import argparse import json import subprocess import sys from pathlib import Path 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 p.get("prompt"): print("ERROR: prompt is required — describe the edit you want") sys.exit(1) cli = Path(sys.executable).parent / "mflux-generate-qwen-edit" if not cli.exists(): print(f"ERROR: {cli} missing. Run scripts/install_mflux.sh") sys.exit(1) src = Path(a.input[0]) outdir = Path(a.outdir) out = outdir / f"{src.stem}_edited.png" # ALL inputs go to Qwen (it composes up to ~3 images: "put the shirt from image 2 on the person # in image 1"). Single-image jobs behave exactly as before. cmd = [str(cli), "--image-paths", *[str(Path(x).resolve()) for x in a.input], "--prompt", p["prompt"], "--steps", str(p.get("steps", 25)), "--seed", str(p.get("seed", 42)), "--guidance", str(p.get("guidance", 4.0)), "--output", str(out.resolve())] # Qwen-Edit LoRAs: "name" or "name:scale", comma-separated. Names resolve # (case-insensitive prefix match) against ~/Documents/localmodels/qwen-loras, # which mirrors ultra's civit/_parked-qwen stash. mflux natively takes # --lora-paths/--lora-scales; a LoRA for the wrong base is a silent no-op. LORA_DIR = Path.home() / "Documents" / "localmodels" / "qwen-loras" if p.get("loras"): paths, scales = [], [] avail = {f.name.lower(): f for f in LORA_DIR.rglob("*.safetensors")} for item in str(p["loras"]).split(","): item = item.strip() if not item: continue name, _, scale = item.partition(":") name = name.strip().lower() hit = avail.get(name) or avail.get(name + ".safetensors") or next( (f for k, f in sorted(avail.items()) if k.startswith(name)), None) if not hit: print(f"ERROR: no LoRA matching '{name}' under {LORA_DIR}") print("available:", ", ".join(sorted(f.stem for f in avail.values())[:40])) sys.exit(1) paths.append(str(hit)) scales.append(str(float(scale) if scale.strip() else 1.0)) if paths: cmd += ["--lora-paths", *paths, "--lora-scales", *scales] print("+", " ".join(cmd), flush=True) print("(first run downloads Qwen-Image-Edit weights)", flush=True) res = subprocess.run(cmd, cwd=str(outdir), stdout=sys.stdout, stderr=subprocess.STDOUT) if res.returncode != 0: sys.exit(res.returncode) pngs = sorted(outdir.rglob("*.png")) if not pngs: print("ERROR: no edited image produced") sys.exit(1) img = out if out.exists() else pngs[-1] (outdir / "result.json").write_text(json.dumps( {"outputs": [{"path": img.name, "meta": {"tool": "qwen-image-edit"}}]})) print(f"done: {img.name}", flush=True)