inikolax/remiqora

★ 106⑂ 15

Local AI music studio unifying ACE-Step 1.5 and YuE2-3B in one Vue interface — text-to-music generation, stem separation, MIDI transcription, and LoRA fine-tuning, with a built-in multitrack DAW.

About inikolax/remiqora

inikolax/remiqora is an open-source project on GitHub, mainly written in Vue. Local AI music studio unifying ACE-Step 1.5 and YuE2-3B in one Vue interface — text-to-music generation, stem separation, MIDI transcription It currently holds 106 stars and 15 forks with 0 open issues, and was last pushed on an unknown date (repository created unknown).

Project Overview

AI Homed tracks it on the Today's Trending board, currently at rank #96 with 0 new stars today.

GitHub Repository Details

Repository inikolax/remiqora · default branch - · size 0 KB · watchers 0 · source: GitHub REST API and repository README

README

English · Русский

https://github.com/inikolax/remiqora/blob/HEAD/Remiqora

Remiqora

Made with AI. Made by you.

A local, GPU-powered music generation and production studio — one interface for ACE-Step 1.5 and YuE2-3B, with a built-in multitrack DAW.

🚧 Actively in development — expect breaking changes, bugs, and rough edges. Not a stable release yet.

https://github.com/inikolax/remiqora/blob/HEAD/Status https://github.com/inikolax/remiqora/blob/HEAD/License https://github.com/inikolax/remiqora/blob/HEAD/Platform https://github.com/inikolax/remiqora/blob/HEAD/GPU https://github.com/inikolax/remiqora/blob/HEAD/Stack https://github.com/inikolax/remiqora/blob/HEAD/UI languages https://github.com/inikolax/remiqora/blob/HEAD/Support on Ko-fi

https://github.com/inikolax/remiqora/blob/HEAD/Remiqora — made with AI, made by you

Why · What's inside · ACE-Step · YuE2 · LoRA · DAW · Built with · License · Installation

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Why this exists

ACE-Step and YuE2 are two independent music generation engines, each with its own web UI, its own result-storage format, and its own process that has to be started and stopped by hand. They typically cannot run simultaneously on a single consumer GPU. Remiqora solves this with a single layer on top:

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What's inside

| Module | What it does | |---|---| | ACE-Step 1.5 | Fast generation from text/style tags, covers, section repainting, extracting/adding parts on top of a reference track. | | YuE2-3B | Full-length track generation with CoT score planning (a symbolic ABC plan before the audio). | | SheetSage2 | Extracts melody and harmony from a reference track into ABC notation — used as YuE2's input. | | LoRA training | Dataset → auto-labeling → preprocessing → training → export — the whole ACE-Step fine-tuning pipeline for your own voice/style, in the browser. | | Demucs | Splits any track into 4 stems: vocals, drums, bass, other. | | MuScriptor | Transcribes audio (the full mix or a single stem) into MIDI notes. | | Built-in DAW | A multitrack timeline editor for assembling tracks/stems into a final mix: an effects rack on every channel, auto-BPM and time-stretch, WAV/MP3 export. |

The interface is fully bilingual (Russian/English, switcher in the header).

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ACE-Step: generation

ACE-Step: generation and track feed

Two input modes: “Simple” — a single text description the model uses to infer both style and lyrics on its own; and “Custom” — style tags with autocomplete plus lyrics with structure markup ([Verse]/[Chorus]/[Bridge]) and performance annotations ((whisper), (falsetto)), or an “Instrumental” checkbox.

Attaching a reference track unlocks 5 remix scenarios:

Plus: 10–300 s duration, batch of 1/2/4 variants, mp3/wav/flac formats, advanced parameters (BPM, key, time signature, vocal language, inference steps, guidance scale, seed), LoRA adapter support with adjustable strength, local presets, and a "Stop all" button for bulk job cancellation.

YuE2 and SheetSage2: generation

YuE2: generation and track feed

Three CoT (Chain-of-Thought) modes: off — straight to audio; melody — the arrangement is built around a given melody (ABC); full — the model first builds a symbolic plan (melody + chords), then generates the audio.

SheetSage2 lets you upload a reference track and pull its melody into ABC notation, right in the form, with one click — editable by hand afterwards. Beyond that: q8_0/q4_0 precision, batch of 1–4, a full set of sampling parameters for audio generation and the ABC planner separately, local presets, and viewing/reusing the ABC score of an already-generated track.

LoRA training (ACE-Step)

LoRA training

The full ACE-Step fine-tuning pipeline on your own dataset, no console required:

1. Dataset — upload audio files straight from the browser (drag & drop) or point at an existing server folder, a trigger word, an "all tracks are instrumental" flag. 2. Automatic labeling — LLM-generated description, genre, BPM/key, lyrics transcription/reformatting. 3. Review and edit — a table of every sample where you can fix the description/genre/tags before training. 4. Preprocessing — converts labeled samples into tensors. 5. Training — LoRA rank/alpha/dropout, learning rate, epochs, batch size, FP8, gradient checkpointing, live progress with an ETA and a TensorBoard link. 6. Export and registry — the finished adapter is immediately added to the LoRA list on the generation form.

Stem separation (Demucs)

Stem separation

One click splits any saved track into 4 isolated stems (Demucs htdemucs), with a progress bar, a separate player and download per stem, and the option to redo or delete. Runs alongside the active generation model (without stopping it), sharing a GPU lock. The "Open in editor" button allows you to instantly send all 4 stems into a new built-in DAW project for further mixdown.

MIDI transcription (MuScriptor)

MIDI transcription

Transcribes the full mix, or any already-separated stem, into MIDI. Technically this isn't a separate process — it's a model loaded into the already-running YuE2 server, so transcription requires YuE2 to be the active model. Result: a built-in Web Audio synth player, a mini piano roll, a note count and BPM readout, and .mid download.

Built-in DAW

Editor: a four-stem project on the timeline

Any number of tracks, onto which you can add anything from the shared library (a full mix, a single stem, a file uploaded from disk) — via a picker dialog or by dragging a file straight onto a track. The quickest way in is through stems: the "Open in editor" button on the stems panel creates a ready-made four-track project (vocals, drums, bass, other).

Timeline and clips

Channels and effects

Effects rack on the vocals channel

Help

Built-in editor help

The "?" button in the toolbar opens built-in help: a list of hotkeys, mouse controls, and short tips on Loop and Magnet.

Project and export

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Architecture

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Built with

Remiqora is a UI and orchestrator on top of third-party inference engines. Their code isn't vendored into this repository — only small functional patches (external/patches/) on top of the originals:

| Project | What's used | License | |---|---|---| | ACE-Step-1.5 | Text/style-driven music generation engine, LoRA training | MIT | | audio.cpp (dev branch) | YuE2 (generation), SheetSage2 (melody extraction), MuScriptor (MIDI transcription) | Apache-2.0 | | Demucs | Stem separation (htdemucs) | MIT |

Patch details and exact base commits are in external/patches/README.md.

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License & liability for generated content

Remiqora's own code (this repository) is MIT-licensed. That covers the UI and orchestrator only — it is a separate thing from the license of a track you generate with it. Remiqora is an orchestrator, not a generator with its own model — all audio is produced by third-party engines (ACE-Step 1.5, YuE2-3B, and the SheetSage2/MuScriptor tools built on top of them). Because of that:

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📦 Installation

Step 0: build tools

setup_prereqs.bat

Via winget (built into Windows 10/11), installs Git, Python, uv, Node.js, CMake, ffmpeg, plus Visual Studio Build Tools (C++ workload) and the CUDA Toolkit — those are large, need admin rights, and can take a while. setup_prereqs.bat -SkipHeavy installs only the small, fast tools, leaving Build Tools/CUDA for you to install manually from links the script prints.

The NVIDIA GPU driver is deliberately left out — install it by hand from nvidia.com/drivers for your card: silently swapping a video driver on someone else's machine is risky (it can blank the screen and usually needs a reboot on your schedule, not the script's).

After installing, close the terminal and open a new one so PATH picks up the freshly installed tools.

On macOS (Apple Silicon):

./setup_prereqs.sh
Via Homebrew, installs Git, Python, uv, Node.js, CMake, ffmpeg and Ninja. No separate GPU driver step: Metal is built into macOS. CMake/Ninja are only actually used by the --from-source build path below — the default YuE2 setup needs no compiler at all.

Step 1: generation engines

setup_models.bat

The script: 1. Clones ace-step/ACE-Step-1.5 (MIT) and 0xShug0/audio.cpp (Apache-2.0, dev branch — YuE2 support is dev-only for now) into external/. 2. Applies a small patch to ACE-Step (a task-cancellation API; audio.cpp needs no patch, see external/patches/README.md) — without the upstream custom web-uis, which aren't needed. 3. Runs uv sync for ACE-Step and builds audiocpp_server (CUDA release, yue2,sheetsage2,muscriptor models) for audio.cpp. 4. Downloads the YuE2/SheetSage2/MuScriptor GGUF weights (~10 GB) via audio.cpp's tools/model_manager_v2.py. 5. Sets up a demucs uv project in external/Demucs for stem separation, routed at PyTorch's cu128 wheel index so it gets a CUDA build (a plain uv add demucs would silently resolve a CPU-only torch wheel instead). 6. Creates backend/.env with paths to the freshly cloned repositories, including FFMPEG_BIN_DIR — auto-detected from ffmpeg's winget install (setup_prereqs.bat), even right after installing it in the same terminal, before a new one would pick it up on PATH.

ACE-Step's own weights don't need a separate download — acestep-api pulls them from HuggingFace/ModelScope on first request, the same way its Gradio UI does.

The script is idempotent — safe to re-run (the -SkipBuild / -SkipWeights flags skip the corresponding steps). It expects git, uv, Python 3, CMake, the CUDA Toolkit and Visual Studio Build Tools (C++ workload) to already be installed — if any is missing, that step is simply skipped with a hint on what to install.

After that, the only manual step left is checking CUDA_BIN_DIR in backend/.env (FFMPEG_BIN_DIR is filled in automatically — unless ffmpeg wasn't found at all, in which case the script says so and it needs setting by hand).

Hard machine requirements the script can't remove: Windows, a CUDA-capable NVIDIA GPU (tested on an RTX 4080 16 GB), and an installed video driver.

On macOS (Apple Silicon):

./setup_models.sh
Adapted for macOS, with one difference from the Windows steps above: by default, audiocpp_server is installed from audio.cpp's own prebuilt macOS/Metal release (a pinned tag, sha256-verified before extracting) — no compiler needed at all, unlike the Windows path, which always builds from source since there's no prebuilt CUDA release. The Demucs uv project also isn't routed at a CUDA wheel index — a plain torch dependency already resolves an MPS-capable wheel on darwin/arm64, same as ACE-Step-1.5's own pyproject.toml does. The written backend/.env has no CUDA_BIN_DIR — there's no CUDA toolkit on this path.

Pass --from-source to build audio.cpp from the same pinned dev commit Windows uses instead of downloading the release (useful if the release lags behind a dev-only fix, or on Intel Macs, which the prebuilt asset doesn't cover) — that path needs full Xcode.app (not just the Command Line Tools) for its Metal shader compiler; setup_prereqs.sh prints exact steps if it's missing. --skip-build / --skip-weights mirror -SkipBuild / -SkipWeights. Otherwise it expects git, uv and Python 3 to already be installed (cmake too, for --from-source).

Hard machine requirements this path can't remove: macOS, Apple Silicon (M-series) for the default prebuilt path (Intel needs --from-source). Tested on a MacBook Air, Apple M5, 24 GB RAM — including a from-scratch run against a machine with no prior Homebrew packages or project state, all the way through generating audio with YuE2 on the Metal backend. This path is newer and less exercised than the Windows/CUDA one — expect it to be slower (Metal instead of CUDA). --from-source in particular may need occasional manual fixing up (a bumped commit pin) if audio.cpp's dev branch drifts upstream; the default release-based path is pinned to a fixed tag instead, so it doesn't drift on its own.

Step 2: run

dev.bat
Brings up the backend (port 9000) and the frontend with Hot Module Replacement (Vite, port 5173), creates backend/.venv and frontend/node_modules on first run, and opens a browser at http://localhost:5173.

For production mode — build the SPA and serve everything from a single port:

prod_run.bat
Builds the client via npm run build and serves the finished SPA bundle together with the API at http://127.0.0.1:9000.

Stem separation's demucs uv project is set up by setup_models.bat above; the htdemucs weights themselves download automatically on first use.

On macOS: ./dev.sh and ./prod_run.sh are the equivalents — same behavior, except the backend/frontend run as background jobs of the script itself (stop both with Ctrl+C) rather than in separate terminal windows.

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⚙ Configuration (.env)

Settings live in backend/.env (template: backend/.env.example; setup_models.bat creates it automatically with paths to the cloned repositories):

ACE_STEP_DIR=E:\AI\ACE\ACE-Step-1.5
YUE2_DIR=E:\AI\YuE2-3B
DEMUCS_DIR=E:\AI\Demucs
FFMPEG_BIN_DIR=E:\AI\ACE\tools\ffmpeg-shared\ffmpeg-master-latest-win64-gpl-shared\bin
CUDA_BIN_DIR=C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\bin
---

Known limitations

GitHub Stars & Activity

106Stars
15Forks
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GitHub stars106
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