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| #!/usr/bin/env python3 | |
| # GhostAI Music Generator Hugging Face Spaces GPU-Compatible | |
| import spaces # <--- Must be imported FIRST before torch and CUDA | |
| import os | |
| import sys | |
| import gc | |
| import warnings | |
| import tempfile | |
| import torch | |
| import torchaudio | |
| import numpy as np | |
| import gradio as gr | |
| from pydub import AudioSegment | |
| from audiocraft.models import MusicGen | |
| from huggingface_hub import login | |
| warnings.filterwarnings("ignore") | |
| # Hugging Face token auth | |
| HF_TOKEN = os.getenv("HF_TOKEN") | |
| if not HF_TOKEN: | |
| sys.exit("ERROR: HF_TOKEN not set.") | |
| login(HF_TOKEN) | |
| # Device setup | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| print(f"Running on {device.upper()}") | |
| os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "max_split_size_mb:128" | |
| # Load MusicGen model explicitly on GPU | |
| musicgen = MusicGen.get_pretrained("medium") | |
| musicgen.lm.to(device) | |
| musicgen.set_generation_params(duration=10) | |
| def clean_resources(): | |
| if device == "cuda": | |
| torch.cuda.empty_cache() | |
| gc.collect() | |
| # <-- Correct GPU decorator for HF | |
| def generate_music(prompt, cfg, top_k, top_p, temp, total_len, chunk_len, crossfade): | |
| if not prompt.strip(): | |
| return None, "⚠️ Enter a valid prompt." | |
| sample_rate = musicgen.sample_rate | |
| segments = [] | |
| chunks = max(1, total_len // chunk_len) | |
| for _ in range(chunks): | |
| with torch.no_grad(): | |
| audio = musicgen.generate( | |
| [prompt], | |
| temperature=temp, | |
| cfg_coef=cfg, | |
| top_k=top_k, | |
| top_p=top_p, | |
| duration=chunk_len, | |
| progress=False | |
| )[0].cpu().float() | |
| if audio.dim() == 1: | |
| audio = audio.unsqueeze(0).repeat(2, 1) | |
| elif audio.shape[0] == 1: | |
| audio = audio.repeat(2, 1) | |
| with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp: | |
| torchaudio.save(tmp.name, audio, sample_rate) | |
| segment = AudioSegment.from_wav(tmp.name) | |
| os.unlink(tmp.name) | |
| segments.append(segment) | |
| clean_resources() | |
| final = segments[0] | |
| for seg in segments[1:]: | |
| final = final.append(seg, crossfade=crossfade) | |
| final = final[:total_len * 1000].fade_in(1000).fade_out(1000).normalize(headroom=-9.0) | |
| out_path = "output_cleaned.mp3" | |
| final.export(out_path, format="mp3", bitrate="128k", tags={"title": "GhostAI Track", "artist": "GhostAI"}) | |
| return out_path, "✅ Done!" | |
| demo = gr.Interface( | |
| fn=generate_music, | |
| inputs=[ | |
| gr.Textbox(label="Instrumental Prompt"), | |
| gr.Slider(1.0, 10.0, value=3.0, step=0.1, label="CFG Scale"), | |
| gr.Slider(10, 500, value=250, step=10, label="Top-K"), | |
| gr.Slider(0.0, 1.0, value=0.9, step=0.05, label="Top-P"), | |
| gr.Slider(0.1, 2.0, value=1.0, step=0.1, label="Temperature"), | |
| gr.Radio([30, 60, 90, 120], value=30, label="Length (seconds)"), | |
| gr.Slider(5, 15, value=10, step=1, label="Chunk Length (seconds)"), | |
| gr.Slider(100, 2000, value=1000, step=100, label="Crossfade (ms)") | |
| ], | |
| outputs=[ | |
| gr.Audio(label="Generated Music", type="filepath"), | |
| gr.Textbox(label="Status") | |
| ], | |
| title="👻 GhostAI Music Generator", | |
| description="Generate instrumental music using MusicGen Medium model." | |
| ) | |
| demo.launch(share=False) | |