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| import gradio as gr | |
| from transformers import pipeline | |
| import tempfile, os | |
| from midi2audio import FluidSynth | |
| # --- Music Generation Logic (API-like Function) --- | |
| def generate_music_api(midi_data=None, chord_progression=None, tempo=120, temperature=0.95, nb_tokens=512, bar_range="0-4"): | |
| try: | |
| # Load the MusicLang Predict model (replace with actual loading code) | |
| ml = ... # Example: ml = pipeline("music-generation", model="your-musiclang-predict-model") | |
| # Handle different generation scenarios based on inputs | |
| if midi_data is not None and chord_progression.strip() != "": | |
| # Continue sequence with chord progression | |
| generated_score = ml.continue_sequence( | |
| midi_data, | |
| chord_progression=chord_progression, | |
| nb_tokens=int(nb_tokens), | |
| temperature=float(temperature), | |
| # ... other parameters | |
| ) | |
| elif midi_data is not None and chord_progression.strip() == "": | |
| # Generate using the uploaded MIDI file as a prompt | |
| generated_score = ml.predict( | |
| midi_data, # Use the uploaded MIDI as the prompt | |
| nb_tokens=int(nb_tokens), | |
| temperature=float(temperature), | |
| # ... other parameters | |
| ) | |
| else: | |
| # Generate with specific chord progression | |
| generated_score = ml.predict_chords( | |
| chord_progression, | |
| # ... other parameters | |
| ) | |
| # Save generated files to temporary locations | |
| 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) # Assuming time_signature is defined | |
| temp_mp3_file = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) | |
| mp3_path = temp_mp3_file.name | |
| # ... (convert MIDI to MP3 using FluidSynth and FFmpeg) | |
| # Read binary data from the temporary files | |
| with open(mp3_path, 'rb') as f_mp3: | |
| mp3_binary = f_mp3.read() | |
| with open(midi_path, 'rb') as f_midi: | |
| midi_binary = f_midi.read() | |
| # Remove temporary files | |
| os.remove(mp3_path) | |
| os.remove(midi_path) | |
| return { | |
| "mp3": mp3_binary, | |
| "midi": midi_binary, | |
| "chord_repr": chord_repr, # Assuming chord_repr is still needed | |
| "tempo_message": tempo_message # Assuming tempo_message is still needed | |
| } | |
| except Exception as e: | |
| return {"error": str(e)} | |
| # --- Gradio Interface --- | |
| def musiclang_gradio(midi_file, chord_progression, tempo, temperature, nb_tokens, bar_range): | |
| midi_data = None | |
| if midi_file: | |
| with open(midi_file.name, "rb") as f: | |
| midi_data = f.read() | |
| api_response = generate_music_api(midi_data=midi_data, chord_progression=chord_progression, tempo=tempo, temperature=temperature, nb_tokens=nb_tokens, bar_range=bar_range) | |
| if "error" in api_response: | |
| return None, None, api_response["error"] | |
| # Create temporary files for Gradio | |
| mp3_path = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False).name | |
| midi_path = tempfile.NamedTemporaryFile(suffix=".mid", delete=False).name | |
| # Write binary data to temporary files | |
| with open(mp3_path, "wb") as f: | |
| f.write(api_response["mp3"]) | |
| with open(midi_path, "wb") as f: | |
| f.write(api_response["midi"]) | |
| return mp3_path, midi_path, None | |
| 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_gradio, | |
| 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=[["/home/user/app/bach_847.mid", "", 120, 0.95, 512, "0-4"], | |
| ["/home/user/app/bach_847.mid", "Cm C7/E Fm F#dim G7", 120, 0.95, 512, "0-4"], | |
| ["/home/user/app/boney_m_ma_baker.mid", "", 120, 0.95, 512, "0-4"], | |
| ["/home/user/app/eminem_slim_shady.mid", "Cm AbM BbM G7 Cm", 120, 0.95, 512, "0-4"], | |
| ["/home/user/app/mozart_alla_turca.mid", "", 120, 0.95, 512, "0-4"], | |
| ["/home/user/app/mozart_alla_turca.mid", "Am Em CM G7 E7 Am Am E7 Am", 120, 0.95, 512, "0-4"], | |
| ["/home/user/app/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_gradio, | |
| cache_examples=True, | |
| ) | |
| demo.launch() |