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import gradio as gr
import requests
# from IPython.display import Audio
import tempfile
import os
def generate_music(prompt, duration=10):
API_URL = "https://api-inference.huggingface.co/models/facebook/musicgen-small"
headers = {"Authorization": f"Bearer {os.getenv('HF_API_KEY')}"}
payload = {
"inputs": prompt
}
try:
response = requests.post(API_URL, headers=headers, json=payload, timeout=300)
if response.status_code != 200:
return None, f"Error: API returned status code {response.status_code}"
# Save the audio bytes to a temporary file
with tempfile.NamedTemporaryFile(delete=False, suffix='.wav') as tmp_file:
tmp_file.write(response.content)
tmp_file_path = tmp_file.name
return tmp_file_path, "Music generated successfully!"
except Exception as e:
return None, f"Error: {str(e)}"
# Create the Gradio interface
def gradio_interface(prompt, duration=10):
audio_path, message = generate_music(prompt, duration)
if audio_path:
return audio_path, message
else:
raise gr.Error(message)
# Create the Gradio app
with gr.Blocks() as demo:
gr.Markdown("""
# MusicGen Audio Generator
Generate music from text descriptions using Meta's MusicGen model.
""")
with gr.Row():
with gr.Column():
prompt_input = gr.Textbox(
label="Enter your music description",
placeholder="e.g., liquid drum and bass, atmospheric synths, airy sounds",
lines=3
)
duration_slider = gr.Slider(
minimum=5,
maximum=30,
value=10,
step=5,
label="Duration (seconds)"
)
generate_button = gr.Button("Generate Music")
with gr.Column():
audio_output = gr.Audio(label="Generated Music")
message_output = gr.Textbox(label="Status")
generate_button.click(
fn=gradio_interface,
inputs=[prompt_input, duration_slider],
outputs=[audio_output, message_output]
)
# Launch the app
if __name__ == "__main__":
demo.launch()
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