import argparse
import json
import os
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 the fleet-standard stash, which is
# present on BOTH mflux nodes (m3ultra + ultra) — a job can dispatch to either,
# so a node-local dir would resolve on one and fail on the other.
# mflux natively takes --lora-paths/--lora-scales; a LoRA for the wrong base
# model is a SILENT no-op (no error, the edit just ignores it).
LORA_DIRS = [Path(d).expanduser() for d in
             (os.environ.get("QWEN_LORA_DIRS") or "").split(os.pathsep) if d.strip()] \
    or [Path.home() / "Documents" / "localmodels" / "QwenLora"]
if p.get("loras"):
    paths, scales = [], []
    avail = {}
    for d in LORA_DIRS:
        for f in d.rglob("*.safetensors"):
            avail.setdefault(f.name.lower(), f)
    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)