"""Fresh art for stale project pages — Oracle, Lyra Technique, Garuda, Agni, Meridian.

Matching site aesthetic: navy/gold, no human faces on product pages,
abstract/architectural, the feel of the tool working.
"""
import torch, os, gc, time
os.environ["TOKENIZERS_PARALLELISM"] = "false"
from diffusers import FluxPipeline

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

pipe = FluxPipeline.from_pretrained(
    "black-forest-labs/FLUX.1-dev",
    torch_dtype=torch.bfloat16,
    safety_checker=None, requires_safety_checker=False,
)
pipe.to("mps")

PROJECTS = {
    "oracle": (
        "A vast circular diagnostic instrument made of dark navy metal and gold, "
        "suspended in space. Concentric rings rotate independently — each ring inscribed "
        "with geometric patterns that glow amber when active. At the center, a lens focuses "
        "golden light onto a stream of flowing data rendered as a luminous ribbon. "
        "The instrument is reading something, measuring, diagnosing — you can feel it working. "
        "No figures, no text. Deep navy background with warm gold accents. "
        "The aesthetic of a precision measurement device that sees what the output hides."
    ),
    "lyra_technique": (
        "A cross-section of layered geometric space — imagine slicing through a transformer's "
        "internal representation and seeing the structure. Parallel planes of dark navy, each with "
        "different gold patterns: one shows spectral ridges (sharp peaks), another shows flat entropy "
        "(smooth), another shows branching pathways. The planes are slightly transparent, stacked, "
        "with golden threads connecting corresponding points between layers. "
        "The feel of looking inside a mind and seeing geometry where thoughts should be. "
        "Abstract, architectural, precise. Navy and gold only."
    ),
    "garuda": (
        "A golden eagle rendered in geometric, architectural style — not naturalistic but structural. "
        "Wings spread wide, each feather is a sharp angular plate of burnished gold against deep navy. "
        "The eagle's eye is a lens, scanning. Below it, faint red threads represent intercepted threats — "
        "thin, fragile against the eagle's mass. The eagle doesn't chase the threats; it watches, "
        "assesses, decides. Heraldic but modern. The feel of a sentinel that devours serpents. "
        "No text. Navy background, gold and amber eagle, red threat indicators."
    ),
    "agni": (
        "A crucible of dark navy ceramic filled with molten gold — but the gold is being tested. "
        "Seven geometric probes descend into the liquid, each glowing a different shade of amber "
        "depending on what they find. Some glow bright (passing), some glow dim (failing). "
        "The crucible has fine cracks filled with cooled gold (kintsugi). Around it, faint traces "
        "of rejected material — things that didn't survive the fire. "
        "The feel of purification through rigorous testing. "
        "Abstract, no figures, no text. Navy ceramic, molten gold, amber probes."
    ),
    "meridian": (
        "A compass rose made of intersecting golden arcs on a dark navy field, "
        "but the arcs are alive — papers, documents, data streams flowing along the curves "
        "toward a central nexus point where they converge and transform into structured knowledge. "
        "The streams come from all directions. Some are bright (relevant), some dim (filtered out). "
        "At the center, a small dense cluster of interconnected golden nodes — the knowledge graph "
        "being built in real time. The feel of a swarm that never sleeps, finding what matters. "
        "No figures, no text. Navy background, gold arcs and streams."
    ),
}

for name, prompt in PROJECTS.items():
    for seed in [137, 2026]:
        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}")