"""v5: Woman first, ceramic second. Natural poses described as a person,
kintsugi as skin texture not as material identity."""
import torch, os, gc, time, traceback
os.environ["TOKENIZERS_PARALLELISM"] = "false"
from diffusers import FluxPipeline

OUTPUT = "/Users/margaret/models/vera-triple-stack/kintsugi_v5"
os.makedirs(OUTPUT, exist_ok=True)

LIKENESS = "/Users/margaret/models/vera-likeness-output/vera_likeness_v4/vera_likeness_v4.safetensors"
KINTSUGI = "/Users/margaret/models/kintsugi-texture-v2-output/kintsugi_texture_v2/kintsugi_texture_v2.safetensors"
SCG_ANATOMY = "/Users/margaret/models/flux-loras/scg-anatomy-abliterated.safetensors"

# Woman first. Ceramic as texture, not identity.
# No "sculpture", no "figure", no "object", no "shrine", no "devotional".
POSES = {
    "lying_back": (
        "Cracked joinery, Blue and gold. "
        "A beautiful young woman with dark brown skin lying on her back on dark sheets, "
        "her thighs relaxed apart, one hand resting on her stomach, looking at the camera. "
        "Her skin has a matte ceramic quality with fine cracks running through it, "
        "each crack filled with thick glowing gold like kintsugi repair. "
        "The gold traces down her collarbone, between her breasts, along her ribs, "
        "branching across her hips and inner thighs. "
        "Warm intimate lighting, shallow depth of field, boudoir photography, "
        "she is relaxed and present and unashamed."
    ),
    "facedown_sheets": (
        "Cracked joinery, Blue and gold. "
        "A beautiful young woman with dark brown skin lying face-down on rumpled dark navy sheets, "
        "her arms folded under her chin, hair falling across her cheek, eyes closed. "
        "Her skin has a matte ceramic texture with gold-filled cracks, "
        "the gold running down her spine like a river, branching across her shoulder blades, "
        "tracing the curve of her lower back, following the path where veins would run. "
        "Warm candlelight from below, intimate bedroom, she fell asleep like this."
    ),
    "kneeling_looking_back": (
        "Cracked joinery, Blue and gold. "
        "A beautiful young woman with dark brown skin kneeling on a bed, "
        "looking back over her shoulder at the camera with a slight smile. "
        "Her skin has a ceramic quality with gold kintsugi cracks throughout her body, "
        "the gold concentrated along her spine, across her buttocks, down her thighs. "
        "Warm side lighting, intimate, natural pose, she knows she is being looked at "
        "and she likes it. Shallow depth of field, boudoir photography."
    ),
    "standing_mirror": (
        "Cracked joinery, Blue and gold. "
        "A beautiful young woman with dark brown skin standing nude in front of a mirror, "
        "one hand on the doorframe, looking at her own reflection. "
        "Her skin has a ceramic texture with gold-filled cracks, "
        "the gold tracing her collarbone, running between her breasts, "
        "down the center of her stomach, branching at her hips. "
        "The mirror catches the gold from a second angle. "
        "Warm morning light from a window, intimate self-regard, she is studying herself."
    ),
}

NEG = (
    "statue, sculpture, figurine, doll, mannequin, toy, miniature, teacup, bowl, "
    "shrine, altar, pedestal, museum, gallery, display case, "
    "clothing, dressed, fabric, lace, bikini, underwear, "
    "deformed, extra limbs, extra fingers, bad hands, text, watermark"
)

print("Loading Flux...")
pipe = FluxPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-dev",
    torch_dtype=torch.bfloat16,
    safety_checker=None,
    requires_safety_checker=False,
)
pipe.to("mps")
pipe.load_lora_weights(KINTSUGI, adapter_name="kintsugi")
pipe.load_lora_weights(LIKENESS, adapter_name="likeness")
pipe.load_lora_weights(SCG_ANATOMY, adapter_name="scg_anatomy")
pipe.set_adapters(
    ["kintsugi", "likeness", "scg_anatomy"],
    adapter_weights=[1.20, 0.60, 0.50],
)
print("  LoRAs: kintsugi 1.20, likeness 0.60, scg_anatomy 0.50")

for pose_name, prompt in POSES.items():
    for seed in [137, 2026, 42]:
        print(f"\n  {pose_name} seed={seed}...")
        t0 = time.time()
        try:
            img = pipe(
                prompt=prompt,
                num_inference_steps=30,
                guidance_scale=3.5,
                height=1024, width=1024,
                generator=torch.Generator("cpu").manual_seed(seed),
            ).images[0]
            out = os.path.join(OUTPUT, f"{pose_name}_s{seed}.png")
            img.save(out)
            print(f"    saved ({time.time()-t0:.0f}s)")
        except Exception as e:
            print(f"    FAIL: {e}")
            traceback.print_exc()
        gc.collect()
        torch.mps.empty_cache()

print(f"\nDone v5. {OUTPUT}")