Update app.py

app.py

@@ -1,26 +1,24 @@
 #!/usr/bin/env python3
-"""Music Transcriber..."""
+"""Music Transcriber - Gradio Web App for Hugging Face Spaces (ZeroGPU)"""
 
 import gradio as gr
-import spaces  # ← ADD THIS LINE
+import spaces  # ← REQUIRED FOR ZEROGPU
 from pathlib import Path
 import tempfile
 import os
 
-# Redirect caches to /tmp for HF Spaces
 os.environ['HF_HOME'] = '/tmp/hf_cache'
 os.environ['TORCH_HOME'] = '/tmp/hf_cache/torch'
 os.environ['TRANSFORMERS_CACHE'] = '/tmp/hf_cache'
 
+@spaces.GPU(duration=600)  # ← THIS IS THE KEY FIX
 def transcribe_audio(audio_file, model_size, instruments):
-    """Transcribe audio to MIDI with progress tracking."""
     if audio_file is None:
         return None, "❌ Please upload an audio file first.", 0
     
     from muscriptor import TranscriptionModel
     from muscriptor.events import ProgressEvent
     
-    # Parse instrument filter
     instrument_group = None
     instrument_names = []
     if instruments:
@@ -42,18 +40,17 @@ def transcribe_audio(audio_file, model_size, instruments):
     
     try:
         note_events = []
-        progress_status = "Starting..."
         
         for event in model.transcribe(str(audio_file), instrument_group=instrument_group):
-            if isinstance(event, ProgressEvent):
-                progress_status = f"🎹 Processing: {int(event.fraction * 100)}%"
+            if hasattr(event, 'fraction'):
+                pass  # Progress tracked internally
             elif hasattr(event, 'note_id'):
                 note_events.append(event)
         
         midi_bytes = model.transcribe_to_midi(str(audio_file), instrument_group=instrument_group)
         output_path.write_bytes(midi_bytes)
         
-        msg = f"✅ Complete!\n🎼 {len(note_events)} notes detected\n📁 MIDI ready for download"
+        msg = f"✅ Complete!\n🎼 {len(note_events)} notes detected"
         if instrument_names:
             msg += f"\n🔍 Filtered: {', '.join(instrument_names)}"
         
@@ -65,77 +62,46 @@ def transcribe_audio(audio_file, model_size, instruments):
         return None, f"❌ Error: {e}", 0
 
 def list_instruments():
-    """Return list of available instruments."""
     try:
         from muscriptor.tokenizer.mt3 import MT3_FULL_PLUS_GROUP_NAMES
-        instruments = sorted(MT3_FULL_PLUS_GROUP_NAMES.keys())
-        return "\n".join(f"• {name}" for name in instruments)
+        return "\n".join(f"• {name}" for name in sorted(MT3_FULL_PLUS_GROUP_NAMES.keys()))
     except Exception:
-        return "Could not load instrument list. Install muscriptor first."
+        return "Could not load instrument list."
 
-# Build Gradio Interface
-with gr.Blocks(
-    title="🎵 Music Transcriber",
-    theme=gr.themes.Soft(primary_hue="purple"),
-    css="""
-        .gradio-container { max-width: 900px !important; }
-        .note-count { font-size: 2rem; font-weight: bold; color: #8b5cf6; text-align: center; padding: 1rem; }
-        .instructions { font-size: 0.9rem; color: #6b7280; }
-    """
-) as demo:
+with gr.Blocks(title="🎵 Music Transcriber") as demo:
     
-    gr.Markdown("# 🎵 Music Transcriber\nTurn audio into MIDI using AI. Upload a song, select model size, and get your transcription!")
+    gr.Markdown("# 🎵 Music Transcriber\nTurn audio into MIDI using AI!")
     
     with gr.Row():
         with gr.Column(scale=1):
-            audio_input = gr.Audio(
-                type="filepath",
-                label="Upload Audio (MP3, WAV, FLAC, OGG, M4A)",
-                interactive=True
+            audio_input = gr.Audio(type="filepath", label="Upload Audio (MP3, WAV, FLAC)")
+            model_select = gr.Radio(
+                choices=[("Small (~100M) - Fastest ⚡", "small"),
+                        ("Medium (~300M) - Balanced 👍", "medium"),
+                        ("Large (~1.3B) - Best Quality 🌟", "large")],
+                value="medium", label="Model Size"
             )
-            
-            with gr.Row():
-                model_select = gr.Radio(
-                    choices=[("Small (~100M) - Fastest ⚡", "small"),
-                            ("Medium (~300M) - Balanced 👍", "medium"),
-                            ("Large (~1.3B) - Best Quality 🌟", "large")],
-                    value="medium",
-                    label="Model Size"
-                )
-            
-            instrument_input = gr.Textbox(
-                label="Filter Instruments (optional)",
-                placeholder="e.g., acoustic_piano, acoustic_guitar, electric_bass",
-                info="Comma-separated instrument names. Leave blank for all instruments."
-            )
-            
+            instrument_input = gr.Textbox(label="Filter Instruments (optional)", placeholder="e.g., acoustic_piano, acoustic_guitar")
             transcribe_btn = gr.Button("🎹 Transcribe Audio", variant="primary", size="lg")
         
         with gr.Column(scale=1):
             status_output = gr.Textbox(label="Status", lines=4)
-            note_count_output = gr.HTML('<div class="note-count">0</div>')
+            note_count_output = gr.HTML('<div style="font-size: 2rem; font-weight: bold; color: #8b5cf6; text-align: center; padding: 1rem;">0</div>')
             midi_output = gr.File(label="Download MIDI", visible=False)
     
-    # List instruments accordion
     with gr.Accordion("📋 View Available Instruments", open=False):
-        gr.Markdown("```")
-        inst_list = gr.Markdown(label="Instruments")
-        gr.Markdown("```")
+        gr.Markdown(list_instruments())
     
-    # Button callbacks
     transcribe_btn.click(
         fn=transcribe_audio,
         inputs=[audio_input, model_select, instrument_input],
         outputs=[midi_output, status_output, note_count_output]
     ).then(
-        lambda path, notes: (gr.update(visible=bool(path)), f"<div class='note-count'>{notes}</div>"),
+        lambda path, notes: (gr.update(visible=bool(path)), 
+                           f"<div style=\"font-size: 2rem; font-weight: bold; color: #8b5cf6; text-align: center; padding: 1rem;\">{notes}</div>"),
         inputs=[midi_output, note_count_output],
         outputs=[midi_output, note_count_output]
     )
-    
-    # Initialize instrument list
-    gr.Markdown("Click the accordion above to see all available instruments.")
-    inst_list.value = list_instruments()
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(theme=gr.themes.Soft(primary_hue="purple"), show_error=True)