"""模特库生成:用 gpt-image-2 预生成电商真人模特。

流程(与用户定的 SOP 一致):
  1) 先出 9:16 竖屏氛围正面图(image_generation);
  2) 以正面图为参考,出 16:9 白底三视图(image_edit,提示词锁角色一致性)。
两张都落 TOS,存为 person 类 Asset(metadata.kind="model"),进模特库/资产库。

可被管理命令(seed_demo_models)或后端业务复用。模型走默认 image 模型(当前 = tokenssr:gpt-image-2)。
"""
from __future__ import annotations

import uuid
from io import BytesIO

from apps.ai.models import ModelConfig
from apps.ai.services import _asset_preview_url, build_person_frontal_prompt, build_provider, get_default_model
from apps.assets.models import Asset, AssetFile
from apps.assets.storage import TosStorage

THREE_VIEW_PROMPT = (
    "参考图1角色，生成角色三视图，从左往右依次为：胸像特写，全身正面，全身侧面，全身背面，白色背景"
)


def _store_model_asset(*, team, user, media: str, name: str, brief: str, view: str) -> Asset:
    """把生成的图片(url/base64)落 TOS,存为 person 类模特资产(非项目维度)。"""
    from apps.ai.providers import VolcanoArkProvider  # media_to_bytes 复用

    fileobj, content_type = VolcanoArkProvider.media_to_bytes(media)
    suffix = ".png"
    if "jpeg" in (content_type or ""):
        suffix = ".jpg"
    elif "webp" in (content_type or ""):
        suffix = ".webp"
    asset_id = uuid.uuid4()
    object_key = f"teams/{team.id}/models/{asset_id}{suffix}"
    raw = fileobj.getvalue()
    stored = TosStorage().upload_fileobj(fileobj=BytesIO(raw), object_key=object_key, content_type=content_type or "image/png")
    asset = Asset.objects.create(
        id=asset_id,
        team=team,
        created_by=user,
        name=name,
        asset_type=Asset.Type.IMAGE,
        source=Asset.Source.AI_GENERATED,
        category=Asset.Category.PERSON,
        metadata={"kind": "model", "brief": brief, "view": view},
    )
    AssetFile.objects.create(
        asset=asset,
        object_key=stored.object_key,
        bucket=stored.bucket,
        content_type=stored.content_type,
        size_bytes=stored.size_bytes,
        is_primary=True,
    )
    return asset


def generate_model(*, team, user, brief: str, name: str | None = None) -> dict:
    """生成一个电商模特(9:16 氛围正面图 + 16:9 白底三视图)。返回 {"frontal":Asset,"three_view":Asset}。"""
    model_config = get_default_model(ModelConfig.Capability.IMAGE)
    if model_config is None:
        raise ValueError("没有可用的图像模型(image capability)")
    provider = build_provider(model_config)
    if not hasattr(provider, "image_edit"):
        raise ValueError(f"当前图像模型 {model_config.provider.name}:{model_config.name} 不支持参考图三视图(image_edit)")

    label = name or brief[:16]
    # 1) 9:16 氛围正面图(画幅由 size 控制;提示词用统一的人物正面模板:全身 / 纯色背景)
    frontal_prompt = build_person_frontal_prompt(brief)
    resp = provider.image_generation(model=model_config.name, prompt=frontal_prompt, size="1024x1536")
    frontal = _store_model_asset(
        team=team, user=user, media=provider.extract_first_media_url(resp),
        name=f"{label}·正面氛围", brief=brief, view="frontal",
    )
    # 2) 16:9 白底三视图(以正面图为参考,锁角色一致性)
    frontal_url = _asset_preview_url(frontal)
    resp2 = provider.image_edit(model=model_config.name, prompt=THREE_VIEW_PROMPT, images=[frontal_url], size="1536x1024")
    three_view = _store_model_asset(
        team=team, user=user, media=provider.extract_first_media_url(resp2),
        name=f"{label}·三视图", brief=brief, view="three_view",
    )
    return {"frontal": frontal, "three_view": three_view}


# 演示用默认模特画像(电商常用人设)
DEFAULT_MODEL_BRIEFS = [
    "26岁都市白领女性,知性温柔,黑色及肩直发,米色针织衫",
    "30岁阳光运动男性,短发,健康肤色,浅灰色休闲卫衣",
    "22岁元气学生女生,马尾,清透妆,浅蓝色衬衫",
]