| name | media-musicgen |
| description | Open-source AI music generation with permissive-license models: Riffusion (MIT, spectrogram-to-audio music from text), YuE (Apache 2.0, Chinese Academy 2025 full-song generation with vocals), Stable Audio Open (Stability community license, commercial up to 1M ARR). Text-to-music, genre-conditioned generation, full song with structure, continuation from existing audio, stem splits via media-demucs. Use when the user asks to generate music from text, create AI songs, make background music for video, generate a jingle, produce royalty-free music with open-source models, make a full song with vocals, or continue an existing musical idea.
|
| argument-hint | [prompt] [output] |
Media MusicGen
Context: $ARGUMENTS
Quick start
- Quick background music (MIT, fully free):
scripts/musicgen.py generate --model riffusion --prompt "lo-fi hip-hop beat" --duration 10 --out out.wav → Step 3
- Full song with vocals:
scripts/musicgen.py generate --model yue --prompt "emotional indie rock, male vocalist, 80 bpm" --duration 90 --out song.wav → Step 3
- Higher-quality 44.1kHz stereo:
scripts/musicgen.py generate --model stable-audio-open --prompt "ambient cinematic strings" --duration 47 --out out.wav → Step 3 (read LICENSES.md first)
- Continue an existing idea:
scripts/musicgen.py continue --in sketch.wav --prompt "build into chorus" --duration 20 --out extended.wav → Step 4
- Split generated music into stems:
scripts/musicgen.py stems --in out.wav --out-dir stems/ → Step 5 (hands off to media-demucs)
When to use
- Generate royalty-free background music for video, podcasts, games
- Prototype song ideas or jingles from a text description
- Produce a full song with AI-generated vocals (YuE only)
- Extend an existing musical idea by feeding it as continuation prompt
- Build AI-music pipelines that stay commercial-safe
Do NOT use this skill for:
- MusicGen / AudioCraft — EXCLUDED, CC-BY-NC weights despite MIT code
- Suno / Udio — commercial paid APIs, not open-source
- Lyria / MusicLM — Google proprietary, not open-weights
- Research-only models (Jukebox, MuseNet, etc.)
Step 1 — Pick a model
| Task | Recommended | License | Commercial use? | Vocals? |
|---|
| Any, lowest friction, fully permissive | Riffusion | MIT | Yes, unconditionally | No |
| Full song with vocals, best 2025 quality | YuE | Apache 2.0 | Yes, unconditionally | Yes |
| Highest audio quality, instrumental | Stable Audio Open | Stability AI Community License | Yes, up to $1M annual revenue | No |
Full license audit (including excluded models and Stable Audio's $1M ARR cap) in references/LICENSES.md.
Step 2 — Install
pip install diffusers transformers torch accelerate soundfile
pip install transformers torch soundfile
pip install stable-audio-tools soundfile
Or let the script help:
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py install riffusion
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py install yue
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py install stable-audio-open
Check what's available:
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py check
Step 3 — Generate
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py generate \
--model riffusion \
--prompt "dreamy lo-fi hip-hop beat with mellow piano" \
--duration 10 \
--out beat.wav
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py generate \
--model yue \
--prompt "emotional indie rock, male vocalist, 80 bpm, acoustic guitar, simple drums" \
--duration 90 \
--out song.wav
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py generate \
--model stable-audio-open \
--prompt "ambient cinematic strings, slow rise, film score" \
--duration 47 \
--out cue.wav
Per-model limits:
- Riffusion native window is 5-second spectrograms. Longer durations (>5s) are produced by repeated inference + crossfade; the script handles this automatically.
- YuE accepts "chain-of-thought" prompts with sections (Verse 1 / Chorus / Bridge). Prompt engineering matters more than other models.
- Stable Audio Open caps individual generations at ~47 seconds.
Step 4 — Continue an existing audio idea
Feed an existing clip as seed; the model continues in style.
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py continue \
--in sketch.wav \
--model stable-audio-open \
--prompt "add energy, build into chorus" \
--duration 20 \
--out extended.wav
Only Stable Audio Open and Riffusion support continuation reliably; YuE's continuation API is less stable.
Step 5 — Split output into stems (vocals / drums / bass / other)
Delegates to the media-demucs skill.
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py stems \
--in song.wav \
--out-dir stems/
Step 6 — Post-process / mux
- Loudness normalization for streaming: hand off to
media-ffmpeg-normalize (Spotify -14 LUFS, YouTube -14 LUFS, broadcast -23 LUFS).
- Export MP3 / Opus / FLAC:
ffmpeg -i song.wav -c:a libmp3lame -b:a 320k song.mp3
- Use as video background:
ffmpeg -i video.mp4 -i music.wav -map 0:v -map 1:a -c:v copy -shortest out.mp4
- Loop seamlessly: see
ffmpeg-audio-filter skill (afade + concat demuxer).
Gotchas
- License boundary with Stable Audio Open: the Stability AI Community License permits commercial use only up to $1M in cumulative revenue. Above that you need a commercial agreement with Stability. Riffusion and YuE have no such cap. Flag this early to the user. See
references/LICENSES.md.
- MusicGen / AudioCraft / Suno / Udio are EXCLUDED from this skill. MusicGen's code is MIT but weights are CC-BY-NC. Do not recommend or install them here.
- Prompt engineering dominates output quality. Bad results are almost always prompt problems. Try: genre + instrumentation + tempo + mood + production style (e.g. "80 bpm lo-fi hip-hop beat with mellow rhodes piano and vinyl crackle, chill sunset vibe").
- Riffusion generates via spectrograms. Under the hood it's Stable Diffusion v1.5 fine-tuned to produce mel-spectrograms, then Griffin-Lim or WaveNet-style decoder. This is why 5 s is the native window.
- YuE produces vocals but expects structured prompts. Its best results are with section labels:
"[Verse 1]\n...lyrics...\n[Chorus]\n...lyrics...". See the YuE HuggingFace model card.
- Stable Audio Open output is 44.1 kHz stereo FP32. Save directly; no resampling needed for most mastering workflows.
- GPU is practically required for YuE (7B params). Riffusion runs on CPU slowly (~2 min for 5 s); Stable Audio Open needs GPU for any reasonable speed.
- Durations are approximate. All three models generate fixed-length latents; actual output length can be ±10% of the requested duration.
- Seeds: pass
--seed N for reproducibility. Default is a random seed each run.
- Model downloads are 2-15 GB each. First run caches into
~/.cache/huggingface/.
- Stereo vs mono: Riffusion is mono-only. YuE is mono. Stable Audio Open is stereo. Upmix to stereo in ffmpeg if needed:
-ac 2.
- No copyright laundering: the user is responsible for confirming generated music doesn't accidentally reproduce a copyrighted melody. Highly specific artist-imitation prompts raise the risk — use genre/mood descriptors instead of artist names.
- Avoid
--chain-of-thought in prompts for non-YuE models. Prompts that reference "Verse 1 / Chorus" etc. confuse Riffusion and Stable Audio Open.
Examples
Example 1: 10-second background music for a video intro
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py generate \
--model riffusion \
--prompt "upbeat corporate bright synth pad, inspirational" \
--duration 10 \
--out intro_music.wav
ffmpeg -i intro.mp4 -i intro_music.wav \
-map 0:v -map 1:a -c:v copy -shortest intro_scored.mp4
Example 2: Full 90-second indie rock song with vocals via YuE
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py generate \
--model yue \
--prompt "[Verse 1] acoustic guitar picking, soft male vocals about a road trip. [Chorus] full band, big drums, uplifting harmonies, 80 bpm. [Verse 2] same as verse 1 with harmony vocal." \
--duration 90 \
--seed 42 \
--out indie_song.wav
Example 3: Stable Audio Open cinematic cue + stem split for DAW mix
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py generate \
--model stable-audio-open \
--prompt "ambient cinematic strings, slow build, film score, Johann Johannsson style" \
--duration 45 \
--out cue.wav
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py stems --in cue.wav --out-dir cue_stems/
Example 4: Extend a sketch idea
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py continue \
--in sketch_8bars.wav \
--model stable-audio-open \
--prompt "build into a climax, more energy, bigger drums" \
--duration 15 \
--out sketch_extended.wav
Troubleshooting
Error: ModuleNotFoundError: No module named 'diffusers'
Cause: Riffusion backend isn't installed.
Solution: pip install diffusers transformers torch accelerate soundfile or scripts/musicgen.py install riffusion.
Error: CUDA out of memory on YuE
Cause: YuE 7B needs ~16 GB VRAM in fp16.
Solution: load in int4 / bnb-4bit (--load-in-4bit flag; requires bitsandbytes), shorten duration, or generate on CPU (slow — 30+ min).
Output clips at 5 s for longer prompts
Cause: Riffusion's native window is 5 s; longer requires the crossfade-loop which the script normally handles automatically.
Solution: confirm --duration exceeds 5 and that the script version is up to date. Try --model stable-audio-open for native long-form.
YuE produces melody but no vocals
Cause: prompt lacks section markers or vocal cues.
Solution: use [Verse 1] / [Chorus] tags and mention vocals explicitly ("male vocalist", "female vocalist", "harmonies").
Generated music sounds like a specific copyrighted song
Cause: overly specific artist / song reference in the prompt.
Solution: describe the style instead of the source (e.g. "melancholic 90s grunge with distorted guitars" rather than "a Nirvana song").
Stable Audio Open refuses to run locally
Cause: Stability CC access-gated on HuggingFace.
Solution: accept the model license on https://huggingface.co/stabilityai/stable-audio-open-1.0 and huggingface-cli login.
Reference docs
references/LICENSES.md — strict confirmation of commercial-safety, including Stable Audio Open's $1M ARR cap and explicit exclusions of MusicGen / Suno / Udio / Jukebox.
