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create-stems

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.

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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
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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