Update app.py

app.py

@@ -63,7 +63,7 @@ def load_model():
 
 # Function to set up, generate, and process the audio
 @spaces.GPU(duration=120)  # Allocate GPU only when this function is called
-def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7):
+def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7, return_raw_audio=False):
     """
     Generate instrumental music using Stable Audio.
     This function runs on GPU via @spaces.GPU decorator.
@@ -128,19 +128,10 @@ def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7):
     output = output.to(torch.float32).div(torch.max(torch.abs(output))).clamp(-1, 1).mul(32767).to(torch.int16).cpu()    
     print("Audio normalized and converted.")
 
-    # Generate a unique filename for the output
-    unique_filename = f"output_{uuid.uuid4().hex}.wav"
-    print(f"Saving audio to file: {unique_filename}")
-
-    # Save to file
-    torchaudio.save(unique_filename, output, sample_rate)
-    print(f"Audio saved: {unique_filename}")
-
-    # Return the path to the generated audio file
-    return unique_filename
-
+    # only used through the API
+    if return_raw_audio:
+        return output
 
-def save_audio_to_file(output:np.array) -> str:
     # Generate a unique filename for the output
     unique_filename = f"output_{uuid.uuid4().hex}.wav"
     print(f"Saving audio to file: {unique_filename}")
@@ -152,16 +143,11 @@ def save_audio_to_file(output:np.array) -> str:
     # Return the path to the generated audio file
     return unique_filename
 
-
-def inf_function(prompt, seconds_total=30, steps=100, cfg_scale=7):
-    output = generate_audio(prompt, seconds_total, steps, cfg_scale)
-    filename = save_audio_to_file(output)
-    return filename
     
 
 # Setting up the Gradio Interface
 interface = gr.Interface(
-    fn=inf_function,
+    fn=generate_audio,
     inputs=[
         gr.Textbox(
             label="Prompt",