Update app.py

app.py

@@ -1,32 +1,21 @@
-import torch
 import gradio as gr
-from transformers import AutoProcessor, MusicgenForConditionalGeneration
-import scipy
+from transformers import pipeline
 
-device = "cpu"
-model = MusicgenForConditionalGeneration.from_pretrained("facebook/musicgen-stereo-32khz").to(device)
-processor = AutoProcessor.from_pretrained("facebook/musicgen-stereo-32khz")
+# Load the text-to-audio model
+tts = pipeline("text-to-audio", model="facebook/musicgen-small")
 
-def generate_music(prompt):
-    inputs = processor(text=[prompt], return_tensors="pt").to(device)
-    audio_values = model.generate(**inputs, max_new_tokens=256)  # Adjust length
-    audio_array = audio_values[0].cpu().numpy()
-    sample_rate = model.config.audio_encoder.sampling_rate
+def text_to_audio(text):
+    output = tts(text)
+    return output["audio"]
 
-    # Save as WAV file
-    output_path = "generated_music.wav"
-    scipy.io.wavfile.write(output_path, sample_rate, audio_array.T)
-    return output_path
-
-# Gradio UI
+# Create Gradio interface
 iface = gr.Interface(
-    fn=generate_music,
-    inputs=gr.Textbox(label="Enter a music prompt (e.g., 'calm piano melody')"),
-    outputs=gr.Audio(label="Generated Music"),
-    title="AI Music Generator",
-    description="Describe the music style and let AI generate it."
+    fn=text_to_audio,
+    inputs=gr.Textbox(label="Enter Text"),
+    outputs=gr.Audio(label="Generated Audio"),
+    title="Text-to-Audio Chatbot",
+    description="Enter text, and get an AI-generated audio response."
 )
 
 if __name__ == "__main__":
-    iface.launch()
-
+    iface.launch()