row():
+            duration = gr.Slider(label="Duration", minimum=1, maximum=30, step=1, value=5)
+            submit_btn = gr.Button("Submit")
+        audio_o = gr.Audio(label="Generative Music result")
+
+    submit_btn.click(
+        fn=infer,
+        inputs=[prompt_in, duration],
+        outputs=[audio_o]
+    )
+
+# agent5.com music creator
+
+demo.queue().launch()