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| import gradio as gr | |
| from transformers import AutoModel | |
| from miditok import MusicTokenizer | |
| import torch | |
| import numpy as np | |
| import pretty_midi | |
| from io import BytesIO | |
| import os | |
| import requests | |
| # URL of the file to download | |
| url = "https://raw.githubusercontent.com/urish/cinto/refs/heads/master/media/FluidR3%20GM.sf2" | |
| # Local filename to save the file | |
| filename = "FluidR3_GM.sf2" | |
| if not os.path.exists(filename): | |
| response = requests.get(url) | |
| response.raise_for_status() | |
| with open(filename, "wb") as file: | |
| file.write(response.content) | |
| def score_to_audio(score, sample_rate: int = 44100) -> tuple[int, np.ndarray]: | |
| """ | |
| Convert a symusic Score to integer PCM audio data. | |
| Args: | |
| score (Score): symusic Score object | |
| sample_rate (int): desired sample rate in Hz, defaults to 44100 | |
| Returns: | |
| tuple[int, np.ndarray]: Tuple of (sample_rate, audio_data as int16) | |
| """ | |
| # Get MIDI bytes and create MIDI object | |
| midi_data = BytesIO(score.dumps_midi()) | |
| pm = pretty_midi.PrettyMIDI(midi_data) | |
| # Synthesize to float array first | |
| # float_audio = pm.synthesize(fs=sample_rate) | |
| float_audio = pm.fluidsynth( | |
| fs=sample_rate, sf2_path="./FluidR3_GM.sf2" | |
| ) | |
| # Convert to 16-bit integer PCM | |
| # Scale to full int16 range (-32768 to 32767) | |
| int_audio = (float_audio * 32767).astype(np.int16) | |
| int_audio = np.trim_zeros(int_audio, "b") | |
| return sample_rate, int_audio | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| tokenizer = MusicTokenizer.from_pretrained("shikhr/music_maker") | |
| model = AutoModel.from_pretrained("shikhr/music_maker", trust_remote_code=True) | |
| model.to(device) | |
| def generate_music(): | |
| # Generate some music | |
| out = model.generate( | |
| torch.tensor([[1]]).to(device), max_new_tokens=400, temperature=1.0, top_k=None | |
| ) | |
| # Save the generated MIDI | |
| res = tokenizer(out[0].tolist()) | |
| res.dump_midi("output.mid") | |
| nx = score_to_audio(res) | |
| # print(nx) | |
| return "Generated" , nx | |
| demo = gr.Interface(generate_music, inputs=[], outputs=["text", "audio"], flagging_mode="never") | |
| if __name__ == "__main__": | |
| demo.launch() | |