Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline
+import scipy.io.wavfile as wavfile
+import numpy as np
+
+# Load the small version of MusicGen (Fits in Free Tier memory)
+model_id = "facebook/musicgen-small"
+synthesizer = pipeline("text-to-audio", model=model_id)
+
+def generate_music(prompt):
+    # The model generates the audio based on your prompt
+    output = synthesizer(prompt, forward_params={"do_sample": True})
+    
+    # Extract the audio data and sampling rate
+    sampling_rate = output["sampling_rate"]
+    audio_data = output["audio"]
+    
+    # Hugging Face/Gradio expects a tuple of (rate, data)
+    # We ensure the data is in the correct format (float32 or int16)
+    return (sampling_rate, audio_data.T)
+
+# Create the beautiful web interface
+with gr.Blocks() as demo:
+    gr.Markdown("# 🎵 Open Hearts Music Generator")
+    gr.Markdown("Enter your cinematic prompt below to generate a unique track.")
+    
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                label="Your Music Prompt", 
+                placeholder="A cinematic pop-folk crossover with piano and strings...",
+                lines=3
+            )
+            generate_btn = gr.Button("Generate Music", variant="primary")
+        
+        with gr.Column():
+            audio_output = gr.Audio(label="Resulting Audio")
+
+    # Connect the button to the function
+    generate_btn.click(fn=generate_music, inputs=input_text, outputs=audio_output)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()