type LayoutReplaceModelDescriptor = {
  capabilities?: unknown;
  displayName?: string | null;
  healthStatus?: string | null;
  id: string;
  imageGenConfig?: unknown;
  isDefault?: boolean | null;
  isSubModel?: boolean | null;
  modelId?: string | null;
  supportsImageGen?: boolean | null;
  supportsVision?: boolean | null;
};

type LayoutReplaceProviderDescriptor = {
  type?: string | null;
};

export type CanvasLayoutReplaceModelCandidate = {
  model: LayoutReplaceModelDescriptor;
  provider: LayoutReplaceProviderDescriptor;
};

const MODEL_PREFERENCE_PATTERNS: RegExp[] = [
  /^snapgen\/gpt-image-2$/i,
  /^gpt-image-2(?:-vip)?$/i,
  /^openai\/gpt-image-2-developer\/edit$/i,
  /^openai\/gpt-image-2\/edit$/i,
  /^bytedance\/seedream-v5(?:\.0)?-pro\/edit$/i,
  /^qwen\/qwen-image-2(?:\.0)?-pro\/edit$/i,
  /gpt-image.*\/edit/i,
  /seedream.*\/edit/i,
  /qwen-image.*\/edit/i,
  /(?:^|[\s/_-])edit(?:$|[\s/_-])/i,
];

const PROVIDER_PREFERENCE = new Map([
  ["vip98k", 30],
  ["atlascloud", 25],
  ["openai-image", 20],
  ["volcano-vision", 15],
  ["snapgen-image", 10],
]);

function readPositiveNumber(source: unknown, keys: string[]) {
  if (!source || typeof source !== "object") return null;
  const record = source as Record<string, unknown>;
  for (const key of keys) {
    const parsed = Number(record[key]);
    if (Number.isFinite(parsed) && parsed > 0) return parsed;
  }
  return null;
}

function getConfiguredReferenceImageLimit(model: LayoutReplaceModelDescriptor) {
  return (
    readPositiveNumber(model.imageGenConfig, [
      "maxReferenceImages",
      "maxInputImages",
    ]) ||
    readPositiveNumber(model.capabilities, [
      "maxReferenceImages",
      "maxInputImages",
    ])
  );
}

function getModelDescriptor(candidate: CanvasLayoutReplaceModelCandidate) {
  return JSON.stringify([
    candidate.model.modelId,
    candidate.model.displayName,
    candidate.model.capabilities,
    candidate.model.imageGenConfig,
  ]).toLowerCase();
}

export function isCanvasLayoutReplaceModelEligible(
  candidate: CanvasLayoutReplaceModelCandidate,
) {
  if (String(candidate.provider.type || "").trim() === "fal-image") return false;
  if (!candidate.model.supportsImageGen || candidate.model.isSubModel) return false;
  if (candidate.model.supportsVision === false) return false;
  if (candidate.model.healthStatus === "auto_disabled") return false;

  const referenceImageLimit = getConfiguredReferenceImageLimit(candidate.model);
  // supportsVision alone does not mean that the image-generation invocation
  // accepts two inputs. Unknown/single-image limits cannot preserve both roles.
  return referenceImageLimit !== null && referenceImageLimit >= 2;
}

function getCanvasLayoutReplaceModelScore(
  candidate: CanvasLayoutReplaceModelCandidate,
) {
  const modelId = String(candidate.model.modelId || "").trim();
  const descriptor = getModelDescriptor(candidate);
  const preferenceIndex = MODEL_PREFERENCE_PATTERNS.findIndex(
    (pattern) => pattern.test(modelId) || pattern.test(descriptor),
  );
  const modelScore =
    preferenceIndex >= 0 ? (MODEL_PREFERENCE_PATTERNS.length - preferenceIndex) * 100 : 0;
  // A preferred model alias on a degraded account must not outrank a healthy
  // multi-image editor (e.g. an otherwise preferred but depleted reseller).
  const healthScore = candidate.model.healthStatus === "healthy" ? 2000 : 0;
  const providerScore =
    PROVIDER_PREFERENCE.get(candidate.provider.type || "") || 0;
  const defaultScore = candidate.model.isDefault ? 5 : 0;
  return modelScore + healthScore + providerScore + defaultScore;
}

export function rankCanvasLayoutReplaceModels(
  models: CanvasLayoutReplaceModelCandidate[],
  requestedModel?: string | null,
) {
  const eligible = models.filter(isCanvasLayoutReplaceModelEligible);
  const requested = String(requestedModel || "").trim();

  return eligible.sort((left, right) => {
    if (requested && requested !== "auto") {
      const leftRequested =
        left.model.id === requested || left.model.modelId === requested;
      const rightRequested =
        right.model.id === requested || right.model.modelId === requested;
      if (leftRequested !== rightRequested) return leftRequested ? -1 : 1;
    }

    const scoreDifference =
      getCanvasLayoutReplaceModelScore(right) -
      getCanvasLayoutReplaceModelScore(left);
    if (scoreDifference !== 0) return scoreDifference;
    return left.model.id.localeCompare(right.model.id);
  });
}

export function buildCanvasLayoutReplacePrompt(params: {
  referenceHeight?: number;
  referenceWidth?: number;
  sourceProductAspectRatio?: number;
  supplementalPrompt?: string;
}) {
  const geometry =
    params.referenceWidth && params.referenceHeight
      ? `${params.referenceWidth}x${params.referenceHeight}`
      : "与图1完全相同";
  const supplement = String(params.supplementalPrompt || "").trim();
  const sourceProductAspectRatio =
    Number.isFinite(params.sourceProductAspectRatio) &&
    Number(params.sourceProductAspectRatio) > 0
      ? Number(params.sourceProductAspectRatio)
      : null;
  const sourceProductRatioConstraint = sourceProductAspectRatio
    ? `【新商品轮廓】图2透明前景测得的商品外框宽高比约为 ${sourceProductAspectRatio.toFixed(3)}:1，只允许整体等比缩放与平移，不得改变各部件的比例。`
    : "";

  return [
    "执行商品模版替换，最终只输出一张完整成图。",
    "【图片角色与方向】图1是目标模版底图，是最终场景、版式、文字和构图的唯一依据。图2是新商品身份图，只提供需要放入模版的新商品。必须在图1中换入图2商品，绝对不能把图1的旧商品搬入图2的背景。",
    "【编辑底图】以图1作为实际编辑底图，识别并移除图1的旧商品，在对应位置放入图2的新商品；不使用图2的背景、房间、墙面、地面、装饰、文字或水印。图2即使是有背景的实拍图，也必须结合图1旧商品的类别，定位图2对应的新商品主体，不能把源图整个场景或无关物件当成新商品。",
    "【商品身份】忠实保留图2商品的外形、颜色、材质、部件数量、分区和相对比例，不得把图1旧商品的款式、配色或结构混入新商品。按实际图片识别商品，不能凭空增加抽屉、门、腿或其他零件。商品完整出现一次，不裁切、不拼接、不复制。",
    sourceProductRatioConstraint,
    "【模版版式和原有文字】保留图1原有标题、品牌、价格、标签、卖点、图标和其他可见文案，以及它们的内容、字体风格、位置和层级。只替换商品；不能把电商海报变成无字场景照片。图1没有文字时不新增文字。模版中其他独立物件和背景保留原有位置及遮挡关系。",
    `【画布与融合】输出画布为 ${geometry}，宽高比和图1一致。将新商品整体等比缩放、放置在模版中合理的商品位置，保持真实结构；只调整必要的接触阴影、环境色和光照以融入图1，不重构整个场景。`,
    supplement ? `【用户补充】${supplement}。补充仅约束商品替换细节，不改变两张图的职责、商品身份或模版版式。` : "",
    "【输出前检查】确认输出沿用了图1的模版，而商品确实来自图2；检查商品配色、结构和部件，检查原有文案与布局是否保留。只输出最终成图，不输出并排对比、拼图、多方案、说明文字、新增边框或水印。",
  ].filter(Boolean).join("\n\n");
}