Add application file

audiogen_demo.py

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+import torchaudio
+from audiocraft.models import AudioGen
+from audiocraft.data.audio import audio_write
+import os
+import gradio as gr
+
+def generate_audio(descriptions):
+    if not os.path.exists('audio_files'):
+        os.makedirs('audio_files')
+    model = AudioGen.get_pretrained('facebook/audiogen-medium')
+    model.set_generation_params(duration=5)  # generate 5 seconds.
+    wav = model.generate([descriptions])  # generates 3 samples.
+    results = []
+
+    for idx, one_wav in enumerate(wav):
+        filename = f'{descriptions}.wav'
+        file_path = os.path.join('audio_files', filename)
+        audio_write(file_path, one_wav.cpu(), model.sample_rate, strategy="loudness", loudness_compressor=True, add_suffix=False)
+        print(f"Generated audio for '{descriptions}'")
+        results.append(file_path)
+    
+    return results[0]
+
+def ui_full():
+    with gr. Blocks() as interface:
+        gr.Markdown(
+            """
+            # AudioGen Demo
+            presented at: [Simple and Controllable Music Generation](https://huggingface.co/)
+            """
+        )
+        with gr.Row():            
+            descriptions = gr.Textbox(lines=2, label="Enter descriptions of the audio to generate")
+        with gr.Row():
+            generate_button = gr.Button("Generate Audio")
+        with gr.Row():    
+            output = gr.Audio(label="Generated Audio")
+
+        generate_button.click(fn=generate_audio, inputs=descriptions, outputs=[output])
+        interface.queue().launch()
+    
+ui_full()