Create app.py

app.py

@@ -0,0 +1,31 @@
+import gradio as gr
+import torch
+import torchaudio
+from df import enhance, init_df
+
+# Initialize DeepFilterNet model
+model, df_state, _ = init_df()
+
+def denoise_audio(audio):
+    # Load the input audio file
+    waveform, sample_rate = torchaudio.load(audio)
+    
+    # Denoise the audio
+    enhanced_audio = enhance(model, df_state, waveform)
+    
+    # Save and return the enhanced audio file
+    output_file = "enhanced_output.wav"
+    torchaudio.save(output_file, enhanced_audio, sample_rate)
+    
+    return output_file
+
+# Gradio interface
+iface = gr.Interface(
+    fn=denoise_audio, 
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs="file",
+    title="DeepFilterNet Audio Denoising",
+    description="Upload an audio file to remove noise using DeepFilterNet."
+)
+
+iface.launch()