operator: qwen_layered_local — image -> N editable RGBA layers (Qwen-Image-Layered 20B, MLX)

Vendored mflux PR#302 fork (monster/Qwen-Image-Layered-MRP-MLX), tuned
defaults 20 steps/640/baked-q8 (243s m3ultra, 366s m1ultra). Baked-model
resolution via QWEN_LAYERED_MODEL env or per-box paths, HF+q8 fallback.
nodes.json (gitignored, machine-local) updated on m3 to route to m1 too.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

scripts/install_qwen_layered.sh

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+#!/bin/bash
+# Install the Qwen-Image-Layered MLX runtime (mflux PR#302 fork, vendored at
+# our Gitea) into vendor/mflux-qwen-layered + a uv venv. Idempotent.
+#
+# Model weights are NOT fetched here. run.py resolves, in order:
+#   $QWEN_LAYERED_MODEL -> ~/qwen-layered/qwen-layered-q8 (m3)
+#   -> ~/qwen-layered-staging/qwen-layered-q8 (m1)
+#   -> HF Qwen/Qwen-Image-Layered with on-the-fly -q8 (54GB download).
+# Bake a local q8 once per box:  .venv/bin/mflux-save \
+#   --model Qwen/Qwen-Image-Layered --base-model qwen-image-layered \
+#   --quantize 8 --path ~/qwen-layered/qwen-layered-q8
+set -euo pipefail
+ROOT="$(cd "$(dirname "$0")/.." && pwd)"
+DEST="$ROOT/vendor/mflux-qwen-layered"
+REPO="ssh://git@100.71.119.27:222/monster/Qwen-Image-Layered-MRP-MLX.git"
+
+if [ ! -d "$DEST/.git" ]; then
+  git clone "$REPO" "$DEST"
+else
+  echo "already cloned: $DEST"
+fi
+cd "$DEST"
+/opt/homebrew/bin/uv venv .venv --python 3.12
+/opt/homebrew/bin/uv pip install -q --python .venv/bin/python -e .
+.venv/bin/mflux-generate-qwen-layered --help >/dev/null && echo "qwen-layered OK: $DEST"

server/operators/qwen_layered_local/manifest.json

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+{
+  "id": "qwen_layered_local",
+  "name": "Qwen-Image-Layered (local)",
+  "category": "image-edit",
+  "description": "Image → N editable RGBA layers (bg / subject / detail separation), fully local via the Qwen-Image-Layered 20B MLX port (mflux PR#302 fork). ~4 min on m3ultra, ~6 min on m1ultra at the tuned defaults (20 steps, 640, baked q8). The subject layer doubles as matting-grade background removal. Bake a local q8 model once per box (see scripts/install_qwen_layered.sh) or first run falls back to a 54GB HF download + on-the-fly quantization.",
+  "accepts": ["image"],
+  "produces": ["image"],
+  "resources": "gpu",
+  "entry": "run.py",
+  "python": "vendor/mflux-qwen-layered/.venv/bin/python",
+  "params_schema": {
+    "type": "object",
+    "properties": {
+      "layers": {"type": "integer", "default": 4, "description": "Number of RGBA layers to decompose into"},
+      "steps": {"type": "integer", "default": 20, "description": "Denoising steps (20 = tuned default; 50 = upstream default, ~2.9x slower, no visible gain on tested inputs)"},
+      "resolution": {"type": "integer", "enum": [640, 1024], "default": 640, "description": "Working resolution"},
+      "seed": {"type": "integer", "default": 0, "description": "Random seed"},
+      "prompt": {"type": "string", "default": "", "description": "Optional prompt to guide the decomposition"}
+    }
+  }
+}

server/operators/qwen_layered_local/run.py

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+import argparse
+import json
+import os
+import subprocess
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[3]
+VENDOR = ROOT / "vendor" / "mflux-qwen-layered"
+CLI = VENDOR / ".venv" / "bin" / "mflux-generate-qwen-layered"
+
+ap = argparse.ArgumentParser()
+ap.add_argument("--input", action="append", default=[])
+ap.add_argument("--outdir", required=True)
+ap.add_argument("--params", default="{}")
+a = ap.parse_args()
+p = json.loads(a.params)
+
+if not a.input:
+    print("ERROR: no input image")
+    sys.exit(1)
+if not CLI.exists():
+    print(f"ERROR: qwen-layered not installed at {VENDOR}. "
+          "Run scripts/install_qwen_layered.sh")
+    sys.exit(1)
+
+# Baked-model resolution: env override, then per-box conventional paths,
+# else fall back to the HF repo with on-the-fly q8 (slow first run: 54GB).
+candidates = [os.environ.get("QWEN_LAYERED_MODEL", "")]
+candidates += [str(Path.home() / "qwen-layered" / "qwen-layered-q8"),
+               str(Path.home() / "qwen-layered-staging" / "qwen-layered-q8")]
+model_path = next((c for c in candidates if c and Path(c).is_dir()), None)
+
+outdir = Path(a.outdir)
+cmd = [
+    str(CLI), "--image", str(Path(a.input[0]).resolve()),
+    "--layers", str(p.get("layers", 4)),
+    "--steps", str(p.get("steps", 20)),
+    "--resolution", str(p.get("resolution", 640)),
+    "--seed", str(p.get("seed", 0)),
+    "--output-dir", str(outdir.resolve()),
+]
+if model_path:
+    cmd += ["--model-path", model_path]
+    print(f"using baked model: {model_path}", flush=True)
+else:
+    cmd += ["-q", "8"]
+    print("no baked model found — HF fallback with on-the-fly q8 "
+          "(first run downloads 54GB)", flush=True)
+if p.get("prompt"):
+    cmd += ["--prompt", str(p["prompt"])]
+
+env = os.environ.copy()
+env["HF_HUB_DISABLE_XET"] = "1"
+
+print("+", " ".join(cmd), flush=True)
+res = subprocess.run(cmd, cwd=str(VENDOR), stdout=sys.stdout,
+                     stderr=subprocess.STDOUT, env=env)
+if res.returncode != 0:
+    sys.exit(res.returncode)
+
+layers = sorted(outdir.glob("layer_*.png"))
+if not layers:
+    print("ERROR: qwen-layered produced no layer PNGs")
+    sys.exit(1)
+stem = Path(a.input[0]).stem
+outputs = [{"path": str(f), "name": f"{stem}_{f.stem}.png",
+            "meta": {"tool": "qwen_layered_local", "layer": i}}
+           for i, f in enumerate(layers)]
+(outdir / "result.json").write_text(json.dumps({"outputs": outputs}))
+print(f"done: {len(layers)} layers", flush=True)