Audio stem separation using Demucs (4-stem or 6-stem) and optional UVR ensemble. Uses the Python API entrypoint for clean error handling. GPU-accelerated, local-first.
Scanned 9/11/2026
Install to Claude Code
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---
name: create-stems
description: >
Audio stem separation using Demucs (4-stem or 6-stem) and optional UVR ensemble.
Uses the Python API entrypoint for clean error handling. GPU-accelerated, local-first.
allowed-tools: [Bash, Read, Write, Task]
triggers:
- separate stems
- stem separation
- demucs
- split audio
- extract vocals
- create stems
metadata:
short-description: "Stem separation (Demucs 6s + UVR)"
author: "Horus"
version: "0.1.0"
provides:
- create-stems
composes:
- learn-artist
- learn-voice
- discover-music
- task-monitor
- agentic-evals
disciplines:
- voice-audio
---
# create-stems
Audio stem separation using Demucs' Python API. Default model is `htdemucs_6s` which splits audio into 6 sources: vocals, drums, bass, other, guitar, piano.
## Usage
```bash
# 6-source separation (default)
./run.sh separate --mix song.wav --out ./stems
# Extract a specific instrument by name (auto-maps to Demucs source)
./run.sh separate --mix song.wav --out ./stems --instrument vocals
./run.sh separate --mix song.wav --out ./stems --instrument oud
./run.sh separate --mix song.wav --out ./stems --instrument piano
# Raw two-stems mode (if you know the Demucs source name)
./run.sh separate --mix song.wav --out ./stems --two-stems guitar
# 4-source with VRAM control
./run.sh separate --mix song.wav --out ./stems --model htdemucs --segment 12
# Quality mode (GPU recommended)
./run.sh separate --mix song.wav --out ./stems --shifts 2
# MP3 output
./run.sh separate --mix song.wav --out ./stems --mp3
# Low-VRAM mode
./run.sh separate --mix song.wav --out ./stems --segment 8 --no-cuda-mem-caching
```
## Instrument Mapping
Use `--instrument` with natural names. The skill maps them to the closest Demucs source:
| Instrument | Maps to (6s) | Notes |
|------------|-------------|-------|
| vocals, voice, singing | vocals | |
| drums, percussion | drums | |
| bass, upright bass, bass guitar | bass | |
| guitar, oud, lute, banjo, mandolin, sitar, ukulele, bouzouki | guitar | Plucked strings |
| piano, keyboard, keys, organ, synth, accordion, harpsichord | piano | Keyboard family |
| violin, cello, trumpet, sax, flute, strings, brass, woodwind | other | Orchestral/misc |
This means an agent can say `--instrument oud` and the skill determines the best extraction path (`--two-stems guitar` on `htdemucs_6s`).
## Models
| Model | Sources | Notes |
|-------|---------|-------|
| `htdemucs_6s` | 6 (vocals/drums/bass/other/guitar/piano) | Default. Best for full separation. |
| `htdemucs` | 4 (vocals/drums/bass/other) | Faster. Guitar+piano in "other". |
| `htdemucs_ft` | 4 (fine-tuned) | Higher quality 4-stem. |
## VRAM Tuning
| Flag | Effect |
|------|--------|
| `--segment N` | Split size (seconds). Smaller = less VRAM. Try 8-12 for 8GB cards. |
| `--overlap F` | Window overlap (default 0.25). Reduce for speed. |
| `--shifts N` | Random time-shift averaging. Higher = better quality, slower. |
| `--jobs N` | Parallel jobs. Increases RAM proportionally. |
| `--no-cuda-mem-caching` | Sets `PYTORCH_NO_CUDA_MEMORY_CACHING=1`. Helps with very low VRAM. |
## Output Structure
```
<out_dir>/
htdemucs_6s/
<track_name>/
vocals.wav
drums.wav
bass.wav
other.wav
guitar.wav
piano.wav
manifest.json
```
## Sanity Checks
```bash
./sanity.sh # Full environment check
```
## Hardware Requirements
| Component | Minimum | Recommended |
|-----------|---------|-------------|
| VRAM | 4GB (with --segment 8) | 8GB+ |
| RAM | 8GB | 16GB+ |
| Storage | 5GB (model cache) | 10GB+ |
## Integration
Used by:
- **create-music** - stem separation step in music creation pipeline
- **discover-music** - `youtube-stems` command delegates here
- **learn-artist** - vocal/instrument extraction for RVC training
## References
- [Demucs](https://github.com/facebookresearch/demucs)
- [python-audio-separator (UVR)](https://github.com/nomadkaraoke/python-audio-separator)
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