import os import tempfile import torch import gradio as gr from huggingface_hub import hf_hub_download, snapshot_download import spaces torch.backends.cuda.matmul.allow_tf32 = True torch.backends.cudnn.allow_tf32 = True torch.set_float32_matmul_precision('high') # Download models from HuggingFace Hub on startup def download_models(): """Download all required model files from HuggingFace Hub.""" cache_dir = os.environ.get("HF_HOME", os.path.expanduser("/tmp")) model_dir = os.path.join(cache_dir, "heartmula_models") if not os.path.exists(model_dir): os.makedirs(model_dir, exist_ok=True) # Download HeartMuLaGen (tokenizer and gen_config) print("Downloading HeartMuLaGen files...") for filename in ["tokenizer.json", "gen_config.json"]: hf_hub_download( repo_id="HeartMuLa/HeartMuLaGen", filename=filename, local_dir=model_dir, ) # Download HeartMuLa-oss-3B print("Downloading HeartMuLa-oss-3B...") snapshot_download( repo_id="HeartMuLa/HeartMuLa-oss-3B-happy-new-year", local_dir=os.path.join(model_dir, "HeartMuLa-oss-3B"), ) # Download HeartCodec-oss print("Downloading HeartCodec-oss...") snapshot_download( repo_id="HeartMuLa/HeartCodec-oss-20260123", local_dir=os.path.join(model_dir, "HeartCodec-oss"), ) print("All models downloaded successfully!") return model_dir from heartlib import HeartMuLaGenPipeline model_dir = download_models() # Determine device and dtype if torch.cuda.is_available(): device = torch.device("cuda") dtype = torch.bfloat16 else: device = torch.device("cpu") dtype = torch.float32 print(f"Loading pipeline on {device} with {dtype}...") pipe = HeartMuLaGenPipeline.from_pretrained( model_dir, device=device, dtype=dtype, version="3B", ) print("Pipeline loaded successfully!") @spaces.GPU(duration=120) def generate_music( lyrics: str, tags: str, max_duration_seconds: int, temperature: float, topk: int, cfg_scale: float, # progress=gr.Progress(track_tqdm=True), ): """Generate music from lyrics and tags.""" if not lyrics.strip(): raise gr.Error("Please enter some lyrics!") if not tags.strip(): raise gr.Error("Please enter at least one tag!") # Create a temporary file for output with tempfile.NamedTemporaryFile(suffix=".mp3", delete=False) as f: output_path = f.name max_audio_length_ms = max_duration_seconds * 1000 with torch.no_grad(): pipe( { "lyrics": lyrics, "tags": tags, }, max_audio_length_ms=max_audio_length_ms, save_path=output_path, topk=topk, temperature=temperature, cfg_scale=cfg_scale, ) return output_path # Example lyrics EXAMPLE_LYRICS = """[Intro] [Verse] Frustrated, degraded Down before you're done Rejection, depression Can't get what you want [Prechorus] You ask me how I make my way You ask me everywhere and why You hang on every word I say But the truth is like a lie [Chorus] Live to win 'til you die 'Til the light goes out in your eyes Live to win, take it all Just keep fighting 'til you fall [Verse] Obsessive, compulsive Suffocate your mind Confusion, delusions Kill your dreams in time [Prechorus] You ask me how I took the pain Crawled up from my lowest low Step by step and day by day 'Til there's one last breath to go [Chorus] Live to win 'til you die 'Til the light goes out in your eyes Live to win, take it all Just keep fighting 'til you fall Day by day, kickin' all the way I'm not caving in Let another round begin, live to win Yeah, live, yeah, win [Chorus] Live to win 'til you die 'Til the light goes out in your eyes Live to win, take it all Just keep fighting 'til you fall Day by day, kickin' all the way I'm not caving in Let another round begin, live to win Live to win Live to win Yeah, live, yeah, win [Outro]""" EXAMPLE_TAGS = "rock, dark, agressive" # Build the Gradio interface with gr.Blocks( title="HeartMuLa Music Generator", ) as demo: gr.Markdown( """ # HeartMuLa ❤️ ## The best open-sourced music generation model in terms of lyrics controllability and music quality ## *Super-fast torch compiled version* """ ) gr.HTML("""
Project Los Angeles · HeartMuLa Select
""") gr.Markdown( """ Generate music from lyrics and tags using [HeartMuLa](https://github.com/HeartMuLa/heartlib), an open-source music foundation model. **Instructions:** 1. Enter your lyrics with structure tags like `[Verse]`, `[Chorus]`, `[Bridge]`, etc. 2. Add comma-separated tags describing the music style (e.g., `piano,happy,romantic`) 3. For best results use one tag per category 3. Adjust generation parameters as needed 4. Click "Generate Music" and wait for your song! *Note: Generation can take several minutes depending on the duration.* """ ) with gr.Row(): with gr.Column(scale=1): lyrics_input = gr.Textbox( label="Lyrics", placeholder="Enter lyrics with structure tags like [Verse], [Chorus], etc.", lines=20, value=EXAMPLE_LYRICS, ) tags_input = gr.Textbox( label="Tags", placeholder="piano,happy,romantic,synthesizer", value=EXAMPLE_TAGS, info="Comma-separated tags describing the music style (one tag per category)", ) with gr.Accordion("Advanced Settings", open=False): max_duration = gr.Slider( minimum=30, maximum=240, value=240, step=10, label="Max Duration (seconds)", info="Maximum length of generated audio", ) temperature = gr.Slider( minimum=0.1, maximum=2.0, value=1.0, step=0.1, label="Temperature", info="Higher = more creative, Lower = more consistent", ) topk = gr.Slider( minimum=1, maximum=100, value=50, step=1, label="Top-K", info="Number of top tokens to sample from", ) cfg_scale = gr.Slider( minimum=1.0, maximum=5.0, value=3.0, step=0.1, label="CFG Scale", info="Classifier-free guidance scale", ) generate_btn = gr.Button("Generate Music", variant="primary", size="lg") with gr.Column(scale=1): audio_output = gr.Audio( label="Generated Music", type="filepath", ) gr.Markdown( """ ### Tips for Better Results - Use structured lyrics with section tags - Be specific with your style tags and use one tag per style category - Try different temperature values for variety - Shorter durations generate faster ### Offical Tags 1. **GENRE** (95% - MANDATORY) Examples: Pop, Rock, Electronic, Hiphop, Jazz, Classical, Techno, Trance, Ambient. 2. **TIMBRE** (50% - Sound Texture) Examples: Soft, Warm, Husky, Bright, Dark, Distorted. 3. **GENDER** (37% - Vocal Character) Examples: Male, Female. 4. **MOOD** (32% - Emotional Vibe) Examples: Happy, Sad, Energetic, Joyful, Melancholic, Relaxing, Dark. 5. **INSTRUMENT** (25% - Dominant Sounds) Examples: Piano, Synthesizer, Acoustic Guitar, Electric Guitar, Bass, Drums, Strings, Violin. 6. **SCENE** (20% - Listening Context) Examples: Dance, Workout, Dating, Study, Cinematic, Party. 7. **REGION** (12% - Cultural Influence) Examples: K-pop, Latin, Western. 8. **TOPIC** (10% - Lyrical Theme) Examples: Love, Summer, Heartbreak. """ ) generate_btn.click( fn=generate_music, inputs=[ lyrics_input, tags_input, max_duration, temperature, topk, cfg_scale, ], outputs=audio_output, ) gr.Markdown( """ --- **Model:** [HeartMuLa-oss-3B](https://huggingface.co/HeartMuLa/HeartMuLa-oss-3B-happy-new-year) | **Paper:** [arXiv](https://arxiv.org/abs/2601.10547) | **Code:** [GitHub](https://github.com/HeartMuLa/heartlib) *Licensed under Apache 2.0* """ ) demo.launch()