update

README.md

@@ -4,7 +4,7 @@ emoji: 🏆
 colorFrom: indigo
 colorTo: gray
 sdk: gradio
-sdk_version: 3.45.1
+sdk_version: 4.7.1
 app_file: app.py
 pinned: false
 license: mit

app.py

@@ -8,13 +8,13 @@ from pyharp import ModelCard, build_endpoint, save_and_return_filepath
 
 # Define the process function
 @torch.inference_mode()
-def process_fn(input_audio, pitch_shift_amount):
+def process_fn(input_audio_path, pitch_shift_amount):
     from audiotools import AudioSignal
 
     if isinstance(pitch_shift_amount, torch.Tensor):
         pitch_shift_amount = pitch_shift_amount.long().item()
 
-    sig = AudioSignal(input_audio)
+    sig = AudioSignal(input_audio_path)
 
     ps = torchaudio.transforms.PitchShift(
         sig.sample_rate,
@@ -24,7 +24,9 @@ def process_fn(input_audio, pitch_shift_amount):
     ) 
     sig.audio_data = ps(sig.audio_data)
 
-    return save_and_return_filepath(sig)
+    output_audio_path = save_and_return_filepath(sig)
+
+    return output_audio_path
 
 # Create a ModelCard
 card = ModelCard(
@@ -57,6 +59,7 @@ with gr.Blocks() as demo:
     output = gr.Audio(label="Audio Output", type="filepath")
 
     # Build the endpoint
-    ctrls_data, ctrls_button, process_button = build_endpoint(inputs, output, process_fn, card)
+    widgets = build_endpoint(inputs, output, process_fn, card)
 
+demo.queue()
 demo.launch(share=True)