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), 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 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 generated_score = ml.predict_chords( chord_progression, score=score, # Use the uploaded MIDI as the score prompt time_signature=time_signature, temperature=temperature, 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) wav_path = temp_wav_file.name 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 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(): midi_file = gr.File(label="Prompt MIDI File (Optional)", type="filepath", file_types=[".mid", ".midi"], 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", value=512, minimum=256, maximum=2048, step=256, elem_id='nb_tokens_input') temperature = gr.Slider( label="Temperature", value=0.95, 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') generated_midi = gr.File(label="Download MIDI", elem_id='generated_midi_output') generate_btn.click( 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(): gr.Markdown("## Examples") gr.Examples( examples=[["examples/Bach_847.mid", "", 120, 0.95, 512, "0-4"], ["examples/Bach_847.mid", "Cm C7/E Fm F#dim G7", 120, 0.95, 512, "0-4"], ["examples/Boney_m_ma_baker.mid", "", 120, 0.95, 512, "0-4"], ["examples/Eminem_slim_shady.mid", "Cm AbM BbM G7 Cm", 120, 0.95, 512, "0-4"], ["examples/Mozart_alla_turca.mid", "", 120, 0.95, 512, "0-4"], ["examples/Mozart_alla_turca.mid", "Am Em CM G7 E7 Am Am E7 Am", 120, 0.95, 512, "0-4"], ["examples/Daft_punk_Around_the_world.mid", "", 120, 0.95, 512, "0-4"], ], inputs=[midi_file, chord_progression, tempo, temperature, nb_tokens, bar_range], outputs=[generated_music, generated_midi, info_message], fn=musiclang, cache_examples=True, ) demo.launch()