Update app.py

app.py

@@ -1,50 +1,20 @@
-import gradio as gr
-from musiclang_predict import MusicLangPredictor
-from musiclang import Score
-from midi2audio import FluidSynth
-import os
-import tempfile
-
-
-def inner_loop(midi_file, chord_progression, tempo, temperature, nb_tokens, bar_range):
-    top_p = 0.98
-    seed = 0
-    # Initialize the MusicLangPredictor
-    ml = MusicLangPredictor('musiclang/musiclang-v2')
-    tempo_message = ""  # Default message if no MIDI file is uploaded
-    time_signature = (4, 4)
-    if midi_file is not None and midi_file != "":
-        # Load the MIDI file and use it as the score prompt
-        filepath = midi_file
-        start_bar, end_bar = map(int, bar_range.split("-"))
-        score = Score.from_midi(filepath, chord_range=(start_bar, end_bar))
-        tempo = score.config['tempo'] # Use the tempo from the MIDI file and change input
-        time_signature = score.config['time_signature']
-        time_signature = (time_signature[1], time_signature[2])
-        tempo_message = f"Warning : real tempo of file is : {int(tempo)} BPM."  # Update message based on MIDI file
-    else:
-        score = None  # Default score is None if no MIDI file is uploaded
-
-    # Generate the score based on provided inputs and the uploaded MIDI file if available
-    if chord_progression.strip() == "" and score is None:
-        # Generate without specific chord progression or MIDI prompt
-        generated_score = ml.predict(
-            nb_tokens=int(nb_tokens),
+import gradio
+from transformers import pipeline
             temperature=float(temperature),
             topp=top_p,
             rng_seed=seed
-        )
-    elif score is not None and chord_progression.strip() == "":
-        # Generate using the uploaded MIDI file as a prompt
+        )    
+elif score is not None and chord_progression.strip() == "":        
+# Generate using the uploaded MIDI file as a prompt
         generated_score = ml.predict(
             score=score,  # Use the uploaded MIDI as the score prompt
             nb_tokens=int(nb_tokens),
             temperature=float(temperature),
             topp=top_p,
             rng_seed=seed
-        )
-    else:
-        # Generate with specific chord progression
+        )    
+else:        
+# Generate with specific chord progression
         generated_score = ml.predict_chords(
             chord_progression,
             score=score,  # Use the uploaded MIDI as the score prompt
@@ -53,14 +23,11 @@ def inner_loop(midi_file, chord_progression, tempo, temperature, nb_tokens, bar_
             topp=top_p,
             rng_seed=seed
         )
-
     chord_repr = generated_score.to_chord_repr()
-
     # Save the generated score as a MIDI file
     temp_midi_file = tempfile.NamedTemporaryFile(suffix=".mid", delete=False)
     midi_path = temp_midi_file.name
     generated_score.to_midi(midi_path, tempo=tempo, time_signature=time_signature)
-
     # Convert MIDI to WAV then WAV to MP3 for playback
     temp_wav_file = tempfile.NamedTemporaryFile(suffix=".wav", delete=False)
     temp_mp3_file = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False)
@@ -68,37 +35,32 @@ def inner_loop(midi_file, chord_progression, tempo, temperature, nb_tokens, bar_
     mp3_path = temp_mp3_file.name
     FluidSynth("/usr/share/sounds/sf2/FluidR3_GM.sf2").midi_to_audio(midi_path, wav_path)
     os.system(f'ffmpeg -i {wav_path} -acodec libmp3lame -y -loglevel quiet -stats {mp3_path}')
-
     # Remove the temporary WAV file
     os.remove(wav_path)
-
     return mp3_path, midi_path, chord_repr, tempo_message
-
 def musiclang(midi_file, chord_progression, tempo, temperature, nb_tokens, bar_range):
     exception = None
-    mp3_path, midi_path, chord_repr, tempo_message = None, None, None, ""
-    try:
-        mp3_path, midi_path, chord_repr, tempo_message = inner_loop(midi_file, chord_progression, tempo, temperature, nb_tokens, bar_range)
-    except Exception as e:
-        exception = "Error : " + e.__class__.__name__ + " " + str(e)
-    # Return the MP3 path for Gradio to display and the MIDI file path for download
-    return mp3_path, midi_path, exception
-
-
-with gr.Blocks() as demo:
-    # Introductory text
+    mp3_path, midi_path, chord_repr, tempo_message = None, None, None, ""    
+try:
+        mp3_path, midi_path, chord_repr, tempo_message = inner_loop(midi_file, chord_progression, tempo, temperature, nb_tokens, bar_range)    
+except Exception as e:
+        exception = "Error : " + e.__class__.__name__ + " " + str(e)    
+# Return the MP3 path for Gradio to display and the MIDI file path for download    
+return mp3_path, midi_path, exception
+
+with gr.Blocks() as demo:    
+# Introductory text
     gr.Markdown("""
     # Controllable Symbolic Music Generation with MusicLang Predict
     [MusicLang Predict](https://github.com/musiclang/musiclang_predict) offers advanced controllability features and high-quality music generation by manipulating symbolic music.
     You can for example use it to continue your composition with a specific chord progression.
     """)
-
-    with gr.Row():
-        with gr.Column():
-            with gr.Row():
+    with gr.Row():        
+with gr.Column():            
+with gr.Row():
                 midi_file = gr.File(label="Prompt MIDI File (Optional)", type="filepath", file_types=[".mid", ".midi"],
-                                    elem_id='midi_file_input')
-                with gr.Column():
+                                    elem_id='midi_file_input')                
+with gr.Column():
                     bar_range = gr.Textbox(label="Bar Range of input file (eg: 0-4 for first four bars)", placeholder="0-4",
                                            value="0-4", elem_id='bar_range_input')
                     nb_tokens = gr.Number(label="Nb Tokens",
@@ -109,15 +71,12 @@ with gr.Blocks() as demo:
                         visible=False,
                         minimum=0.1, maximum=1.0, step=0.1, elem_id='temperature_input')
                     tempo = gr.Slider(label="Tempo", value=120, minimum=60, maximum=240, step=1, elem_id='tempo_input')
-
             with gr.Row():
                 chord_progression = gr.Textbox(
                     label="Chord Progression (Optional)",
                     placeholder="Am CM Dm7/F E7 Asus4", lines=2, value="", elem_id='chord_progression_input')
-
             with gr.Row():
                 generate_btn = gr.Button("Generate", elem_id='generate_button')
-
         with gr.Column():
             info_message = gr.Textbox(label="Info Message", elem_id='info_message_output')
             generated_music = gr.Audio(label="Preview generated Music", elem_id='generated_music_output')
@@ -126,11 +85,9 @@ with gr.Blocks() as demo:
                 fn=musiclang,
                 inputs=[midi_file, chord_progression, tempo, temperature, nb_tokens, bar_range],
                 outputs=[generated_music, generated_midi, info_message]
-            )
-            
-
-    with gr.Row():
-        with gr.Column():
+            )            
+    with gr.Row():        
+with gr.Column():
             gr.Markdown("## Examples")
             gr.Examples(
                 examples=[["/home/user/app/bach_847.mid", "", 120, 0.95, 512, "0-4"],
@@ -146,5 +103,4 @@ with gr.Blocks() as demo:
                 fn=musiclang,
                 cache_examples=True,
             )
-
-demo.launch()
+demo.launch()