try to debug

app.py

@@ -8,63 +8,34 @@ from anticipation.tokenize import extract_instruments
 import torch
 from pyharp import *
 
-# === Define AMT Model Paths ===
 SMALL_MODEL = "stanford-crfm/music-small-800k"
 MEDIUM_MODEL = "stanford-crfm/music-medium-800k"
 LARGE_MODEL = "stanford-crfm/music-large-800k"
 
-# === Define PyHARP Model Card ===
 model_card = ModelCard(
     name="Anticipatory Music Transformer",
-    description="Using Anticipatory Music Transformer (AMT) to generate accompaniment for a given MIDI file.",
+    description="Using Anticipatory Music Transformer (AMT) to generate accompaniment for a given MIDI file with selected melody.",
     author="John Thickstun, David Hall, Chris Donahue, Percy Liang",
     tags=["midi", "generation", "accompaniment"],
     midi_in=True,
     midi_out=True
 )
 
-# === Load AMT Model Efficiently ===
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-current_model = None
-current_model_choice = None  # Track currently loaded model
-
 def load_amt_model(model_choice):
-    """Loads the selected AMT model only if it changes."""
-    global current_model, current_model_choice
-    if current_model is not None and model_choice == current_model_choice:
-        return current_model  # Use already loaded model
-    
-    print(f"Loading AMT Model: {model_choice}")
-    current_model = AutoModelForCausalLM.from_pretrained(model_choice).to(device)
-    current_model_choice = model_choice
-    return current_model
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    model = AutoModelForCausalLM.from_pretrained(model_choice).to(device)
+    return model
 
-# === Generate Accompaniment Using ZeroGPU ===
-@spaces.GPU  # Enables ZeroGPU acceleration on Hugging Face Spaces
+# Generate Accompaniment Using ZeroGPU 
+@spaces.GPU 
 def generate_accompaniment(midi_file, model_choice, selected_midi_program):
     """Generates accompaniment for the entire MIDI input, conditioned on the first 5 seconds."""
-    
-    # Load the correct AMT model
     model = load_amt_model(model_choice)
-
-    # Validate MIDI file
-    if not midi_file or not hasattr(midi_file, 'name'):
-        raise ValueError("Invalid MIDI file input")
-
-    # Convert MIDI to events
     events = midi_to_events(midi_file.name)
     total_time = round(ops.max_time(events, seconds=True))
-
-    # Extract the melody track
-    events, melody = extract_instruments(events, [selected_midi_program])
-
-    if not melody:
-        raise ValueError("No melody detected for the selected MIDI program!")
-
-    # Use first 5 seconds as history
+    event,melody = extract_instruments(events, [selected_midi_program])
     history = ops.clip(events, 0, 5, clip_duration=False)
-
-    # Generate accompaniment
+    # Generate accompaniment **for the rest of the MIDI duration**
     accompaniment = generate(
         model, 
         5,  # Start generating at 5s
@@ -75,24 +46,23 @@ def generate_accompaniment(midi_file, model_choice, selected_midi_program):
         debug=False
     )
 
-    # Combine accompaniment with melody
+    # Combine the accompaniment with the melody
     output_events = ops.clip(ops.combine(accompaniment, melody), 0, total_time, clip_duration=True)
-
-    # Convert to MIDI
-    output_midi = "generated_accompaniment.mid"
+    # Convert back to MIDI
+    output_midi = "generated_ccompaniment.mid"
     mid = events_to_midi(output_events)
     mid.save(output_midi)
 
     return output_midi
 
-# === PyHARP Process Function ===
+# PyHARP Process Function 
 def process_fn(input_midi, model_choice, selected_midi_program):
     """Processes the input and runs AMT to generate accompaniment for the full MIDI file."""
-    print(f"Model selected: {model_choice}")
     output_midi = generate_accompaniment(input_midi, model_choice, selected_midi_program)
     return output_midi 
 
-# === Build PyHARP Interface ===
+
+# Build Gradio UI
 with gr.Blocks() as demo:
     # Dropdown for selecting AMT model
     model_dropdown = gr.Dropdown(
@@ -104,7 +74,7 @@ with gr.Blocks() as demo:
     # MIDI file upload
     midi_file_input = gr.File(label="Upload MIDI File", file_types=[".mid"])
 
-    # MIDI Program Selection Slider (default to 53)
+    # Static slider (default to 53)
     selected_midi_program = gr.Slider(
         0, 127, step=1, value=53, label="Select Melody Instrument (MIDI Program Number)"
     )
@@ -115,13 +85,12 @@ with gr.Blocks() as demo:
     # Output MIDI File
     output_midi = gr.File(label="Generated Accompaniment (MIDI)")
 
-    # Connect PyHARP to Gradio
-    app = build_endpoint(
-        model_card=model_card,
-        components=[model_dropdown, selected_midi_program],
-        process_fn=process_fn
+    # Connect Gradio Components
+    generate_button.click(
+        process_fn,
+        inputs=[midi_file_input, model_dropdown, selected_midi_program],
+        outputs=[output_midi]
     )
 
-# Launch PyHARP App
 demo.queue()
-demo.launch(show_error=True)
+demo.launch(show_error=True)