media-musicgen

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

# Riffusion (MIT, diffusers-based)
pip install diffusers transformers torch accelerate soundfile

# YuE (Apache 2.0) — HuggingFace transformers based
pip install transformers torch soundfile
# YuE models: m-a-p/YuE-s1-7B-anneal-en-cot (English, chain-of-thought)
#             m-a-p/YuE-s1-7B-anneal-zh-cot (Mandarin)

# Stable Audio Open (Stability Community License)
pip install stable-audio-tools soundfile
# (HuggingFace: stabilityai/stable-audio-open-1.0)

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

# Riffusion — fast, MIT, spectrogram diffusion
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

# YuE — full song with vocals
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

# Stable Audio Open — 44.1 kHz stereo, instrumental
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/
# -> stems/vocals.wav, stems/drums.wav, stems/bass.wav, stems/other.wav

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

# Generate
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

# Split stems for further work
uv run ${CLAUDE_SKILL_DIR}/scripts/musicgen.py stems --in cue.wav --out-dir cue_stems/
# -> cue_stems/{vocals,drums,bass,other}.wav (other will dominate for instrumental)

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.