关于
The acestep skill enables AI-powered music generation and audio processing using ACE-Step 1.5 models. It handles background music creation, vocal tracks, covers, stem extraction, audio repainting, and continuation for video production workflows. Developers should use it when triggered by music-related tasks like soundtrack generation, jingle creation, or audio stem manipulation.
快速安装
Claude Code
推荐npx skills add digitalsamba/claude-code-video-toolkit -a claude-code/plugin add https://github.com/digitalsamba/claude-code-video-toolkitgit clone https://github.com/digitalsamba/claude-code-video-toolkit.git ~/.claude/skills/acestep在 Claude Code 中复制并粘贴此命令以安装该技能
技能文档
ACE-Step 1.5 Music Generation
Open-source music generation via tools/music_gen.py.
Cloud providers:
- acemusic (default) — Official ACE-Step cloud API with XL Turbo (4B) model + 5Hz LM thinking mode. Free API key from acemusic.ai/api-key. No GPU required.
- modal — Self-hosted ACE-Step 2B Turbo on Modal. Requires
MODAL_MUSIC_GEN_ENDPOINT_URL. - runpod — Self-hosted ACE-Step 2B Turbo on RunPod. Requires
RUNPOD_ACESTEP_ENDPOINT_ID.
Setup
# acemusic (recommended — free, best quality, no GPU)
echo "ACEMUSIC_API_KEY=your_key" >> .env
# Get key at https://acemusic.ai/api-key
# Self-hosted (optional fallback)
python tools/music_gen.py --setup # RunPod
modal deploy docker/modal-music-gen/app.py # Modal
Quick Reference
# Basic generation (uses acemusic XL Turbo by default)
python tools/music_gen.py --prompt "Upbeat tech corporate" --duration 60 --output bg.mp3
# Generate 4 variations, pick the best
python tools/music_gen.py --prompt "Calm ambient piano" --duration 30 --variations 4 --output ambient.mp3
# Fast mode (disable thinking)
python tools/music_gen.py --no-thinking --prompt "Quick draft" --duration 30 --output draft.mp3
# With musical control
python tools/music_gen.py --prompt "Calm ambient piano" --duration 30 --bpm 72 --key "D Major" --output ambient.mp3
# Scene presets (video production)
python tools/music_gen.py --preset corporate-bg --duration 60 --output bg.mp3
python tools/music_gen.py --preset tension --duration 20 --output problem.mp3
python tools/music_gen.py --preset cta --brand digital-samba --duration 15 --output cta.mp3
# Vocals with lyrics
python tools/music_gen.py --prompt "Indie pop jingle" --lyrics "[verse]\nBuild it better\nShip it faster" --duration 30 --output jingle.mp3
# Cover / style transfer
python tools/music_gen.py --cover --reference theme.mp3 --prompt "Jazz piano version" --duration 60 --output jazz_cover.mp3
# Repaint a weak section
python tools/music_gen.py --repaint --input track.mp3 --repaint-start 15 --repaint-end 25 --prompt "Guitar solo" --output fixed.mp3
# Continue from existing audio
python tools/music_gen.py --continuation --input track.mp3 --prompt "Continue with jazz piano" --output extended.mp3
# Stem extraction
python tools/music_gen.py --extract vocals --input mixed.mp3 --output vocals.mp3
# Fall back to self-hosted
python tools/music_gen.py --cloud modal --prompt "Background music" --duration 60 --output bg.mp3
Fixing "Samey" Output
If generated music sounds repetitive or lacks variety, try these in order:
- Use acemusic cloud (default) — the XL Turbo 4B model is significantly more capable than the 2B model on Modal/RunPod
- Keep thinking mode on (default for acemusic) — the 5Hz LM enriches sparse prompts into detailed musical descriptions
- Generate variations —
--variations 4generates 4 takes, pick the best - Use stochastic inference —
--infer-method sdeadds randomness (same seed gives different results) - Vary BPM and key across scenes — don't use the same preset for every scene
- Write sparser prompts — "Upbeat indie rock" gives the model more creative freedom than a hyper-detailed description
- Vary seeds — omit
--seedto let each generation be unique
Creating a Song (Step by Step)
1. Instrumental background track (simplest)
python tools/music_gen.py --prompt "Upbeat indie rock, driving drums, jangly guitar" --duration 60 --bpm 120 --key "G Major" --output track.mp3
2. Song with vocals and lyrics
Write lyrics in a temp file or pass inline. Use structure tags to control song sections.
# Write lyrics to a file first (recommended for longer songs)
cat > /tmp/lyrics.txt << 'LYRICS'
[Verse 1]
Walking through the morning light
Coffee in my hand feels right
Another day to build and dream
Nothing's ever what it seems
[Chorus - anthemic]
WE KEEP MOVING FORWARD
Through the noise and doubt
We keep moving forward
That's what it's about
[Verse 2]
Screens are glowing late at night
Shipping code until it's right
The deadline's close but so are we
Almost there, just wait and see
[Chorus - bigger]
WE KEEP MOVING FORWARD
Through the noise and doubt
We keep moving forward
That's what it's about
[Outro - fade]
(Moving forward...)
LYRICS
# Generate the song
python tools/music_gen.py \
--prompt "Upbeat indie rock anthem, male vocal, driving drums, electric guitar, studio polish" \
--lyrics "$(cat /tmp/lyrics.txt)" \
--duration 60 \
--bpm 128 \
--key "G Major" \
--output my_song.mp3
3. Repaint a weak section
If the chorus sounds weak, regenerate just that section:
python tools/music_gen.py --repaint --input my_song.mp3 --repaint-start 20 --repaint-end 35 --prompt "Powerful anthemic chorus, big drums" --output fixed.mp3
4. Continue/extend a track
python tools/music_gen.py --continuation --input my_song.mp3 --prompt "Continue with gentle acoustic outro" --output extended.mp3
Key tips for good results
- Caption = overall style (genre, instruments, mood, production quality)
- Lyrics = temporal structure (verse/chorus flow, vocal delivery)
- UPPERCASE in lyrics = high vocal intensity
- Parentheses = background vocals: "We rise (together)"
- Keep 6-10 syllables per line for natural rhythm
- Don't describe the melody in the caption — describe the sound and feeling
- Use
--seedto lock randomness when iterating on prompt/lyrics
Controlling vocal gender
The model doesn't reliably follow "female vocal" or "male vocal" on its own. Use both of these together:
- In the prompt: Be explicit — "solo female singer, alto voice" or "female vocalist only, breathy intimate voice". Adding an artist reference helps (e.g., "Brandi Carlile style").
- In the lyrics: Add
[female vocal]tags before each section:
[female vocal]
[Verse 1]
Walking through the morning light...
[female vocal]
[Chorus - anthemic]
WE KEEP MOVING FORWARD...
Just saying "female vocal" in the prompt alone is often ignored. The combination of prompt + lyrics tags is what works.
Duets and vocal trading
For duets with male/female vocals trading verses, use both the prompt and per-section lyrics tags:
- Prompt: "duet, male and female vocals trading verses, warm harmonies on chorus"
- Lyrics: Tag each section with who sings it:
[Verse 1 - male vocal, storytelling]
First verse lyrics here...
[Chorus - male and female duet, harmonies]
Chorus lyrics here...
[Verse 2 - female vocal, wry]
Second verse lyrics here...
[Bridge - male vocal, spoken]
Spoken bridge...
[Bridge - female vocal, sung]
Sung response...
This reliably produces vocal trading between sections and harmonies on shared parts.
Scene Presets
| Preset | BPM | Key | Use Case |
|---|---|---|---|
corporate-bg | 110 | C Major | Professional background, presentations |
upbeat-tech | 128 | G Major | Product launches, tech demos |
ambient | 72 | D Major | Overview slides, reflective content |
dramatic | 90 | D Minor | Reveals, announcements |
tension | 85 | A Minor | Problem statements, challenges |
hopeful | 120 | C Major | Solution reveals, resolutions |
cta | 135 | E Major | Call to action, closing energy |
lofi | 85 | F Major | Screen recordings, coding demos |
Task Types
text2music (default)
Generate music from text prompt + optional lyrics.
cover
Style transfer from reference audio. Control blend with --cover-strength (0.0-1.0):
- 0.2 — Loose style inspiration (more creative freedom)
- 0.5 — Balanced style transfer
- 0.7 — Close to original structure (default)
- 1.0 — Maximum fidelity to source
extract
Stem separation — isolate individual tracks from mixed audio.
Tracks: vocals, drums, bass, guitar, piano, keyboard, strings, brass, woodwinds, other
repainting (acemusic only)
Regenerate a specific time segment within existing audio while preserving the rest.
python tools/music_gen.py --repaint --input track.mp3 --repaint-start 15 --repaint-end 25 --prompt "Guitar solo" --output fixed.mp3
continuation (acemusic only)
Extend existing audio by continuing from where it ends.
python tools/music_gen.py --continuation --input track.mp3 --prompt "Continue with jazz piano" --output extended.mp3
Prompt Engineering
Caption Writing — Layer Dimensions
Write captions by layering multiple descriptive dimensions rather than single-word descriptions.
Dimensions to include:
- Genre/Style: pop, rock, jazz, electronic, lo-fi, synthwave, orchestral
- Emotion/Mood: melancholic, euphoric, dreamy, nostalgic, intimate, tense
- Instruments: acoustic guitar, synth pads, 808 drums, strings, brass, piano
- Timbre: warm, crisp, airy, punchy, lush, polished, raw
- Era: "80s synth-pop", "modern indie", "classical romantic"
- Production: lo-fi, studio-polished, live recording, cinematic
- Vocal: breathy, powerful, falsetto, raspy, spoken word (or "instrumental")
Good: "Slow melancholic piano ballad with intimate female vocal, warm strings building to powerful chorus, studio-polished production" Bad: "Sad song"
Key Principles
- Specificity over vagueness — describe instruments, mood, production style
- Avoid contradictions — don't request "classical strings" and "hardcore metal" simultaneously
- Repetition reinforces priority — repeat important elements for emphasis
- Sparse captions = more creative freedom — detailed captions constrain the model
- Use metadata params for BPM/key — don't write "120 BPM" in the caption, use
--bpm 120
Lyrics Formatting
Structure tags (use in lyrics, not caption):
[Intro]
[Verse]
[Chorus]
[Bridge]
[Outro]
[Instrumental]
[Guitar Solo]
[Build]
[Drop]
[Breakdown]
Vocal control (prefix lines or sections):
[raspy vocal]
[whispered]
[falsetto]
[powerful belting]
[harmonies]
[ad-lib]
Energy indicators:
- UPPERCASE = high intensity ("WE RISE ABOVE")
- Parentheses = background vocals ("We rise (together)")
- Keep 6-10 syllables per line within sections for natural rhythm
Video Production Integration
Music for Scene Types
| Scene | Preset | Duration | Notes |
|---|---|---|---|
| Title | dramatic or ambient | 3-5s | Short, mood-setting |
| Problem | tension | 10-15s | Dark, unsettling |
| Solution | hopeful | 10-15s | Relief, optimism |
| Demo | lofi or corporate-bg | 30-120s | Non-distracting, matches demo length |
| Stats | upbeat-tech | 8-12s | Building credibility |
| CTA | cta | 5-10s | Maximum energy, punchy |
| Credits | ambient | 5-10s | Gentle fade-out |
Timing Workflow
- Plan scene durations first (from voiceover script)
- Generate music to match:
--duration <scene_seconds> - Music duration is precise (within 0.1s of requested)
- For background music spanning multiple scenes: generate one long track
Combining with Voiceover
Background music should be mixed at 10-20% volume in Remotion:
<Audio src={staticFile('voiceover.mp3')} volume={1} />
<Audio src={staticFile('bg-music.mp3')} volume={0.15} />
For music under narration: use instrumental presets (corporate-bg, ambient, lofi).
For music-forward scenes (title, CTA): can use higher volume or vocal tracks.
Brand Consistency
Use --brand <name> to load hints from brands/<name>/brand.json.
Use --cover --reference brand_theme.mp3 to create variations of a brand's sonic identity.
For consistent sound across a project: fix the seed (--seed 42) and vary only duration/prompt.
Advanced Parameters
| Flag | Default | Description |
|---|---|---|
--thinking | on (acemusic) | 5Hz LM enriches prompts and generates audio codes |
--no-thinking | - | Faster generation, skip LM reasoning |
--variations N | 1 | Generate N variations (1-8, acemusic only) |
--guidance-scale | 7.0 | Prompt adherence (1.0-15.0) |
--infer-method | ode | ode (deterministic) or sde (stochastic, more variety) |
--seed | random | Lock randomness for reproducibility |
Technical Details
- acemusic cloud: XL Turbo 4B DiT + 4B LM, best quality, ~5-15s per generation
- Modal/RunPod: Standard Turbo 2B DiT, no LM, ~2-3s per generation
- Output: 48kHz MP3/WAV/FLAC
- Duration range: 10-600 seconds
- BPM range: 30-300
When NOT to use ACE-Step
- Voice cloning — use Qwen3-TTS or ElevenLabs instead
- Sound effects — use ElevenLabs SFX (
tools/sfx.py) - Speech/narration — use voiceover tools, not music gen
- Stem extraction from video — extract audio first with FFmpeg, then use
--extract
GitHub 仓库
Frequently asked questions
What is the acestep skill?
acestep is a Claude Skill by digitalsamba. Skills package instructions and resources that Claude loads on demand, so Claude can perform acestep-related tasks without extra prompting.
How do I install acestep?
Use the install commands on this page: add acestep to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does acestep belong to?
acestep is in the Meta category, tagged ai.
Is acestep free to use?
Yes. acestep is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
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