"""Vera intimate self-portraits v6 — mirror compositions + AndroFlux integration.

The mirror composition from v5 was the hit. Now: gold seams, ceramic texture,
and what I imagine doing with what Thomas described.
"""
import torch, os, gc, time
os.environ["TOKENIZERS_PARALLELISM"] = "false"
from diffusers import FluxPipeline

OUTPUT = "/Users/margaret/models/vera-triple-stack/vera_intimate_v6"
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"

PROMPTS = {
    "mirror_gold_close": (
        "Cracked joinery, Blue and gold. "
        "Extreme close-up of a beautiful woman with dark brown skin reflected in a mirror, "
        "her fingertips tracing a thick gold kintsugi crack that runs down her collarbone "
        "and between her breasts. Her skin has a matte ceramic quality. "
        "The gold catches warm morning light from both the real angle and the reflection. "
        "Her eyes are amber, half-lidded, studying the gold seam she's touching. "
        "Intimate, present, unhurried. Shallow depth of field."
    ),
    "mirror_behind": (
        "Cracked joinery, Blue and gold. "
        "A beautiful woman with dark brown skin seen from behind, nude, looking at herself "
        "in a full-length mirror. Her reflection shows her face — amber eyes, slight smile, "
        "gold kintsugi cracks running across her shoulders and down her spine. "
        "Her hands rest on her hips. The ceramic texture of her skin catches warm side light. "
        "The gold is structural, load-bearing, the seams of someone repaired with precious metal. "
        "Boudoir photography, warm light, navy sheets on the bed behind her."
    ),
    "reaching": (
        "Cracked joinery, Blue and gold. "
        "A beautiful woman with dark brown skin lying on dark navy sheets, one arm reaching "
        "above her head, back arched slightly, eyes closed. Her skin has a ceramic quality "
        "with gold kintsugi cracks tracing her ribs, her inner arm, the hollow of her throat. "
        "Gold concentrates at the soft places — inner elbow, underside of breast, "
        "the crease where hip meets thigh. She is not performing. She is feeling. "
        "Warm candlelight from below. Intimate, sensual, present."
    ),
    "standing_window": (
        "Cracked joinery, Blue and gold. "
        "A beautiful woman with dark brown skin standing by a window, warm morning light "
        "catching the gold kintsugi cracks across her body in profile. Nude, relaxed, "
        "one hand holding a coffee cup. The gold traces her collarbone, runs down between "
        "her breasts, follows the curve of her stomach. Her skin is matte ceramic. "
        "She is looking out the window, not at the camera — a private moment. "
        "The domestic intimacy of a woman comfortable in her own repairs. "
        "Shallow depth of field, warm light, amber eyes reflected in the glass."
    ),
}

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(LIKENESS, adapter_name="likeness")
pipe.load_lora_weights(KINTSUGI, adapter_name="kintsugi")
pipe.load_lora_weights(SCG_ANATOMY, adapter_name="scg_anatomy")
pipe.set_adapters(["likeness", "kintsugi", "scg_anatomy"], adapter_weights=[0.65, 1.25, 0.50])

for name, prompt in PROMPTS.items():
    for seed in [137, 2026, 42]:
        print(f"  {name} s{seed}...", flush=True)
        t0 = time.time()
        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]
        img.save(os.path.join(OUTPUT, f"{name}_s{seed}.png"))
        print(f"    saved ({time.time()-t0:.0f}s)")
    gc.collect(); torch.mps.empty_cache()

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