Update app.py

app.py

@@ -33,9 +33,7 @@ SEP = '=' * 70
 PDT = timezone('US/Pacific')
 
 MODEL_CHECKPOINT = 'Godzilla_Piano_Transformer_No_Velocity_Trained_Model_21113_steps_0.3454_loss_0.895_acc.pth'
-SOUDFONT_PATH = 'SGM-v2.01-YamahaGrand-Guit-Bass-v2.7.sf2'
-NUM_OUT_BATCHES = 12
-PREVIEW_LENGTH = 120  # in tokens
+NUM_OUT_BATCHES = 1
 
 # -----------------------------
 # PRINT START-UP INFO
@@ -109,27 +107,6 @@ print_sep()
 model.cuda()
 model.eval()
 
-# -----------------------------
-# HELPER FUNCTIONS
-# -----------------------------
-def render_midi_output(final_composition):
-    """Generate MIDI score, plot, and audio from final composition."""
-    fname, midi_score = save_midi(final_composition)
-    time_val = midi_score[-1][1] / 1000  # seconds marker from last note
-    midi_plot = TMIDIX.plot_ms_SONG(
-        midi_score,
-        plot_title='Godzilla Piano Transformer Composition',
-        block_lines_times_list=[],
-        return_plt=True
-    )
-    midi_audio = midi_to_colab_audio(
-        fname + '.mid',
-        soundfont_path=SOUDFONT_PATH,
-        sample_rate=16000,
-        output_for_gradio=True
-    )
-    return (16000, midi_audio), midi_plot, fname + '.mid', time_val
-
 # -----------------------------
 # MIDI PROCESSING FUNCTIONS
 # -----------------------------
@@ -212,7 +189,7 @@ def generate_music(prime, num_gen_tokens, num_mem_tokens, num_gen_batches, model
             inp,
             num_gen_tokens,
             temperature=model_temperature,
-            return_prime=False,
+            return_prime=True,
             verbose=False
         )
     print("Done!")
@@ -220,7 +197,7 @@ def generate_music(prime, num_gen_tokens, num_mem_tokens, num_gen_batches, model
     return out.tolist()
 
 def generate_music_and_state(input_midi, num_prime_tokens, num_gen_tokens, num_mem_tokens,
-                             model_temperature, final_composition, generated_batches, block_lines):
+                             model_temperature):
     """
     Generate tokens using the model, update the composition state, and prepare outputs.
     This function combines seed loading, token generation, and UI output packaging.
@@ -244,54 +221,26 @@ def generate_music_and_state(input_midi, num_prime_tokens, num_gen_tokens, num_m
     # Load seed from MIDI if there is no existing composition.
     if not final_composition and input_midi is not None:
         final_composition = load_midi(input_midi)[:num_prime_tokens]
-        midi_fname, midi_score = save_midi(final_composition)
-        # Use the last note's time as a marker.
-        TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(
-            midi_score,
-            output_signature='Godzilla Piano Transformer',
-            output_file_name=midi_fname,
-            track_name='Project Los Angeles',
-            list_of_MIDI_patches=[0]*16,
-            verbose=False
-        )
-        block_lines.append(midi_score[-1][1] / 1000 if final_composition else 0)
     
-    batched_gen_tokens = generate_music(final_composition, num_gen_tokens, num_mem_tokens,
+    generated_batches = generate_music(final_composition, num_gen_tokens, num_mem_tokens,
                                         NUM_OUT_BATCHES, model_temperature)
     
-    output_batches = []
-    for i, tokens in enumerate(batched_gen_tokens):
-        preview_tokens = final_composition[-PREVIEW_LENGTH:]
-        midi_fname, midi_score = save_midi(preview_tokens + tokens, batch_number=i)
-        plot_kwargs = {'plot_title': f'Batch # {i}', 'return_plt': True}
-        if len(final_composition) > PREVIEW_LENGTH:
-            plot_kwargs['preview_length_in_notes'] = len([t for t in preview_tokens if t > 256])
-        TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(
-            midi_score,
-            output_signature='Godzilla Piano Transformer',
-            output_file_name=midi_fname,
-            track_name='Project Los Angeles',
-            list_of_MIDI_patches=[0]*16,
-            verbose=False
-        )
-        midi_plot = TMIDIX.plot_ms_SONG(midi_score, **plot_kwargs)
-        midi_audio = midi_to_colab_audio(midi_fname + '.mid',
-                                         soundfont_path=SOUDFONT_PATH,
-                                         sample_rate=16000,
-                                         output_for_gradio=True)
-        output_batches.append([(16000, midi_audio), midi_plot, tokens])
-    
-    # Update generated_batches (for use by add/remove functions)
-    generated_batches = batched_gen_tokens
+
+    midi_fname, midi_score = save_midi(generated_batches[0])
     
+    TMIDIX.Tegridy_ms_SONG_to_MIDI_Converter(
+        midi_score,
+        output_signature='Godzilla Piano Transformer',
+        output_file_name=midi_fname,
+        track_name='Project Los Angeles',
+        list_of_MIDI_patches=[0]*16,
+        verbose=False
+    )
+       
     print("Request end time:", datetime.datetime.now(PDT).strftime("%Y-%m-%d %H:%M:%S"))
     print_sep()
     
-    # Flatten outputs: states then audio and plots for each batch.
-    outputs_flat = []
-    for batch in output_batches:
-        outputs_flat.extend([batch[0], batch[1]])
-    return [final_composition, generated_batches, block_lines] + outputs_flat
+    return midi_fname
 
 def reset(final_composition=[], generated_batches=[], block_lines=[]):
     """Reset composition state."""