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+# --- Cloned submodules (restored by init.bat) ---
+ace-step/
+foundation1/
+separator/
+
+# --- Python environments ---
+.venv/
+
+# --- Generated and uploaded files ---
+outputs/
+uploads/
+
+# --- Python cache ---
+__pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+
+# --- Distribution / packaging ---
+*.egg-info/
+dist/
+build/
+
+# --- Environment variables ---
+.env
+.env.*
+
+# --- Editor / OS ---
+.vscode/
+.idea/
+*.DS_Store
+Thumbs.db
+
+# --- Docs ---
+docs/
+
+# --- Claude ---
+.claude/
+CLAUDE.md
+
+# --- Utility Scripts ---
+_write_*.py
@@ -0,0 +1,633 @@
+# K.G.One
+
+A unified REST API gateway that exposes two AI music-generation models behind a single consistent interface.
+
+| Service | Model | Output | Port |
+|---------|-------|--------|------|
+| **Full-song** | [ACE-Step 1.5](https://github.com/ace-step/ACE-Step-1.5) | Full-length music (MP3/WAV/FLAC) | 8001 (internal) |
+| **Clip** | [Foundation-1](https://huggingface.co/RoyalCities/Foundation-1) | Short instrument clips — WAV **and** MIDI | 8002 (internal) |
+| **Separator** | [python-audio-separator](https://github.com/nomadkaraoke/python-audio-separator) | Separated stems (Vocals, Instrumental, etc.) as MP3 | CLI (no port) |
+| **Gateway** | K.G.One | Routes all requests, enforces GPU mutex | **8000** (public) |
+
+Because all services require a GPU, only one is active at a time. You explicitly switch via `POST /v1/models/load` before generating or separating.
+
+---
+
+## Requirements
+
+| Requirement | Notes |
+|-------------|-------|
+| Windows 10/11 | `init.bat` is Windows-only; Linux/macOS support can be added |
+| NVIDIA GPU | CUDA required for both models |
+| [Git](https://git-scm.com/downloads) | For cloning sub-projects |
+| [uv](https://docs.astral.sh/uv/getting-started/installation/) | Python environment manager |
+| Python 3.10 | Required by Foundation-1; ACE-Step works with 3.10+ |
+
+---
+
+## Setup
+
+### 1. Initialize
+
+Run `init.bat` from the project root. It will:
+
+1. Read pinned commit hashes from `submodules.json`
+2. Clone ACE-Step 1.5 into `ace-step/`
+3. Clone Foundation-1 into `foundation1/`
+4. Create three isolated Python environments:
+   - `.venv` — the gateway (fastapi, httpx)
+   - `ace-step/.venv` — ACE-Step and its CUDA dependencies
+   - `foundation1/.venv` — Foundation-1 and its dependencies (scipy==1.8.1)
+5. Create output directories under `outputs/`
+
+```bat
+init.bat
+```
+
+> **Note:** ACE-Step downloads large CUDA packages. Expect 10–20 minutes on the first run.
+
+### 2. Download model weights
+
+**ACE-Step** downloads weights automatically on first start via its built-in model downloader.
+
+**Foundation-1** downloads from HuggingFace on first start (handled by `get_pretrained_model`). Alternatively, set environment variables to point to a local checkpoint:
+
+```bat
+set FOUNDATION1_CKPT_PATH=C:\path\to\foundation1.safetensors
+set FOUNDATION1_CONFIG_PATH=C:\path\to\model_config.json
+```
+
+### 3. Start the gateway
+
+```bat
+.venv\Scripts\python.exe main.py
+```
+
+The gateway starts on `http://localhost:8000`. Interactive API docs are available at `http://localhost:8000/docs`.
+
+### 4. Load a model and generate
+
+```bash
+# Load Foundation-1
+curl -X POST http://localhost:8000/v1/models/load \
+  -H "Content-Type: application/json" \
+  -d '{"model": "clip"}'
+
+# Submit a generation
+curl -X POST http://localhost:8000/v1/clip/generate \
+  -H "Content-Type: application/json" \
+  -d '{"prompt": "Piano, Rhodes, Warm, 8 Bars, 120 BPM, C major", "bars": 8, "bpm": 120}'
+```
+
+### Upgrading a pinned dependency
+
+Edit the `commit` field in `submodules.json`, delete the corresponding subfolder, then re-run `init.bat`.
+
+---
+
+## Project structure
+
+```
+K.G.One/
+├── submodules.json          # Pinned commits — source of truth for dependency versions
+├── init.bat                 # Windows bootstrap script
+├── pyproject.toml           # Gateway Python project
+├── main.py                  # Gateway FastAPI application (port 8000)
+├── services/
+│   ├── model_manager.py     # GPU mutex — starts/stops sub-service subprocesses
+│   ├── acestep_client.py    # ACE-Step connection config
+│   ├── foundation1_client.py# Foundation-1 connection config
+│   └── separator_runner.py  # Runs audio-separator CLI per-request, manages tasks
+├── foundation1_server/
+│   └── server.py            # Foundation-1 FastAPI wrapper (port 8002)
+├── ace-step/                # Cloned by init.bat — ACE-Step 1.5 source
+├── foundation1/             # Cloned by init.bat — RC-stable-audio-tools source
+├── separator/               # Cloned by init.bat — python-audio-separator source + venv
+├── outputs/
+│   ├── clip/                # Foundation-1 generated WAV + MIDI files
+│   ├── fullsong/            # (reserved for ACE-Step output references)
+│   └── separator/           # Separated stem MP3 files
+└── uploads/
+    └── separator/           # Temporary upload storage (auto-deleted after processing)
+```
+
+---
+
+## API Reference
+
+### System
+
+| Method | URL | Description |
+|--------|-----|-------------|
+| `GET` | `/health` | Gateway health check |
+| `POST` | `/v1/models/load` | Load a model onto the GPU (unloads the active one first) |
+| `GET` | `/v1/models/status` | Return the currently active model |
+
+---
+
+#### `GET /health`
+
+**Response**
+```json
+{
+  "status": "ok",
+  "active_model": "clip"
+}
+```
+
+`active_model` is `null` when no model is loaded.
+
+---
+
+#### `POST /v1/models/load`
+
+Loads a model onto the GPU. If a different model is currently active, it is shut down first.
+
+For `"fullsong"` and `"clip"` this call **blocks** until the sub-service reports healthy (model weights loaded). Expect 30–120 seconds on first run.
+
+For `"separator"` it only terminates the currently running model to free VRAM — no persistent process is started. Returns immediately.
+
+**Request**
+
+| Field | Type | Required | Values |
+|-------|------|----------|--------|
+| `model` | string | yes | `"clip"`, `"fullsong"`, or `"separator"` |
+
+```json
+{ "model": "separator" }
+```
+
+**Response**
+```json
+{
+  "active_model": "separator",
+  "status": "ready"
+}
+```
+
+**Error — unknown model (400)**
+```json
+{ "detail": "Unknown model 'foo'. Must be 'fullsong', 'clip', or 'separator'." }
+```
+
+---
+
+#### `GET /v1/models/status`
+
+**Response**
+```json
+{
+  "active_model": "fullsong"
+}
+```
+
+---
+
+### Full-song generation (ACE-Step 1.5)
+
+> All `/v1/fullsong/*` endpoints return HTTP 503 if `fullsong` is not the active model.
+
+| Method | URL | Description |
+|--------|-----|-------------|
+| `POST` | `/v1/fullsong/generate` | Submit a full-song generation task |
+| `GET` | `/v1/fullsong/result/{task_id}` | Poll task status and retrieve result |
+| `GET` | `/v1/fullsong/audio?path={path}` | Download a generated audio file |
+
+---
+
+#### `POST /v1/fullsong/generate`
+
+Proxied to ACE-Step's `/release_task`. Accepts the full ACE-Step generation parameter set.
+
+**Request** (key fields — see [ACE-Step API docs](https://github.com/ace-step/ACE-Step-1.5/blob/main/docs/en/API.md) for the complete spec)
+
+| Field | Type | Default | Description |
+|-------|------|---------|-------------|
+| `caption` | string | required | Musical style/description |
+| `lyrics` | string | `""` | Song lyrics (`[verse]`, `[chorus]` tags supported) |
+| `duration` | number | `60` | Duration in seconds |
+| `instrumental` | boolean | `false` | Generate without vocals |
+| `bpm` | number | `null` | Target BPM (null = auto) |
+| `inference_steps` | integer | `8` | Diffusion steps (8 = turbo, 50 = full quality) |
+| `guidance_scale` | number | `7.0` | Classifier-free guidance scale |
+| `seed` | integer | `-1` | `-1` for random |
+| `audio_format` | string | `"mp3"` | `"mp3"`, `"wav"`, `"flac"`, `"opus"` |
+
+```json
+{
+  "caption": "upbeat electronic dance, synthesizer, four-on-the-floor kick, 128 BPM",
+  "lyrics": "[verse]\nLights are flashing\nBeats are crashing\n[chorus]\nDance all night",
+  "duration": 90,
+  "instrumental": false,
+  "inference_steps": 8,
+  "guidance_scale": 7.0,
+  "seed": -1,
+  "audio_format": "mp3"
+}
+```
+
+**Response**
+```json
+{
+  "data": {
+    "task_id": "a3f2c1d8-9e4b-4a7f-b012-3c5d6e7f8a9b",
+    "status": "queued",
+    "queue_position": 1
+  },
+  "code": 200,
+  "error": null,
+  "timestamp": 1744300000000
+}
+```
+
+---
+
+#### `GET /v1/fullsong/result/{task_id}`
+
+Poll until `status` is `"finished"`. Recommended interval: 2–5 seconds.
+
+**Path parameter:** `task_id` from the generate response.
+
+**Response — pending**
+```json
+{
+  "data": [
+    {
+      "task_id": "a3f2c1d8-9e4b-4a7f-b012-3c5d6e7f8a9b",
+      "status": "running",
+      "progress": 0.4
+    }
+  ],
+  "code": 200
+}
+```
+
+**Response — finished**
+```json
+{
+  "data": [
+    {
+      "task_id": "a3f2c1d8-9e4b-4a7f-b012-3c5d6e7f8a9b",
+      "status": "finished",
+      "audio_path": "/tmp/acestep/outputs/a3f2c1d8.mp3",
+      "duration": 90.2,
+      "bpm": 128
+    }
+  ],
+  "code": 200
+}
+```
+
+Use `audio_path` as the `path` query parameter when calling `/v1/fullsong/audio`.
+
+---
+
+#### `GET /v1/fullsong/audio?path={path}`
+
+Download the generated audio file. Returns binary audio data.
+
+**Query parameter:** `path` — the `audio_path` value from the result response.
+
+**Response:** Binary audio file (`audio/mpeg`, `audio/wav`, etc. depending on format).
+
+---
+
+### Clip generation (Foundation-1)
+
+> All `/v1/clip/*` endpoints return HTTP 503 if `clip` is not the active model.
+
+Foundation-1 generates short instrument clips (4 or 8 bars) from a structured text prompt, producing both a WAV audio file and a MIDI transcription simultaneously.
+
+| Method | URL | Description |
+|--------|-----|-------------|
+| `POST` | `/v1/clip/generate` | Submit a clip generation task |
+| `GET` | `/v1/clip/result/{task_id}` | Poll task status and retrieve file URLs |
+| `GET` | `/v1/clip/audio/{filename}` | Download the generated WAV file |
+| `GET` | `/v1/clip/midi/{filename}` | Download the generated MIDI file |
+
+---
+
+#### `POST /v1/clip/generate`
+
+**Request**
+
+| Field | Type | Default | Description |
+|-------|------|---------|-------------|
+| `prompt` | string | required | Comma-separated descriptor tags (see prompt guide below) |
+| `negative_prompt` | string | `""` | Tags to avoid |
+| `bars` | integer | `4` | Clip length: `4` or `8` |
+| `bpm` | integer | `140` | Tempo in BPM (e.g. 100, 110, 120, 128, 130, 140, 150) |
+| `note` | string | `"C"` | Root note: `A` through `G#` |
+| `scale` | string | `"minor"` | `"major"` or `"minor"` |
+| `steps` | integer | `75` | Diffusion steps (1–500; 75 is a good balance) |
+| `cfg_scale` | number | `7.0` | Classifier-free guidance (0–25) |
+| `seed` | integer | `-1` | `-1` for random |
+| `sampler_type` | string | `"dpmpp-2m-sde"` | Sampler algorithm |
+| `sigma_min` | number | `0.03` | Minimum noise sigma |
+| `sigma_max` | number | `500.0` | Maximum noise sigma |
+| `cfg_rescale` | number | `0.0` | CFG rescale factor (0–1) |
+
+**Prompt format**
+
+Foundation-1 prompts are structured tag lists. Key components:
+
+```
+[Instrument family], [Sub-type], [Timbre descriptors], [FX], [Bars], [BPM], [Key]
+```
+
+Example prompts:
+- `"Piano, Rhodes Piano, Warm, Bright, Lush, 8 Bars, 120 BPM, C major"`
+- `"Bass, FM Bass, Acid, Gritty, Thick, 8 Bars, 140 BPM, E minor"`
+- `"Synth, Wavetable Synth, Pad, Wide, Silky, 4 Bars, 128 BPM, A minor"`
+
+```json
+{
+  "prompt": "Bass, FM Bass, Acid, Gritty, Wide, Thick, 8 Bars, 140 BPM, E minor",
+  "bars": 8,
+  "bpm": 140,
+  "note": "E",
+  "scale": "minor",
+  "steps": 75,
+  "cfg_scale": 7.0,
+  "seed": -1,
+  "sampler_type": "dpmpp-2m-sde"
+}
+```
+
+**Response**
+```json
+{
+  "task_id": "b7e3a921-4f1c-4d8e-a023-9d6c5e8f1b2a"
+}
+```
+
+---
+
+#### `GET /v1/clip/result/{task_id}`
+
+Poll until `status` is `"complete"`. Recommended interval: 2–5 seconds.
+
+**Path parameter:** `task_id` from the generate response.
+
+**Response — pending / running**
+```json
+{
+  "task_id": "b7e3a921-4f1c-4d8e-a023-9d6c5e8f1b2a",
+  "status": "running",
+  "error": null
+}
+```
+
+**Response — complete**
+```json
+{
+  "task_id": "b7e3a921-4f1c-4d8e-a023-9d6c5e8f1b2a",
+  "status": "complete",
+  "wav_url": "/v1/clip/audio/Bass_FM_Bass_Acid_140BPM_E_minor_42.wav",
+  "midi_url": "/v1/clip/midi/Bass_FM_Bass_Acid_140BPM_E_minor_42.mid"
+}
+```
+
+**Response — error**
+```json
+{
+  "task_id": "b7e3a921-4f1c-4d8e-a023-9d6c5e8f1b2a",
+  "status": "error",
+  "error": "Generation failed — check server logs."
+}
+```
+
+---
+
+#### `GET /v1/clip/audio/{filename}`
+
+Download the generated WAV file (32 kHz stereo).
+
+**Path parameter:** `filename` — the filename portion of `wav_url` from the result response.
+
+**Response:** Binary WAV file (`audio/wav`).
+
+```bash
+curl http://localhost:8000/v1/clip/audio/Bass_FM_Bass_Acid_140BPM_E_minor_42.wav \
+  --output clip.wav
+```
+
+---
+
+#### `GET /v1/clip/midi/{filename}`
+
+Download the MIDI transcription derived from the generated audio (via [basic-pitch](https://github.com/spotify/basic-pitch)).
+
+**Path parameter:** `filename` — the filename portion of `midi_url` from the result response.
+
+**Response:** Binary MIDI file (`audio/midi`).
+
+```bash
+curl http://localhost:8000/v1/clip/midi/Bass_FM_Bass_Acid_140BPM_E_minor_42.mid \
+  --output clip.mid
+```
+
+---
+
+### Stem separation (python-audio-separator)
+
+> All `/v1/separator/*` endpoints return HTTP 503 if `separator` is not the active model.
+
+Separates an uploaded audio file into individual stems (vocals, instrumental, etc.) using UVR models. Outputs are always MP3.
+
+| Method | URL | Description |
+|--------|-----|-------------|
+| `POST` | `/v1/separator/separate` | Upload audio + select model → task ID |
+| `GET` | `/v1/separator/result/{task_id}` | Poll task status and retrieve output filenames |
+| `GET` | `/v1/separator/download/{filename}` | Download a separated stem file |
+
+---
+
+#### `POST /v1/separator/separate`
+
+Accepts a `multipart/form-data` body.
+
+**Form fields**
+
+| Field | Type | Required | Description |
+|-------|------|----------|-------------|
+| `file` | file | yes | Audio file to separate (MP3, WAV, FLAC, …) |
+| `model_filename` | string | yes | One of the three supported models (see below) |
+
+**Supported models**
+
+| `model_filename` | Stems produced |
+|-----------------|----------------|
+| `UVR-MDX-NET-Inst_HQ_3.onnx` | 2 — Vocals, Instrumental |
+| `MDX23C-8KFFT-InstVoc_HQ.ckpt` | 2 — Vocals, Instrumental |
+| `htdemucs_6s.yaml` | 6 — bass, drums, guitar, other, piano, vocals |
+
+Models are downloaded automatically by `audio-separator` on first use.
+
+```bash
+curl -X POST http://localhost:8000/v1/separator/separate \
+  -F "file=@song.mp3" \
+  -F "model_filename=UVR-MDX-NET-Inst_HQ_3.onnx"
+```
+
+**Response**
+```json
+{ "task_id": "c4e2f891-3b1a-4d7e-b023-8e5f6a9c2d1b" }
+```
+
+---
+
+#### `GET /v1/separator/result/{task_id}`
+
+Poll until `status` is `"complete"`. Recommended interval: 2–5 seconds. Separation typically takes 10–60 seconds depending on file length and model.
+
+**Response — running**
+```json
+{
+  "task_id": "c4e2f891-3b1a-4d7e-b023-8e5f6a9c2d1b",
+  "status": "running"
+}
+```
+
+**Response — complete**
+```json
+{
+  "task_id": "c4e2f891-3b1a-4d7e-b023-8e5f6a9c2d1b",
+  "status": "complete",
+  "files": [
+    "c4e2f891_(Instrumental)_UVR-MDX-NET-Inst_HQ_3.mp3",
+    "c4e2f891_(Vocals)_UVR-MDX-NET-Inst_HQ_3.mp3"
+  ]
+}
+```
+
+**Response — error**
+```json
+{
+  "task_id": "c4e2f891-3b1a-4d7e-b023-8e5f6a9c2d1b",
+  "status": "error",
+  "error": "Separation failed — check server logs."
+}
+```
+
+---
+
+#### `GET /v1/separator/download/{filename}`
+
+Download a stem MP3 file. `filename` is one of the entries from the `files` list in the result response.
+
+**Response:** Binary MP3 file (`audio/mpeg`) with `Content-Disposition: attachment`.
+
+```bash
+curl "http://localhost:8000/v1/separator/download/c4e2f891_(Vocals)_UVR-MDX-NET-Inst_HQ_3.mp3" \
+  --output vocals.mp3
+```
+
+---
+
+## Typical workflows
+
+### Generate a full song
+
+```bash
+# 1. Load ACE-Step
+curl -X POST http://localhost:8000/v1/models/load \
+  -H "Content-Type: application/json" \
+  -d '{"model": "fullsong"}'
+
+# 2. Submit generation
+TASK=$(curl -s -X POST http://localhost:8000/v1/fullsong/generate \
+  -H "Content-Type: application/json" \
+  -d '{
+    "caption": "lo-fi hip hop, mellow piano, soft drums, vinyl crackle",
+    "duration": 120,
+    "instrumental": true,
+    "inference_steps": 8,
+    "audio_format": "mp3"
+  }' | python -c "import sys,json; print(json.load(sys.stdin)['data']['task_id'])")
+
+# 3. Poll until finished
+curl http://localhost:8000/v1/fullsong/result/$TASK
+
+# 4. Download (using audio_path from step 3 result)
+curl "http://localhost:8000/v1/fullsong/audio?path=/tmp/acestep/outputs/$TASK.mp3" \
+  --output song.mp3
+```
+
+### Generate a MIDI + WAV clip
+
+```bash
+# 1. Load Foundation-1
+curl -X POST http://localhost:8000/v1/models/load \
+  -H "Content-Type: application/json" \
+  -d '{"model": "clip"}'
+
+# 2. Submit generation
+curl -s -X POST http://localhost:8000/v1/clip/generate \
+  -H "Content-Type: application/json" \
+  -d '{
+    "prompt": "Keys, Rhodes Piano, Warm, Lush, 8 Bars, 90 BPM, D major",
+    "bars": 8, "bpm": 90, "note": "D", "scale": "major", "steps": 75
+  }'
+# => {"task_id": "b7e3a921-..."}
+
+# 3. Poll
+curl http://localhost:8000/v1/clip/result/b7e3a921-...
+# => {"status": "complete", "wav_url": "/v1/clip/audio/Keys_Rhodes_...", "midi_url": "..."}
+
+# 4. Download both files
+curl http://localhost:8000/v1/clip/audio/Keys_Rhodes_Piano_Warm_Lush_42.wav --output clip.wav
+curl http://localhost:8000/v1/clip/midi/Keys_Rhodes_Piano_Warm_Lush_42.mid  --output clip.mid
+```
+
+### Separate stems from an audio file
+
+```bash
+# 1. Load separator (terminates any active model, frees VRAM)
+curl -X POST http://localhost:8000/v1/models/load \
+  -H "Content-Type: application/json" \
+  -d '{"model": "separator"}'
+
+# 2. Upload file and submit separation
+TASK=$(curl -s -X POST http://localhost:8000/v1/separator/separate \
+  -F "file=@song.mp3" \
+  -F "model_filename=UVR-MDX-NET-Inst_HQ_3.onnx" | python -c "import sys,json; print(json.load(sys.stdin)['task_id'])")
+
+# 3. Poll until complete
+curl http://localhost:8000/v1/separator/result/$TASK
+# => {"status": "complete", "files": ["...(Vocals)...", "...(Instrumental)..."]}
+
+# 4. Download stems
+curl "http://localhost:8000/v1/separator/download/...(Vocals)....mp3" --output vocals.mp3
+curl "http://localhost:8000/v1/separator/download/...(Instrumental)....mp3" --output instrumental.mp3
+```
+
+### Switch between models
+
+```bash
+# Foundation-1 is active — switch to ACE-Step
+curl -X POST http://localhost:8000/v1/models/load \
+  -H "Content-Type: application/json" \
+  -d '{"model": "fullsong"}'
+# Foundation-1 subprocess is terminated, ACE-Step starts. Blocks until healthy.
+```
+
+---
+
+## Error reference
+
+| HTTP Status | Meaning |
+|-------------|---------|
+| `400` | Bad request (e.g. unknown model name) |
+| `404` | Task ID or file not found |
+| `503` | Requested model is not currently loaded, or sub-service is unreachable |
+
+**503 body when wrong model is active:**
+```json
+{
+  "detail": {
+    "error": "Model 'clip' is not loaded. POST /v1/models/load first.",
+    "active_model": "fullsong"
+  }
+}
+```
@@ -0,0 +1,79 @@
+@echo off
+setlocal
+
+echo ==========================================
+echo   KGOne Cleanup Script (Windows)
+echo ==========================================
+echo.
+echo This will permanently delete:
+echo   .venv\       (gateway Python environment)
+echo   ace-step\    (submodule + venv + model checkpoints)
+echo   foundation1\ (submodule + venv + model weights)
+echo   separator\   (submodule + venv)
+echo   outputs\     (all generated audio and MIDI files)
+echo   uploads\     (all uploaded audio files)
+echo.
+echo Re-run init.bat to restore everything except outputs and uploads.
+echo.
+
+set /p CONFIRM=Type YES to confirm:
+if /i not "%CONFIRM%"=="YES" (
+    echo Cancelled.
+    exit /b 0
+)
+echo.
+
+if exist ".venv" (
+    echo Removing .venv ...
+    rmdir /s /q ".venv"
+    echo   Done.
+) else (
+    echo .venv not found, skipping.
+)
+
+if exist "ace-step" (
+    echo Removing ace-step ...
+    rmdir /s /q "ace-step"
+    echo   Done.
+) else (
+    echo ace-step not found, skipping.
+)
+
+if exist "foundation1" (
+    echo Removing foundation1 ...
+    rmdir /s /q "foundation1"
+    echo   Done.
+) else (
+    echo foundation1 not found, skipping.
+)
+
+if exist "separator" (
+    echo Removing separator ...
+    rmdir /s /q "separator"
+    echo   Done.
+) else (
+    echo separator not found, skipping.
+)
+
+if exist "outputs" (
+    echo Removing outputs ...
+    rmdir /s /q "outputs"
+    echo   Done.
+) else (
+    echo outputs not found, skipping.
+)
+
+if exist "uploads" (
+    echo Removing uploads ...
+    rmdir /s /q "uploads"
+    echo   Done.
+) else (
+    echo uploads not found, skipping.
+)
+
+echo.
+echo ==========================================
+echo   Cleanup complete.
+echo   Run init.bat to set up again.
+echo ==========================================
+echo.
@@ -0,0 +1,244 @@
+"""Foundation-1 REST API wrapper server.
+
+Wraps RC-stable-audio-tools' generate_cond() behind FastAPI endpoints.
+Runs on port 8002. Managed as a subprocess by the KGOne gateway.
+
+Environment variables:
+  FOUNDATION1_PRETRAINED_NAME  HuggingFace model name (default: RoyalCities/Foundation-1)
+  FOUNDATION1_CKPT_PATH        Path to local .safetensors checkpoint (overrides pretrained name)
+  FOUNDATION1_CONFIG_PATH      Path to local model_config.json (required if CKPT_PATH is set)
+  FOUNDATION1_SERVER_PORT      Port to listen on (default: 8002)
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+import sys
+import time
+import uuid
+from concurrent.futures import ThreadPoolExecutor
+from contextlib import asynccontextmanager
+from pathlib import Path
+from typing import Optional
+
+import uvicorn
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+
+# ── path setup ──────────────────────��──────────────────────────────��──────────
+# Must happen BEFORE importing stable_audio_tools — gradio.py opens config.json
+# relative to CWD at import time.
+
+ROOT_DIR = Path(__file__).parent.parent.resolve()
+FOUNDATION1_DIR = ROOT_DIR / "foundation1"
+OUTPUT_DIR = ROOT_DIR / "outputs" / "clip"
+
+if not FOUNDATION1_DIR.exists():
+    raise RuntimeError(
+        f"Foundation-1 repo not found at {FOUNDATION1_DIR}. "
+        "Run init.bat first to clone the submodules."
+    )
+
+os.chdir(FOUNDATION1_DIR)
+sys.path.insert(0, str(FOUNDATION1_DIR))
+OUTPUT_DIR.mkdir(parents=True, exist_ok=True)
+
+# ── imports from stable_audio_tools (CWD is now FOUNDATION1_DIR) ─────────────
+import stable_audio_tools.interface.gradio as _gradio_module  # noqa: E402
+from stable_audio_tools.interface.gradio import generate_cond, load_model  # noqa: E402
+
+# Override the output directory from the one baked into config.json
+_gradio_module.output_directory = str(OUTPUT_DIR)
+
+# ── logging ────────────────────────────────────────────────────────────────���──
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s %(levelname)s %(name)s: %(message)s",
+)
+logger = logging.getLogger(__name__)
+
+# ── configuration ─────────────────────────────────────────────────────────────
+PRETRAINED_NAME = os.environ.get("FOUNDATION1_PRETRAINED_NAME", "RoyalCities/Foundation-1")
+CKPT_PATH = os.environ.get("FOUNDATION1_CKPT_PATH")
+CONFIG_PATH = os.environ.get("FOUNDATION1_CONFIG_PATH")
+PORT = int(os.environ.get("FOUNDATION1_SERVER_PORT", "8002"))
+
+# Default local paths written by init.bat's snapshot_download step.
+# The HuggingFace repo names the file Foundation_1.safetensors (not model.safetensors),
+# so get_pretrained_model() would fail — we bypass it by using the local path directly.
+_DEFAULT_LOCAL_DIR = ROOT_DIR / "foundation1" / "models" / "RoyalCities-Foundation-1"
+_DEFAULT_CKPT = _DEFAULT_LOCAL_DIR / "Foundation_1.safetensors"
+_DEFAULT_CONFIG = _DEFAULT_LOCAL_DIR / "model_config.json"
+
+# ── in-memory task store ──────────────────────────────────────────────────────
+_tasks: dict[str, dict] = {}
+_executor = ThreadPoolExecutor(max_workers=1)  # one generation at a time (single GPU)
+
+
+# ── app lifecycle ─────────────────────────────────────────────────────────────
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    logger.info("Loading Foundation-1 model...")
+    _load_foundation1_model()
+    logger.info("Foundation-1 model ready.")
+    yield
+    logger.info("Shutting down Foundation-1 server.")
+    _gradio_module.model = None
+
+
+def _load_foundation1_model() -> None:
+    import torch
+
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    logger.info("Using device: %s", device)
+
+    # Resolve checkpoint: env var override > local download > pretrained_name fallback
+    ckpt = Path(CKPT_PATH) if CKPT_PATH else (_DEFAULT_CKPT if _DEFAULT_CKPT.exists() else None)
+    config = Path(CONFIG_PATH) if CONFIG_PATH else (_DEFAULT_CONFIG if _DEFAULT_CONFIG.exists() else None)
+
+    if ckpt and config:
+        with open(config) as f:
+            model_config = json.load(f)
+        load_model(model_config=model_config, model_ckpt_path=str(ckpt), device=device)
+        logger.info("Loaded local checkpoint: %s", ckpt)
+    else:
+        # Last resort: let stable_audio_tools attempt its own download.
+        # Note: get_pretrained_model() expects model.safetensors; this will fail unless
+        # the upstream repo is updated to match that name.
+        logger.warning(
+            "Local weights not found at %s — falling back to pretrained_name download. "
+            "Run init.bat to pre-download weights.",
+            _DEFAULT_CKPT,
+        )
+        load_model(pretrained_name=PRETRAINED_NAME, device=device)
+        logger.info("Loaded pretrained model: %s", PRETRAINED_NAME)
+
+
+app = FastAPI(
+    title="Foundation-1 Server",
+    description="Wraps Foundation-1 (RC-stable-audio-tools) for REST API use.",
+    version="0.1.0",
+    lifespan=lifespan,
+)
+
+
+# ── request model ─────────────────────────────────────────────────────────────
+
+class GenerateRequest(BaseModel):
+    prompt: str
+    negative_prompt: str = ""
+    bars: int = 4
+    bpm: int = 140
+    note: str = "C"
+    scale: str = "minor"
+    steps: int = 75
+    cfg_scale: float = 7.0
+    seed: int = -1
+    sampler_type: str = "dpmpp-2m-sde"
+    sigma_min: float = 0.03
+    sigma_max: float = 500.0
+    cfg_rescale: float = 0.0
+
+
+# ── routes ────────────────────────────────────────────────────────────────────
+
+@app.get("/health")
+async def health():
+    return {"status": "ok", "model_loaded": _gradio_module.model is not None}
+
+
+@app.post("/generate")
+async def generate(req: GenerateRequest):
+    if _gradio_module.model is None:
+        raise HTTPException(503, "Model not loaded")
+
+    task_id = str(uuid.uuid4())
+    _tasks[task_id] = {"status": "pending", "created_at": time.time()}
+
+    loop = asyncio.get_event_loop()
+    loop.run_in_executor(_executor, _run_generate, task_id, req)
+
+    return {"task_id": task_id}
+
+
+def _run_generate(task_id: str, req: GenerateRequest) -> None:
+    _tasks[task_id]["status"] = "running"
+    try:
+        wav_path, _spectrograms, _piano_roll, midi_path = generate_cond(
+            prompt=req.prompt,
+            negative_prompt=req.negative_prompt or None,
+            bars=req.bars,
+            bpm=req.bpm,
+            note=req.note,
+            scale=req.scale,
+            steps=req.steps,
+            cfg_scale=req.cfg_scale,
+            seed=req.seed,
+            sampler_type=req.sampler_type,
+            sigma_min=req.sigma_min,
+            sigma_max=req.sigma_max,
+            cfg_rescale=req.cfg_rescale,
+        )
+        _tasks[task_id].update(
+            {
+                "status": "complete",
+                "wav_filename": Path(wav_path).name if wav_path else None,
+                "midi_filename": Path(midi_path).name if midi_path else None,
+            }
+        )
+    except Exception:
+        logger.exception("Generation failed for task %s", task_id)
+        _tasks[task_id]["status"] = "error"
+        _tasks[task_id]["error"] = "Generation failed — check server logs."
+
+
+@app.get("/result/{task_id}")
+async def get_result(task_id: str):
+    task = _tasks.get(task_id)
+    if task is None:
+        raise HTTPException(404, "Task not found")
+
+    status = task["status"]
+    if status != "complete":
+        return {"task_id": task_id, "status": status, "error": task.get("error")}
+
+    return {"task_id": task_id, "status": "complete"}
+
+
+@app.get("/audio/{task_id}")
+async def serve_audio(task_id: str):
+    task = _tasks.get(task_id)
+    if task is None:
+        raise HTTPException(404, "Task not found")
+    filename = task.get("wav_filename")
+    if not filename:
+        raise HTTPException(404, "No audio file for this task")
+    path = OUTPUT_DIR / filename
+    if not path.is_file():
+        raise HTTPException(404, "Audio file not found on disk")
+    return FileResponse(str(path), media_type="audio/wav")
+
+
+@app.get("/midi/{task_id}")
+async def serve_midi(task_id: str):
+    task = _tasks.get(task_id)
+    if task is None:
+        raise HTTPException(404, "Task not found")
+    filename = task.get("midi_filename")
+    if not filename:
+        raise HTTPException(404, "No MIDI file for this task")
+    path = OUTPUT_DIR / filename
+    if not path.is_file():
+        raise HTTPException(404, "MIDI file not found on disk")
+    return FileResponse(str(path), media_type="audio/midi")
+
+
+# ── entry point ────────────────────────────��────────────────────────────────���─
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=PORT, log_level="info")
@@ -0,0 +1,339 @@
+@echo off
+setlocal enabledelayedexpansion
+
+echo ==========================================
+echo   KGOne Initialization Script (Windows)
+echo ==========================================
+echo.
+
+set "ROOT=%~dp0"
+cd /d "%ROOT%"
+
+echo Checking prerequisites...
+
+where git >nul 2>&1
+if errorlevel 1 (
+    echo   ERROR: git not found. Install from https://git-scm.com/downloads
+    exit /b 1
+)
+
+where uv >nul 2>&1
+if errorlevel 1 (
+    echo   ERROR: uv not found. Install from https://docs.astral.sh/uv/
+    exit /b 1
+)
+
+echo   git ... OK
+echo   uv  ... OK
+echo.
+
+:: ---------------------------------------------------------
+echo [1/6] Reading submodules.json...
+:: ---------------------------------------------------------
+
+powershell -NoProfile -Command "$j = Get-Content 'submodules.json' | ConvertFrom-Json; $j.'ace-step'.url | Out-File -Encoding ASCII '%TEMP%\kg_acestep_url.txt' -NoNewline"
+if errorlevel 1 (
+    echo   ERROR: Failed to read submodules.json
+    exit /b 1
+)
+powershell -NoProfile -Command "$j = Get-Content 'submodules.json' | ConvertFrom-Json; $j.'ace-step'.commit | Out-File -Encoding ASCII '%TEMP%\kg_acestep_commit.txt' -NoNewline"
+powershell -NoProfile -Command "$j = Get-Content 'submodules.json' | ConvertFrom-Json; $j.foundation1.url | Out-File -Encoding ASCII '%TEMP%\kg_f1_url.txt' -NoNewline"
+powershell -NoProfile -Command "$j = Get-Content 'submodules.json' | ConvertFrom-Json; $j.foundation1.commit | Out-File -Encoding ASCII '%TEMP%\kg_f1_commit.txt' -NoNewline"
+powershell -NoProfile -Command "$j = Get-Content 'submodules.json' | ConvertFrom-Json; $j.'python-audio-separator'.url | Out-File -Encoding ASCII '%TEMP%\kg_sep_url.txt' -NoNewline"
+powershell -NoProfile -Command "$j = Get-Content 'submodules.json' | ConvertFrom-Json; $j.'python-audio-separator'.commit | Out-File -Encoding ASCII '%TEMP%\kg_sep_commit.txt' -NoNewline"
+
+set /p ACESTEP_URL=<"%TEMP%\kg_acestep_url.txt"
+set /p ACESTEP_COMMIT=<"%TEMP%\kg_acestep_commit.txt"
+set /p FOUNDATION1_URL=<"%TEMP%\kg_f1_url.txt"
+set /p FOUNDATION1_COMMIT=<"%TEMP%\kg_f1_commit.txt"
+set /p SEP_URL=<"%TEMP%\kg_sep_url.txt"
+set /p SEP_COMMIT=<"%TEMP%\kg_sep_commit.txt"
+del "%TEMP%\kg_acestep_url.txt" "%TEMP%\kg_acestep_commit.txt" "%TEMP%\kg_f1_url.txt" "%TEMP%\kg_f1_commit.txt" "%TEMP%\kg_sep_url.txt" "%TEMP%\kg_sep_commit.txt" >nul 2>&1
+
+if "%ACESTEP_URL%"=="" (
+    echo   ERROR: Could not read from submodules.json
+    exit /b 1
+)
+
+echo   ACE-Step          URL   : %ACESTEP_URL%
+echo   ACE-Step          commit: %ACESTEP_COMMIT%
+echo   Foundation-1      URL   : %FOUNDATION1_URL%
+echo   Foundation-1      commit: %FOUNDATION1_COMMIT%
+echo   audio-separator   URL   : %SEP_URL%
+echo   audio-separator   commit: %SEP_COMMIT%
+echo.
+
+:: ---------------------------------------------------------
+echo [2/6] Setting up ACE-Step...
+:: ---------------------------------------------------------
+
+if exist "ace-step\.git" goto :acestep_fetch
+echo   Cloning ACE-Step (may take several minutes)...
+git clone "%ACESTEP_URL%" ace-step
+if errorlevel 1 (
+    echo   ERROR: Failed to clone ACE-Step
+    exit /b 1
+)
+goto :acestep_checkout
+
+:acestep_fetch
+echo   Repository exists. Fetching refs...
+git -C ace-step fetch --quiet origin
+
+:acestep_checkout
+echo   Checking out pinned commit %ACESTEP_COMMIT%...
+git -C ace-step checkout %ACESTEP_COMMIT% --quiet
+if errorlevel 1 (
+    echo   ERROR: Could not checkout ACE-Step commit %ACESTEP_COMMIT%
+    exit /b 1
+)
+echo   ACE-Step OK.
+echo.
+
+:: ---------------------------------------------------------
+echo [3/6] Setting up Foundation-1...
+:: ---------------------------------------------------------
+
+if exist "foundation1\.git" goto :f1_fetch
+echo   Cloning Foundation-1...
+git clone "%FOUNDATION1_URL%" foundation1
+if errorlevel 1 (
+    echo   ERROR: Failed to clone Foundation-1
+    exit /b 1
+)
+goto :f1_checkout
+
+:f1_fetch
+echo   Repository exists. Fetching refs...
+git -C foundation1 fetch --quiet origin
+
+:f1_checkout
+echo   Checking out pinned commit %FOUNDATION1_COMMIT%...
+git -C foundation1 checkout %FOUNDATION1_COMMIT% --quiet
+if errorlevel 1 (
+    echo   ERROR: Could not checkout Foundation-1 commit %FOUNDATION1_COMMIT%
+    exit /b 1
+)
+echo   Foundation-1 OK.
+echo.
+
+:: ---------------------------------------------------------
+echo Setting up python-audio-separator...
+:: ---------------------------------------------------------
+
+if exist "separator\.git" goto :sep_fetch
+echo   Cloning python-audio-separator...
+git clone "%SEP_URL%" separator
+if errorlevel 1 (
+    echo   ERROR: Failed to clone python-audio-separator
+    exit /b 1
+)
+goto :sep_checkout
+
+:sep_fetch
+echo   Repository exists. Fetching refs...
+git -C separator fetch --quiet origin
+
+:sep_checkout
+echo   Checking out pinned commit %SEP_COMMIT%...
+git -C separator checkout %SEP_COMMIT% --quiet
+if errorlevel 1 (
+    echo   ERROR: Could not checkout python-audio-separator commit %SEP_COMMIT%
+    exit /b 1
+)
+echo   python-audio-separator OK.
+echo.
+
+:: ---------------------------------------------------------
+echo [4/6] Setting up Python environments...
+:: ---------------------------------------------------------
+
+:: Gateway venv
+if exist ".venv\Scripts\python.exe" goto :gateway_venv_done
+echo   Creating gateway venv...
+uv venv .venv
+if errorlevel 1 (
+    echo   ERROR: Failed to create gateway venv
+    exit /b 1
+)
+uv pip install --python .venv "fastapi>=0.110.0" "uvicorn[standard]>=0.27.0" "httpx>=0.27.0" "python-multipart>=0.0.9"
+if errorlevel 1 (
+    echo   ERROR: Failed to install gateway dependencies
+    exit /b 1
+)
+echo   Gateway venv OK.
+goto :acestep_venv_start
+:gateway_venv_done
+echo   Gateway venv already exists, skipping.
+
+:: ACE-Step venv
+:acestep_venv_start
+if exist "ace-step\.venv\Scripts\python.exe" goto :acestep_venv_done
+echo   Creating ACE-Step venv...
+echo   NOTE: Downloads large CUDA packages. May take 10-20 minutes.
+pushd ace-step
+uv venv .venv
+if errorlevel 1 (
+    popd
+    echo   ERROR: Failed to create ACE-Step venv
+    exit /b 1
+)
+uv pip install --python .venv -e .
+if errorlevel 1 (
+    popd
+    echo   ERROR: Failed to install ACE-Step dependencies
+    exit /b 1
+)
+popd
+echo   ACE-Step venv OK.
+goto :f1_venv_start
+:acestep_venv_done
+echo   ACE-Step venv already exists, skipping.
+
+:: Foundation-1 venv
+:f1_venv_start
+if exist "foundation1\.venv\Scripts\python.exe" goto :f1_venv_done
+echo   Creating Foundation-1 venv (requires Python 3.10)...
+uv venv --python 3.10 foundation1\.venv
+if errorlevel 1 (
+    echo   WARNING: Python 3.10 not found. Falling back to default Python.
+    uv venv foundation1\.venv
+    if errorlevel 1 (
+        echo   ERROR: Failed to create Foundation-1 venv
+        exit /b 1
+    )
+)
+echo   Installing PyTorch 2.5.1 (CUDA 12.1 wheels)...
+echo   NOTE: This downloads ~2 GB. May take several minutes.
+uv pip install --python foundation1\.venv torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 --index-url https://download.pytorch.org/whl/cu121
+if errorlevel 1 (
+    echo   ERROR: Failed to install PyTorch
+    exit /b 1
+)
+echo   Installing pinned numpy...
+uv pip install --python foundation1\.venv "numpy==1.23.5"
+if errorlevel 1 (
+    echo   ERROR: Failed to install numpy
+    exit /b 1
+)
+echo   Installing Foundation-1 dependencies...
+uv pip install --python foundation1\.venv -e foundation1
+if errorlevel 1 (
+    echo   ERROR: Failed to install Foundation-1 dependencies
+    exit /b 1
+)
+uv pip install --python foundation1\.venv "fastapi>=0.110.0" "uvicorn[standard]>=0.27.0"
+if errorlevel 1 (
+    echo   ERROR: Failed to install Foundation-1 server dependencies
+    exit /b 1
+)
+echo   Pinning setuptools for pkg_resources compatibility...
+uv pip install --python foundation1\.venv "setuptools<70"
+if errorlevel 1 (
+    echo   ERROR: Failed to pin setuptools
+    exit /b 1
+)
+echo   Foundation-1 venv OK.
+goto :sep_venv_start
+:f1_venv_done
+echo   Foundation-1 venv already exists, skipping.
+
+:: Separator venv
+:sep_venv_start
+if exist "separator\.venv\pyvenv.cfg" goto :sep_venv_done
+echo   Creating separator venv...
+echo   NOTE: Downloads CUDA packages. May take several minutes.
+uv venv separator\.venv
+if errorlevel 1 (
+    echo   ERROR: Failed to create separator venv
+    exit /b 1
+)
+uv pip install --python separator\.venv -e "separator[gpu]"
+if errorlevel 1 (
+    echo   ERROR: Failed to install audio-separator
+    exit /b 1
+)
+uv pip uninstall --python separator\.venv torch torchvision
+uv pip install --python separator\.venv torch==2.11.0+cu126 torchvision==0.26.0+cu126 --index-url https://download.pytorch.org/whl/cu126
+if errorlevel 1 (
+    echo   ERROR: Failed to install PyTorch for separator
+    exit /b 1
+)
+uv pip install --python separator\.venv --force-reinstall onnxruntime-gpu
+if errorlevel 1 (
+    echo   ERROR: Failed to install onnxruntime-gpu
+    exit /b 1
+)
+echo   Separator venv OK.
+goto :venvs_done
+:sep_venv_done
+echo   Separator venv already exists, skipping.
+
+:venvs_done
+echo.
+
+:: ---------------------------------------------------------
+echo [5/6] Creating output directories...
+:: ---------------------------------------------------------
+if not exist "outputs\clip"            mkdir "outputs\clip"
+if not exist "outputs\fullsong"        mkdir "outputs\fullsong"
+if not exist "outputs\separator"       mkdir "outputs\separator"
+if not exist "uploads\separator"       mkdir "uploads\separator"
+if not exist "foundation1\generations" mkdir "foundation1\generations"
+if not exist "foundation1\models"      mkdir "foundation1\models"
+echo   Done.
+echo.
+
+:: ---------------------------------------------------------
+echo [6/6] Downloading model weights...
+:: ---------------------------------------------------------
+
+:: ACE-Step weights - mirrors what the API server does on first initialize:
+::   ensure_model_downloaded('acestep-v15-turbo', checkpoints/)
+::   ensure_model_downloaded('vae', checkpoints/)
+:: Auto-selects HuggingFace vs ModelScope by pinging Google (or ACESTEP_DOWNLOAD_SOURCE env var).
+if exist "ace-step\checkpoints\acestep-v15-turbo\model.safetensors" goto :acestep_weights_done
+echo   Downloading ACE-Step checkpoints (may take several minutes)...
+ace-step\.venv\Scripts\python.exe -c "from acestep.api.model_download import ensure_model_downloaded; import os; ckpt=os.path.join(os.getcwd(),'ace-step','checkpoints'); ensure_model_downloaded('acestep-v15-turbo', ckpt); ensure_model_downloaded('vae', ckpt)"
+if errorlevel 1 (
+    echo   ERROR: ACE-Step weight download failed
+    exit /b 1
+)
+:acestep_weights_done
+echo   ACE-Step weights OK.
+echo.
+
+:: Foundation-1 weights (huggingface_hub is already installed as a dep of stable_audio_tools)
+if exist "foundation1\models\RoyalCities-Foundation-1\Foundation_1.safetensors" goto :f1_weights_done
+echo   Downloading Foundation-1 weights (approx 1.7 GB)...
+foundation1\.venv\Scripts\python.exe -c "from huggingface_hub import snapshot_download; snapshot_download('RoyalCities/Foundation-1', local_dir='foundation1/models/RoyalCities-Foundation-1')"
+if errorlevel 1 (
+    echo   ERROR: Foundation-1 weight download failed
+    exit /b 1
+)
+:f1_weights_done
+echo   Foundation-1 weights OK.
+echo.
+
+:: Separator models are downloaded automatically by audio-separator on first use.
+echo   Separator models will be downloaded on first use (handled by audio-separator).
+echo.
+
+echo ==========================================
+echo   Initialization complete!
+echo ==========================================
+echo.
+echo Start the gateway:
+echo   .venv\Scripts\python.exe main.py
+echo.
+echo Then load a model:
+echo   POST http://localhost:8000/v1/models/load
+echo   Body: {"model": "clip"}     -- Foundation-1 (MIDI + WAV)
+echo   Body: {"model": "fullsong"} -- ACE-Step 1.5 (full songs)
+echo.
+echo Or separate stems (no model load needed):
+echo   POST http://localhost:8000/v1/separator/separate
+echo   Body: multipart/form-data  file=<audio> model_filename=<model>
+echo.
+echo API docs: http://localhost:8000/docs
+echo.
@@ -0,0 +1,468 @@
+"""KGOne — unified REST API gateway for ACE-Step 1.5 (fullsong), Foundation-1 (clip), and UVR separator."""
+
+from __future__ import annotations
+
+import json
+import logging
+import shutil
+import urllib.parse
+import uuid
+from contextlib import asynccontextmanager
+from pathlib import Path
+from typing import Optional
+
+import httpx
+import uvicorn
+from fastapi import FastAPI, File, Form, HTTPException, Request, UploadFile
+from fastapi.responses import FileResponse, Response
+from pydantic import BaseModel, ConfigDict
+
+from services.model_manager import ModelManager, ModelNotActiveError, model_manager
+from services.acestep_client import ACESTEP_BASE_URL
+from services.foundation1_client import FOUNDATION1_BASE_URL
+from services.separator_runner import ALLOWED_MODELS, OUTPUT_DIR, UPLOAD_DIR, separator_runner
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s %(levelname)s %(name)s: %(message)s")
+logger = logging.getLogger(__name__)
+
+# ---------------------------------------------------------------------------
+# App lifecycle
+# ---------------------------------------------------------------------------
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    async with httpx.AsyncClient(timeout=300.0) as client:
+        app.state.http_client = client
+        yield
+    await model_manager.unload()
+
+
+app = FastAPI(
+    title="KGOne Gateway",
+    description="Unified REST API for ACE-Step 1.5 (full-song music) and Foundation-1 (clip MIDI/WAV).",
+    version="0.1.0",
+    lifespan=lifespan,
+)
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+async def _proxy(client: httpx.AsyncClient, method: str, url: str, request: Request) -> Response:
+    """Forward a request body + headers to a sub-service and return its response."""
+    body = await request.body()
+    headers = {k: v for k, v in request.headers.items() if k.lower() not in ("host", "content-length")}
+    try:
+        resp = await client.request(method, url, content=body, headers=headers)
+    except httpx.ConnectError:
+        raise HTTPException(503, "Sub-service unreachable — is the model loaded?")
+    return Response(
+        content=resp.content,
+        status_code=resp.status_code,
+        headers={k: v for k, v in resp.headers.items() if k.lower() not in ("transfer-encoding",)},
+        media_type=resp.headers.get("content-type"),
+    )
+
+
+def _require(model_name: str) -> None:
+    """Raise 503 if the requested model is not the active one."""
+    if model_manager.active_model != model_name:
+        raise HTTPException(
+            status_code=503,
+            detail={
+                "error": f"Model '{model_name}' is not loaded. POST /v1/models/load first.",
+                "active_model": model_manager.active_model,
+            },
+        )
+
+
+# ---------------------------------------------------------------------------
+# Health & model management
+# ---------------------------------------------------------------------------
+
+@app.get("/health", tags=["system"])
+async def health():
+    return {"status": "ok", "active_model": model_manager.active_model}
+
+
+class LoadModelRequest(BaseModel):
+    model: str  # "fullsong" | "clip"
+
+
+@app.post("/v1/models/load", tags=["system"])
+async def load_model(req: LoadModelRequest):
+    """Load a model onto the GPU, unloading the currently active one first.
+
+    - `model`: `"fullsong"` (ACE-Step 1.5), `"clip"` (Foundation-1), or `"separator"` (UVR stem separation)
+
+    For `"fullsong"` and `"clip"` this blocks until the sub-service reports healthy.
+    For `"separator"` it only terminates the currently running model subprocess to free VRAM —
+    no persistent process is started. After loading `"separator"`, call `POST /v1/separator/separate`.
+    """
+    if req.model not in ("fullsong", "clip", "separator"):
+        raise HTTPException(400, f"Unknown model '{req.model}'. Must be 'fullsong', 'clip', or 'separator'.")
+    if separator_runner.active:
+        raise HTTPException(503, "A stem separation task is currently running. Wait for it to complete first.")
+    await model_manager.load(req.model)
+    return {"active_model": model_manager.active_model, "status": "ready"}
+
+
+@app.get("/v1/models/status", tags=["system"])
+async def model_status():
+    return {"active_model": model_manager.active_model}
+
+
+# ---------------------------------------------------------------------------
+# /v1/fullsong — ACE-Step 1.5
+# ---------------------------------------------------------------------------
+
+class FullsongGenerateRequest(BaseModel):
+    """ACE-Step 1.5 generation request. All listed fields are forwarded as-is;
+    any additional ACE-Step fields are also accepted and forwarded."""
+
+    model_config = ConfigDict(extra="allow")
+
+    caption: Optional[str] = None
+    lyrics: Optional[str] = None
+    instrumental: Optional[bool] = None
+    inference_steps: Optional[int] = None
+    guidance_scale: Optional[float] = None
+    use_random_seed: Optional[bool] = None
+    seed: Optional[int] = None
+    thinking: Optional[bool] = None
+    batch_size: Optional[int] = None
+    audio_format: Optional[str] = None
+
+
+@app.post(
+    "/v1/fullsong/generate",
+    tags=["fullsong"],
+    summary="Submit a full-song generation task (ACE-Step 1.5)",
+)
+async def fullsong_generate(req: FullsongGenerateRequest, request: Request):
+    """Proxy to ACE-Step's `/release_task`.
+
+    Forwards the exact JSON body you send (only fields you include are forwarded —
+    no defaults are injected). Extra ACE-Step fields beyond those listed are also passed through.
+
+    Returns `{"data": {"task_id": "...", "status": "queued", ...}}`.
+    """
+    _require("fullsong")
+    body = req.model_dump_json(exclude_unset=True).encode()
+    try:
+        resp = await request.app.state.http_client.post(
+            f"{ACESTEP_BASE_URL}/release_task",
+            content=body,
+            headers={"Content-Type": "application/json"},
+        )
+    except httpx.ConnectError:
+        raise HTTPException(503, "Sub-service unreachable — is the model loaded?")
+    return Response(
+        content=resp.content,
+        status_code=resp.status_code,
+        headers={k: v for k, v in resp.headers.items() if k.lower() not in ("transfer-encoding",)},
+        media_type=resp.headers.get("content-type"),
+    )
+
+
+@app.get(
+    "/v1/fullsong/result/{task_id}",
+    tags=["fullsong"],
+    summary="Poll a fullsong generation task result",
+)
+async def fullsong_result(task_id: str, request: Request):
+    """Query the result of a generation task.
+
+    Returns ACE-Step's raw result payload. Poll until `status` is `1` (succeeded),
+    then call `GET /v1/fullsong/audio/{task_id}` to download the audio.
+    """
+    _require("fullsong")
+    payload = json.dumps({"task_id_list": [task_id]}).encode()
+    try:
+        resp = await request.app.state.http_client.post(
+            f"{ACESTEP_BASE_URL}/query_result",
+            content=payload,
+            headers={"Content-Type": "application/json"},
+        )
+    except httpx.ConnectError:
+        raise HTTPException(503, "ACE-Step service unreachable")
+    return Response(content=resp.content, status_code=resp.status_code, media_type="application/json")
+
+
+@app.get(
+    "/v1/fullsong/audio/{task_id}",
+    tags=["fullsong"],
+    summary="Download generated audio for a completed fullsong task",
+)
+async def fullsong_audio(task_id: str, request: Request, index: int = 0):
+    """Download the generated audio file for a completed task.
+
+    Internally queries ACE-Step for the task result, extracts the audio path,
+    and streams the file back. Only works once the task `status` is `1` (succeeded).
+
+    Use `index` (0-based) to select a specific file when `batch_size > 1`.
+    """
+    _require("fullsong")
+    client: httpx.AsyncClient = request.app.state.http_client
+
+    # Step 1: fetch the task result from ACE-Step
+    try:
+        result_resp = await client.post(
+            f"{ACESTEP_BASE_URL}/query_result",
+            content=json.dumps({"task_id_list": [task_id]}).encode(),
+            headers={"Content-Type": "application/json"},
+        )
+    except httpx.ConnectError:
+        raise HTTPException(503, "ACE-Step service unreachable")
+
+    try:
+        result_data = result_resp.json()
+    except Exception:
+        raise HTTPException(502, "Invalid response from ACE-Step")
+
+    items = result_data.get("data", [])
+    task_item = next((item for item in items if item.get("task_id") == task_id), None)
+    if task_item is None:
+        raise HTTPException(404, f"Task '{task_id}' not found")
+    if task_item.get("status") != 1:
+        raise HTTPException(409, "Task is not yet complete — poll /v1/fullsong/result/{task_id} until status is 1")
+
+    # Step 2: parse the nested result JSON string and extract the file path
+    raw_result = task_item.get("result")
+    if not isinstance(raw_result, str):
+        raise HTTPException(502, "Unexpected result format from ACE-Step")
+    try:
+        results = json.loads(raw_result)
+    except json.JSONDecodeError:
+        raise HTTPException(502, "Could not parse ACE-Step result JSON")
+
+    if not results or index >= len(results):
+        raise HTTPException(404, f"No audio at index {index} (batch contains {len(results)} file(s))")
+
+    file_url = results[index].get("file", "")
+    if not file_url or "path=" not in file_url:
+        raise HTTPException(502, "No audio file path in ACE-Step result")
+
+    # parse_qs handles URL-decoding, giving us the raw filesystem path
+    qs = urllib.parse.parse_qs(urllib.parse.urlparse(file_url).query)
+    fs_path = qs.get("path", [""])[0]
+    if not fs_path:
+        raise HTTPException(502, "Could not extract audio path from ACE-Step result")
+
+    # Step 3: proxy the audio from ACE-Step — httpx re-encodes the path correctly
+    try:
+        audio_resp = await client.get(f"{ACESTEP_BASE_URL}/v1/audio", params={"path": fs_path})
+    except httpx.ConnectError:
+        raise HTTPException(503, "ACE-Step service unreachable")
+
+    if audio_resp.status_code == 404:
+        raise HTTPException(404, "Audio file not found on ACE-Step server")
+    if audio_resp.status_code != 200:
+        raise HTTPException(502, f"ACE-Step returned {audio_resp.status_code} for audio download")
+
+    ext = Path(fs_path).suffix  # e.g. ".mp3" — taken from the actual saved file
+    return Response(
+        content=audio_resp.content,
+        status_code=200,
+        media_type=audio_resp.headers.get("content-type", "audio/mpeg"),
+        headers={"Content-Disposition": f'attachment; filename="{task_id}{ext}"'},
+    )
+
+
+# ---------------------------------------------------------------------------
+# /v1/clip — Foundation-1
+# ---------------------------------------------------------------------------
+
+class ClipGenerateRequest(BaseModel):
+    """Foundation-1 clip generation request."""
+
+    prompt: str
+    negative_prompt: str = ""
+    bars: int = 4
+    bpm: int = 140
+    note: str = "C"
+    scale: str = "minor"
+    steps: int = 75
+    cfg_scale: float = 7.0
+    seed: int = -1
+    sampler_type: str = "dpmpp-2m-sde"
+    sigma_min: float = 0.03
+    sigma_max: float = 500.0
+    cfg_rescale: float = 0.0
+
+
+@app.post(
+    "/v1/clip/generate",
+    tags=["clip"],
+    summary="Submit a clip generation task (Foundation-1)",
+)
+async def clip_generate(req: ClipGenerateRequest, request: Request):
+    """Submit a MIDI + WAV generation task to Foundation-1.
+
+    Returns `{"task_id": "..."}`. Poll `/v1/clip/result/{task_id}` for completion.
+    """
+    _require("clip")
+    body = req.model_dump_json(exclude_unset=True).encode()
+    try:
+        resp = await request.app.state.http_client.post(
+            f"{FOUNDATION1_BASE_URL}/generate",
+            content=body,
+            headers={"Content-Type": "application/json"},
+        )
+    except httpx.ConnectError:
+        raise HTTPException(503, "Sub-service unreachable — is the model loaded?")
+    return Response(
+        content=resp.content,
+        status_code=resp.status_code,
+        headers={k: v for k, v in resp.headers.items() if k.lower() not in ("transfer-encoding",)},
+        media_type=resp.headers.get("content-type"),
+    )
+
+
+@app.get(
+    "/v1/clip/result/{task_id}",
+    tags=["clip"],
+    summary="Poll a clip generation task result",
+)
+async def clip_result(task_id: str, request: Request):
+    """Returns task status. When `status == "complete"`, includes `wav_url` and `midi_url`
+    pointing to the gateway download endpoints."""
+    _require("clip")
+    try:
+        resp = await request.app.state.http_client.get(f"{FOUNDATION1_BASE_URL}/result/{task_id}")
+    except httpx.ConnectError:
+        raise HTTPException(503, "Foundation-1 service unreachable")
+
+    return Response(content=resp.content, status_code=resp.status_code, media_type="application/json")
+
+
+@app.get(
+    "/v1/clip/audio/{task_id}",
+    tags=["clip"],
+    summary="Download a generated WAV clip",
+)
+async def clip_audio(task_id: str, request: Request):
+    _require("clip")
+    try:
+        resp = await request.app.state.http_client.get(f"{FOUNDATION1_BASE_URL}/audio/{task_id}")
+    except httpx.ConnectError:
+        raise HTTPException(503, "Foundation-1 service unreachable")
+    return Response(content=resp.content, status_code=resp.status_code,
+                    media_type=resp.headers.get("content-type", "audio/wav"))
+
+
+@app.get(
+    "/v1/clip/midi/{task_id}",
+    tags=["clip"],
+    summary="Download a generated MIDI clip",
+)
+async def clip_midi(task_id: str, request: Request):
+    _require("clip")
+    try:
+        resp = await request.app.state.http_client.get(f"{FOUNDATION1_BASE_URL}/midi/{task_id}")
+    except httpx.ConnectError:
+        raise HTTPException(503, "Foundation-1 service unreachable")
+    return Response(content=resp.content, status_code=resp.status_code,
+                    media_type=resp.headers.get("content-type", "audio/midi"))
+
+
+# ---------------------------------------------------------------------------
+# /v1/separator — UVR stem separation
+# ---------------------------------------------------------------------------
+
+@app.post(
+    "/v1/separator/separate",
+    tags=["separator"],
+    summary="Submit a stem separation task",
+)
+async def separator_separate(
+    file: UploadFile = File(...),
+    model_filename: str = Form(...),
+):
+    """Upload an audio file and separate its stems using the chosen UVR model.
+
+    - `file`: audio file (MP3, WAV, FLAC, …)
+    - `model_filename`: one of `UVR-MDX-NET-Inst_HQ_3.onnx`, `MDX23C-8KFFT-InstVoc_HQ.ckpt`,
+      `htdemucs_6s.yaml`
+
+    Returns `{"task_id": "..."}`. Poll `/v1/separator/result/{task_id}` for completion.
+    The number of output files depends on the model (2 for MDX models, 6 for htdemucs_6s).
+    """
+    if model_filename not in ALLOWED_MODELS:
+        raise HTTPException(
+            400,
+            f"Unknown model '{model_filename}'. Must be one of: {sorted(ALLOWED_MODELS)}",
+        )
+    if model_manager.active_model != "separator":
+        raise HTTPException(
+            503,
+            {
+                "error": "Separator is not loaded. POST /v1/models/load first.",
+                "hint": '{"model": "separator"}',
+                "active_model": model_manager.active_model,
+            },
+        )
+
+    task_id = str(uuid.uuid4())
+
+    # Preserve the original file extension so audio-separator names outputs correctly
+    suffix = Path(file.filename or "audio").suffix or ".mp3"
+    upload_path = UPLOAD_DIR / f"{task_id}{suffix}"
+    UPLOAD_DIR.mkdir(parents=True, exist_ok=True)
+    with upload_path.open("wb") as f_out:
+        shutil.copyfileobj(file.file, f_out)
+
+    separator_runner.submit(task_id, upload_path, model_filename)
+    return {"task_id": task_id}
+
+
+@app.get(
+    "/v1/separator/result/{task_id}",
+    tags=["separator"],
+    summary="Poll a stem separation task result",
+)
+async def separator_result(task_id: str):
+    """Returns task status.
+
+    - `pending` / `running` while in progress
+    - `complete` — includes `files`: list of output filenames (download via `/v1/separator/download/{filename}`)
+    - `error` — includes `error` message
+    """
+    task = separator_runner.get_task(task_id)
+    if task is None:
+        raise HTTPException(404, f"Task '{task_id}' not found")
+    return {"task_id": task_id, **{k: v for k, v in task.items() if k != "created_at"}}
+
+
+@app.get(
+    "/v1/separator/download/{filename}",
+    tags=["separator"],
+    summary="Download a separated stem file",
+)
+async def separator_download(filename: str):
+    """Download a stem MP3 file produced by a completed separation task.
+
+    `filename` is one of the entries from the `files` list in the result response.
+    """
+    # Prevent path traversal
+    safe_name = Path(filename).name
+    file_path = OUTPUT_DIR / safe_name
+    if not file_path.is_file():
+        raise HTTPException(404, f"File '{safe_name}' not found")
+    return FileResponse(
+        str(file_path),
+        media_type="audio/mpeg",
+        headers={"Content-Disposition": f'attachment; filename="{safe_name}"'},
+    )
+
+
+# ---------------------------------------------------------------------------
+# Entry point
+# ---------------------------------------------------------------------------
+
+def main():
+    uvicorn.run(app, host="0.0.0.0", port=8000, log_level="info")
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,21 @@
+[project]
+name = "kgone-gateway"
+version = "0.1.0"
+description = "Unified REST API gateway for ACE-Step 1.5 and Foundation-1"
+requires-python = ">=3.10"
+dependencies = [
+    "fastapi>=0.110.0",
+    "uvicorn[standard]>=0.27.0",
+    "httpx>=0.27.0",
+    "python-multipart>=0.0.9",
+]
+
+[project.scripts]
+kgone = "main:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["services", "foundation1_server"]
@@ -0,0 +1,4 @@
+"""ACE-Step service constants and configuration."""
+
+ACESTEP_PORT = 8001
+ACESTEP_BASE_URL = f"http://127.0.0.1:{ACESTEP_PORT}"
@@ -0,0 +1,4 @@
+"""Foundation-1 service constants and configuration."""
+
+FOUNDATION1_PORT = 8002
+FOUNDATION1_BASE_URL = f"http://127.0.0.1:{FOUNDATION1_PORT}"
@@ -0,0 +1,126 @@
+"""GPU model manager — ensures only one model subprocess runs at a time."""
+
+from __future__ import annotations
+
+import asyncio
+import logging
+import subprocess
+import time
+from pathlib import Path
+from typing import Optional
+
+import httpx
+
+ROOT_DIR = Path(__file__).parent.parent
+
+ACESTEP_PORT = 8001
+FOUNDATION1_PORT = 8002
+HEALTH_POLL_INTERVAL = 2.0
+HEALTH_TIMEOUT_SECONDS = 180  # model loading can be slow on first run
+
+logger = logging.getLogger(__name__)
+
+
+def _python_exe(venv_dir: Path) -> Path:
+    """Return the Python executable for a given venv directory."""
+    win = venv_dir / "Scripts" / "python.exe"
+    if win.exists():
+        return win
+    return venv_dir / "bin" / "python"
+
+
+class ModelNotActiveError(Exception):
+    def __init__(self, requested: str, active: Optional[str]) -> None:
+        self.requested = requested
+        self.active = active
+        super().__init__(f"Model '{requested}' is not loaded (active: {active!r})")
+
+
+class ModelManager:
+    def __init__(self) -> None:
+        self.active_model: Optional[str] = None
+        self._lock = asyncio.Lock()
+        self._process: Optional[subprocess.Popen] = None
+
+    async def load(self, model: str) -> None:
+        """Load a model, unloading the currently active one first if needed."""
+        async with self._lock:
+            if self.active_model == model:
+                logger.info("Model '%s' is already active.", model)
+                return
+            if self.active_model is not None:
+                logger.info("Unloading model '%s'...", self.active_model)
+                await asyncio.get_event_loop().run_in_executor(None, self._stop_process)
+            logger.info("Starting model '%s'...", model)
+            await asyncio.get_event_loop().run_in_executor(None, self._start_process, model)
+            self.active_model = model
+            logger.info("Model '%s' is ready.", model)
+
+    async def unload(self) -> None:
+        """Unload the active model."""
+        async with self._lock:
+            if self.active_model is None:
+                return
+            logger.info("Unloading model '%s'...", self.active_model)
+            await asyncio.get_event_loop().run_in_executor(None, self._stop_process)
+
+    def _stop_process(self) -> None:
+        if self._process is None:
+            return
+        try:
+            self._process.terminate()
+            self._process.wait(timeout=30)
+        except subprocess.TimeoutExpired:
+            logger.warning("Process did not terminate gracefully, killing.")
+            self._process.kill()
+            self._process.wait()
+        except Exception as exc:
+            logger.error("Error stopping process: %s", exc)
+        finally:
+            self._process = None
+        self.active_model = None
+
+    def _start_process(self, model: str) -> None:
+        if model == "fullsong":
+            self._process = self._launch_acestep()
+            self._wait_healthy(f"http://127.0.0.1:{ACESTEP_PORT}/health")
+        elif model == "clip":
+            self._process = self._launch_foundation1()
+            self._wait_healthy(f"http://127.0.0.1:{FOUNDATION1_PORT}/health")
+        elif model == "separator":
+            pass  # no persistent process; previous model already stopped by load(), VRAM is free
+        else:
+            raise ValueError(f"Unknown model: '{model}'. Must be 'fullsong', 'clip', or 'separator'.")
+
+    def _launch_acestep(self) -> subprocess.Popen:
+        venv_python = _python_exe(ROOT_DIR / "ace-step" / ".venv")
+        cmd = [str(venv_python), "-c", "from acestep.api_server import main; main()"]
+        logger.info("Launching ACE-Step: %s", " ".join(cmd))
+        return subprocess.Popen(cmd, cwd=str(ROOT_DIR / "ace-step"))
+
+    def _launch_foundation1(self) -> subprocess.Popen:
+        venv_python = _python_exe(ROOT_DIR / "foundation1" / ".venv")
+        server_script = str(ROOT_DIR / "foundation1_server" / "server.py")
+        cmd = [str(venv_python), server_script]
+        logger.info("Launching Foundation-1 server: %s", " ".join(cmd))
+        return subprocess.Popen(cmd, cwd=str(ROOT_DIR))
+
+    def _wait_healthy(self, url: str) -> None:
+        deadline = time.monotonic() + HEALTH_TIMEOUT_SECONDS
+        logger.info("Waiting for service at %s ...", url)
+        while time.monotonic() < deadline:
+            try:
+                with httpx.Client(timeout=5.0) as client:
+                    resp = client.get(url)
+                    if resp.status_code == 200:
+                        logger.info("Service healthy: %s", url)
+                        return
+            except Exception:
+                pass
+            time.sleep(HEALTH_POLL_INTERVAL)
+        raise TimeoutError(
+            f"Service at {url} did not become healthy within {HEALTH_TIMEOUT_SECONDS}s"
+        )
+
+
+model_manager = ModelManager()
@@ -0,0 +1,120 @@
+"""Stem separator runner — invokes audio-separator CLI per-request.
+
+Uses a single-worker ThreadPoolExecutor to serialize GPU use.
+Coordinates with model_manager: callers should check model_manager.active_model
+before submitting, and model load routes should check separator_runner.active.
+"""
+
+from __future__ import annotations
+
+import logging
+import subprocess
+import threading
+import time
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+from typing import Optional
+
+ROOT_DIR = Path(__file__).parent.parent
+SEPARATOR_DIR = ROOT_DIR / "separator"
+OUTPUT_DIR = ROOT_DIR / "outputs" / "separator"
+UPLOAD_DIR = ROOT_DIR / "uploads" / "separator"
+
+ALLOWED_MODELS = frozenset([
+    "UVR-MDX-NET-Inst_HQ_3.onnx",
+    "MDX23C-8KFFT-InstVoc_HQ.ckpt",
+    "htdemucs_6s.yaml",
+])
+
+logger = logging.getLogger(__name__)
+
+
+class SeparatorRunner:
+    def __init__(self) -> None:
+        self._tasks: dict[str, dict] = {}
+        self._executor = ThreadPoolExecutor(max_workers=1)
+        self._running_count = 0
+        self._lock = threading.Lock()
+
+    @property
+    def active(self) -> bool:
+        with self._lock:
+            return self._running_count > 0
+
+    def submit(self, task_id: str, file_path: Path, model_filename: str) -> None:
+        """Schedule a separation task. Returns immediately; poll get_task() for status."""
+        self._tasks[task_id] = {"status": "pending", "created_at": time.time()}
+        with self._lock:
+            self._running_count += 1
+        self._executor.submit(self._run, task_id, file_path, model_filename)
+
+    def get_task(self, task_id: str) -> Optional[dict]:
+        return self._tasks.get(task_id)
+
+    def _run(self, task_id: str, file_path: Path, model_filename: str) -> None:
+        self._tasks[task_id]["status"] = "running"
+        try:
+            cmd = [
+                "uv", "run", "audio-separator",
+                str(file_path),
+                "--model_filename", model_filename,
+                "--output_dir", str(OUTPUT_DIR),
+                "--output_format", "MP3",
+            ]
+            logger.info("Running separator: %s", " ".join(cmd))
+            proc = subprocess.Popen(
+                cmd,
+                cwd=str(SEPARATOR_DIR),
+                stdout=subprocess.PIPE,
+                stderr=subprocess.STDOUT,  # merge stderr into stdout
+                text=True,
+                bufsize=1,
+            )
+            output_lines: list[str] = []
+
+            def _read_output() -> None:
+                for line in proc.stdout:
+                    stripped = line.rstrip()
+                    logger.info("[separator] %s", stripped)
+                    output_lines.append(stripped)
+
+            reader = threading.Thread(target=_read_output, daemon=True)
+            reader.start()
+            try:
+                proc.wait(timeout=600)
+            except subprocess.TimeoutExpired:
+                proc.kill()
+                proc.wait()
+                raise RuntimeError("audio-separator timed out after 600s")
+            finally:
+                reader.join(timeout=5)
+
+            if proc.returncode != 0:
+                detail = "\n".join(output_lines[-20:]) or "unknown error"
+                raise RuntimeError(f"audio-separator exited {proc.returncode}: {detail}")
+
+            # Collect output files — named {input_stem}_{stem_type}_{model_base}.mp3
+            stem = file_path.stem
+            files = sorted(p.name for p in OUTPUT_DIR.glob(f"{stem}_*"))
+            if not files:
+                raise RuntimeError("audio-separator completed but produced no output files")
+
+            self._tasks[task_id].update({"status": "complete", "files": files})
+            logger.info("Separation complete for task %s: %s", task_id, files)
+        except Exception:
+            logger.exception("Separation failed for task %s", task_id)
+            self._tasks[task_id].update({
+                "status": "error",
+                "error": "Separation failed — check server logs.",
+            })
+        finally:
+            with self._lock:
+                self._running_count -= 1
+            # Clean up upload file after processing
+            try:
+                file_path.unlink(missing_ok=True)
+            except Exception:
+                pass
+
+
+separator_runner = SeparatorRunner()
@@ -0,0 +1,20 @@
+{
+  "ace-step": {
+    "url": "https://github.com/ace-step/ACE-Step-1.5.git",
+    "commit": "2d14b9e070aff945fd8b3dc3491a4386b91702a6",
+    "description": "Merge PR #793 feat/jetson-docker-support (2026-03-08)",
+    "dir": "ace-step"
+  },
+  "foundation1": {
+    "url": "https://github.com/RoyalCities/RC-stable-audio-tools.git",
+    "commit": "f1f13af77cb9bc34dd6eb001b2430b3c85375ea2",
+    "description": "Foundation-1 Support (2026-03-16)",
+    "dir": "foundation1"
+  },
+  "python-audio-separator": {
+    "url": "https://github.com/nomadkaraoke/python-audio-separator.git",
+    "commit": "0a644dbb07d94a7e747d5265e3abbaf600459449",
+    "description": "fix: synchronous endpoint + Cloud Run scaling (2026-03-26)",
+    "dir": "separator"
+  }
+}
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