Create app.py

app.py

@@ -0,0 +1,34 @@
+# functional app
+from model import load_model, invert_audio
+import os
+
+preloaded = {}
+preloaded["model"], preloaded["processor"] = load_model()
+
+# Co
+for input_audio_path in data_dir.glob('*.wav'):
+    print(os.path.basename(input_audio_path))
+    output_audio_path = os.path.join(output_dir, "inverted-" + os.path.basename(input_audio_path))
+    output_file = invert_audio(
+        preloaded["model"], preloaded["processor"],
+        input_audio_path, output_audio_path)
+
+
+# HuggingFace UI
+import streamlit as st
+import torch
+import julius
+
+st.title("Audio Inversion with HuggingFace & Streamlit")
+
+uploaded_file = st.file_uploader("Upload an audio file", type=["wav", "flac"])
+
+if uploaded_file:
+    st.audio(uploaded_file, format="audio/wav")
+    with st.spinner("Inverting audio..."):
+        output_path = "inverted_output.wav" # Temporary output path. Consider using temp files or dynamic naming in production.
+        invert_audio(model, processor, uploaded_file, output_path)
+        st.audio(output_path, format="audio/wav")
+
+    if st.button("Download Inverted Audio"):
+        st.download_button("Download Inverted Audio", data=output_path, file_name="inverted_output.wav", mime="audio/wav")