Update app.py

app.py

@@ -1,52 +1,62 @@
 import os
+import tempfile
+import gradio as gr
 import tensorflow as tf
 from tensorflow.python.ops.numpy_ops import np_config
 
-# --------------------------
-# TensorFlow config + Spleeter install
-# --------------------------
+# -------------------------
+# TensorFlow configuration
+# -------------------------
 tf.config.run_functions_eagerly(True)
 np_config.enable_numpy_behavior()
 
+# -------------------------
+# Install Spleeter if missing
+# -------------------------
 if not os.path.exists("/home/user/.spleeter_installed"):
-    import install_spleeter
+    import install_spleeter  # assumes install_spleeter.py is available
     open("/home/user/.spleeter_installed", "w").close()
 
-import tempfile
-import gradio as gr
-
-
-# --------------------------
-# Import Spleeter
-# --------------------------
 from spleeter.separator import Separator
 
-# --------------------------
+# -------------------------
 # Initialize separator
-# --------------------------
+# -------------------------
 separator = Separator("spleeter:2stems", multiprocess=False)
 
-# --------------------------
-# Separation function
-# --------------------------
-
+# -------------------------
+# Audio separation function
+# -------------------------
 def separate_audio(audio_file):
-    tmp = tempfile.mkdtemp()
-    separator.separate_to_file(audio_file, tmp, codec="wav")
-
-    base = os.path.splitext(os.path.basename(audio_file))[0]
-    vocals_path = os.path.join(tmp, base, "vocals.wav")
-    instr_path = os.path.join(tmp, base, "accompaniment.wav")
+    """
+    Takes an audio file path, separates vocals & accompaniment,
+    and returns paths to the resulting WAV files.
+    """
+    tmp_dir = tempfile.mkdtemp()
+    
+    # Use Spleeter's file-based separation
+    separator.separate_to_file(audio_file, tmp_dir, codec="wav")
+    
+    base_name = os.path.splitext(os.path.basename(audio_file))[0]
+    vocals_path = os.path.join(tmp_dir, base_name, "vocals.wav")
+    instr_path = os.path.join(tmp_dir, base_name, "accompaniment.wav")
+    
     return vocals_path, instr_path
 
-# --------------------------
-# Gradio Interface
-# --------------------------
-iface = gr.Interface(
-    fn=separate_audio,
-    inputs=gr.Audio(type="filepath"),
-    outputs=[gr.Audio(), gr.Audio(), gr.Textbox()],
-    title="Spleeter Vocal/Instrumental Separator"
-)
-
-iface.launch(share=True)  # Added public link
+# -------------------------
+# Gradio UI
+# -------------------------
+with gr.Blocks() as iface:
+    gr.Markdown("## Audio Source Separation (Vocals & Instrumentals)")
+    
+    audio_input = gr.Audio(label="Upload Audio", type="filepath")
+    vocals_output = gr.Audio(label="Vocals", type="filepath")
+    instr_output = gr.Audio(label="Instrumental", type="filepath")
+    
+    separate_btn = gr.Button("Separate Audio")
+    separate_btn.click(separate_audio, inputs=audio_input, outputs=[vocals_output, instr_output])
+
+# -------------------------
+# Launch Gradio app
+# -------------------------
+iface.launch(server_name="0.0.0.0", server_port=7860, share=False)