Update app.py

app.py

@@ -4,7 +4,6 @@ import numpy as np
 import torch
 from torch.nn.functional import softmax
 import librosa
-import soundfile as sf
 
 # Path to the local directory where the model files are stored within the Space
 local_model_path = "./"
@@ -28,7 +27,7 @@ def predict_voice(audio_file_path):
     waveform, sample_rate = librosa.load(audio_file_path, sr=16000)  # Force resampling to 16000 Hz
 
     # Ensure waveform is mono
-    if len(waveform.shape) > 1:
+    if waveform.ndim > 1:
         waveform = np.mean(waveform, axis=0)
 
     # Convert the input audio file to model's expected format.
@@ -55,7 +54,7 @@ def predict_voice(audio_file_path):
 # Setting up the Gradio interface
 iface = gr.Interface(
     fn=predict_voice,
-    inputs=gr.Audio(source="upload", type="filepath", label="Upload Audio File"),
+    inputs=gr.Audio(label="Upload Audio File", type="filepath"),  # Correct parameter usage
     outputs=gr.Textbox(label="Prediction"),
     title="Voice Authenticity Detection",
     description="Detects whether a voice is real or AI-generated. Upload an audio file to see the results.",
@@ -64,5 +63,3 @@ iface = gr.Interface(
 
 # Run the Gradio interface with share=True for creating a public link
 iface.launch(share=True)
-io interface
-iface.launch()