John King
eed95c45f6
Each family gets its own mflux CLI — they do not accept each other's flags. Z-Image 4-bit runs in ~6GB, viable on the 16-32GB boxes. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
164 lines
6.3 KiB
Python
164 lines
6.3 KiB
Python
import argparse
|
|
import json
|
|
import os
|
|
import shlex
|
|
import subprocess
|
|
import sys
|
|
import time
|
|
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 p.get("prompt"):
|
|
print("ERROR: prompt is required")
|
|
sys.exit(1)
|
|
|
|
model = p.get("model", "flux2-klein-4b")
|
|
steps = int(p.get("steps", 4))
|
|
outdir = Path(a.outdir)
|
|
out_png = outdir / f"flux_{model.replace('/', '_')}_s{p.get('seed', 42)}.png"
|
|
bindir = Path(sys.executable).parent
|
|
|
|
# Each family needs a different mflux CLI, and they do NOT accept each other's flags.
|
|
# z-image/qwen are separate architectures from FLUX despite living in the same venv.
|
|
if model.startswith("flux2-"):
|
|
cli = bindir / "mflux-generate-flux2"
|
|
model_args = ["--model", model]
|
|
quant_args = [] # klein is small; skip quantization flags
|
|
guidance_args = [] # distilled klein: guidance fixed at 1.0
|
|
elif model in ("z-image", "z-image-turbo"):
|
|
# Alibaba Z-Image (DiT). filipstrand's 4-bit MLX build runs in ~6GB, which is what
|
|
# makes it viable on the 16-32GB boxes. Turbo is few-step: 6-10, not 25.
|
|
cli = bindir / ("mflux-generate-z-image-turbo" if model.endswith("turbo")
|
|
else "mflux-generate-z-image")
|
|
model_args = ["--base-model", model]
|
|
if model == "z-image-turbo":
|
|
model_args += ["-m", p.get("hf_repo", "filipstrand/Z-Image-Turbo-mflux-4bit")]
|
|
quant = str(p.get("quantize", "4"))
|
|
quant_args = ["-q", quant] if quant in ("3", "4", "5", "6", "8") else []
|
|
guidance_args = []
|
|
elif model == "qwen":
|
|
cli = bindir / "mflux-generate-qwen"
|
|
model_args = ["--base-model", "qwen"]
|
|
quant = str(p.get("quantize", "4"))
|
|
quant_args = ["-q", quant] if quant in ("3", "4", "5", "6", "8") else []
|
|
guidance_args = []
|
|
elif model == "schnell-4bit":
|
|
cli = bindir / "mflux-generate"
|
|
# ungated community pre-quantized weights (~10GB) — no HF license wall
|
|
model_args = ["--model", "dhairyashil/FLUX.1-schnell-mflux-4bit",
|
|
"--base-model", "schnell"]
|
|
quant_args = []
|
|
guidance_args = []
|
|
else:
|
|
cli = bindir / "mflux-generate"
|
|
model_args = ["--model", model]
|
|
quant = str(p.get("quantize", "8"))
|
|
quant_args = ["--quantize", quant] if quant in ("4", "8") else []
|
|
guidance_args = (["--guidance", str(p.get("guidance", 3.5))]
|
|
if model in ("dev", "krea-dev") else [])
|
|
|
|
if not cli.exists():
|
|
print(f"ERROR: mflux CLI not installed ({cli} missing). Run scripts/install_mflux.sh")
|
|
sys.exit(1)
|
|
|
|
# ---- LoRA -------------------------------------------------------------------
|
|
# THE RULE: a LoRA only works on its own base architecture. Loading an SD1.5 LoRA on
|
|
# FLUX, or a FLUX.1 LoRA on FLUX.2, is a SILENT no-op — mflux does not error, the image
|
|
# just comes back unchanged and you blame the LoRA. So we fail loudly on a missing file
|
|
# and log exactly what was applied.
|
|
#
|
|
# `lora` accepts a path, a bare filename resolved against LORA_DIRS, or a list. Weights
|
|
# come from `lora_weight` (scalar or list, default 0.8).
|
|
lora_dirs = [Path(d).expanduser() for d in
|
|
os.environ.get("MB_LORA_DIRS",
|
|
"~/Documents/localmodels/Lora:~/Documents/civit-lib/sd15/Lora:"
|
|
"~/Documents/civit-lib/sdxl/Lora:~/Documents/loras").split(":")]
|
|
|
|
|
|
def resolve_lora(name):
|
|
q = Path(name).expanduser()
|
|
if q.is_file():
|
|
return q
|
|
for d in lora_dirs:
|
|
c = d / name
|
|
if c.is_file():
|
|
return c
|
|
if not name.endswith(".safetensors"):
|
|
c = d / f"{name}.safetensors"
|
|
if c.is_file():
|
|
return c
|
|
return None
|
|
|
|
|
|
lora_args = []
|
|
raw = p.get("lora") or p.get("loras") or []
|
|
if isinstance(raw, str):
|
|
raw = [raw] if raw.strip() else []
|
|
if raw:
|
|
weights = p.get("lora_weight", p.get("lora_scales", 0.8))
|
|
if not isinstance(weights, list):
|
|
weights = [weights] * len(raw)
|
|
paths, scales = [], []
|
|
for i, nm in enumerate(raw):
|
|
# allow "name=0.7" shorthand
|
|
if isinstance(nm, str) and "=" in nm and not Path(nm).exists():
|
|
nm, _, w = nm.rpartition("=")
|
|
try:
|
|
weights[i] = float(w)
|
|
except ValueError:
|
|
pass
|
|
hit = resolve_lora(nm)
|
|
if not hit:
|
|
print(f"ERROR: LoRA not found: {nm}")
|
|
print(f" searched: {', '.join(str(d) for d in lora_dirs)}")
|
|
sys.exit(1)
|
|
paths.append(str(hit))
|
|
scales.append(str(weights[i] if i < len(weights) else 0.8))
|
|
lora_args = ["--lora-paths", *paths, "--lora-scales", *scales]
|
|
for pth, sc in zip(paths, scales):
|
|
print(f"[lora] {Path(pth).name} @ {sc}", flush=True)
|
|
|
|
cmd = [str(cli), *model_args,
|
|
"--prompt", p["prompt"],
|
|
"--steps", str(steps),
|
|
"--width", str(p.get("width", 1024)),
|
|
"--height", str(p.get("height", 1024)),
|
|
"--seed", str(p.get("seed", 42)),
|
|
"--output", str(out_png),
|
|
*quant_args, *guidance_args, *lora_args]
|
|
|
|
print("+", " ".join(shlex.quote(c) for c in cmd), flush=True)
|
|
print("(first run per model downloads weights from HuggingFace)", flush=True)
|
|
env = os.environ.copy()
|
|
# hf_xet's chunked downloader intermittently fails ("Unable to parse string as
|
|
# hex hash value"); the plain HTTP path is reliable.
|
|
env["HF_HUB_DISABLE_XET"] = "1"
|
|
t0 = time.time()
|
|
res = subprocess.run(cmd, stdout=sys.stdout, stderr=subprocess.STDOUT, env=env)
|
|
if res.returncode != 0:
|
|
print("HINT: gated-repo/auth errors mean this model needs an HF license accept "
|
|
"+ token (Settings → HuggingFace token). flux2-klein-4b, schnell-4bit and "
|
|
"z-image-turbo are ungated and need nothing.")
|
|
sys.exit(res.returncode)
|
|
elapsed = round(time.time() - t0, 1)
|
|
|
|
if not out_png.exists():
|
|
pngs = sorted(outdir.glob("*.png"))
|
|
if not pngs:
|
|
print("ERROR: no image produced")
|
|
sys.exit(1)
|
|
out_png = pngs[-1]
|
|
|
|
(outdir / "result.json").write_text(json.dumps({"outputs": [
|
|
{"path": out_png.name,
|
|
"meta": {"tool": "mflux", "model": model, "steps": steps,
|
|
"seed": p.get("seed", 42), "seconds": elapsed,
|
|
"loras": [Path(x).name for x in lora_args[1:1 + len(raw)]] if raw else []}}]}))
|
|
print(f"done in {elapsed}s: {out_png.name}", flush=True)
|