Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add S3YED/appie-kit --skill open-source-music-generationgit clone --depth 1 https://github.com/S3YED/appie-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/s3yed/appie-kit/open-source-music-generation)<a href="https://agentmods.dev/skills/s3yed/appie-kit/open-source-music-generation"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/open-source-music-generation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/s3yed/appie-kit/open-source-music-generation"><img src="https://agentmods.dev/badge/skills/s3yed/appie-kit/open-source-music-generation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00053 | $0.02155 |
| Opus 5 | $0.00026 | $0.01077 |
| Sonnet 5 | $0.00011 | $0.00431 |
| Haiku 4.5 | $0.00005 | $0.00215 |
Grade A, and why
open-source-music-generation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Open-Source Music Generation
A unified guide to two major open-source music generation ecosystems: HeartMuLa and AudioCraft (MusicGen/AudioGen). Both generate audio from text descriptions; HeartMuLa specializes in lyrics-conditioned song generation while AudioCraft offers broader text-to-music and text-to-sound capabilities with melody conditioning.
Quick Comparison
| Feature | HeartMuLa | AudioCraft |
|---|---|---|
| Focus | Lyrics+tags song generation | Text-to-music, text-to-sound |
| Model sizes | 3B, 7B | 300M (small) to 3.3B (large) |
| Output | MP3 48kHz stereo | WAV 32kHz mono/stereo |
| VRAM (min) | ~6.2GB (3B lazy) | ~2GB (small fp16) to ~16GB (large) |
| Lyrics support | Core feature (required) | Not supported (text-only) |
| Melody conditioning | No | Yes (musicgen-melody) |
| License | Apache-2.0 | MIT |
| Setup complexity | Medium (patches needed) | Low (pip install) |
When to use HeartMuLa: You need to generate a full song with lyrics, multiple languages, or want the most open-source-capable Suno alternative.
When to use AudioCraft: You need text-to-music or text-to-sound effects, melody conditioning, stereo output, or style transfer.
HeartMuLa — Lyrics-to-Song Generation
HeartMuLa generates full songs from lyrics + genre/style tags. Families of models: HeartMuLa (music language model), HeartCodec (12.5Hz audio codec), HeartTranscriptor (lyrics transcription), HeartCLAP (audio-text alignment).
Hardware Requirements
- Minimum: 8GB VRAM with
--lazy_load true(loads/unloads models sequentially, peaks ~6.2GB) - Recommended: 16GB+ VRAM for single-GPU
- Multi-GPU:
--mula_device cuda:0 --codec_device cuda:1 - CPU mode: Possible with
--mula_device cpu --codec_device cpubut extremely slow (30-60 min per song)
Installation
# 1. Clone
git clone https://github.com/HeartMuLa/heartlib.git
cd heartlib
# 2. Python 3.10 venv
uv venv --python 3.10 .venv
. .venv/bin/activate
uv pip install -e .
# 3. Fix dependency conflicts
uv pip install --upgrade datasets transformers
# 4. Download models (all in parallel)
hf download --local-dir './ckpt' 'HeartMuLa/HeartMuLaGen'
hf download --local-dir './ckpt/HeartMuLa-oss-3B' 'HeartMuLa/HeartMuLa-oss-3B-happy-new-year'
hf download --local-dir './ckpt/HeartCodec-oss' 'HeartMuLa/HeartCodec-oss-20260123'
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 214 lines · 53 tokens per session scan A 0af2756395cc
open-source-music-generation is a skill published in the GitHub repository S3YED/appie-kit (8 stars, last pushed 13d ago), licensed MIT. It adds 53 tokens to every session and 2,155 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
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videoagent-audio-studio
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MiniMax Music Gen
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c-music
Control Spotify playback using the spogo CLI. Play, pause, skip, search tracks/albums/playlists, manage the queue, and browse your library.