ai-chatbot/lib/ai/replacement-product-identity.ts

export type ReplacementProductViewSummary = {
  imageIndex: number;
  cameraSummary: string;
  visibleStructure: string;
};

export type ReplacementProductIdentityProfile = {
  identitySummary: string;
  structureSummary: string;
  structuralRisks: string;
  viewSummaries: ReplacementProductViewSummary[];
};

function extractJsonObject(value: string) {
  const source = String(value || "").trim();
  const fenced = source.match(/```(?:json)?\s*([\s\S]*?)```/i)?.[1]?.trim();
  const candidate = fenced || source;
  const start = candidate.indexOf("{");
  const end = candidate.lastIndexOf("}");
  return start >= 0 && end > start ? candidate.slice(start, end + 1) : null;
}

function normalizeText(value: unknown, maxLength: number) {
  return String(value || "")
    .trim()
    .replace(/\s+/g, " ")
    .slice(0, maxLength);
}

export function normalizeReplacementProductImageIndexes(
  value: unknown,
  productImageCount: number,
  maxSelected = 2,
) {
  if (!Array.isArray(value)) return [];

  const safeCount = Math.max(0, Math.floor(productImageCount));
  const safeLimit = Math.max(1, Math.floor(maxSelected));
  const selected: number[] = [];

  value.forEach((item) => {
    const index = Math.round(Number(item));
    if (
      Number.isFinite(index) &&
      index >= 1 &&
      index <= safeCount &&
      !selected.includes(index)
    ) {
      selected.push(index);
    }
  });

  return selected.slice(0, safeLimit);
}

export function parseReplacementProductIdentityProfile(
  value: string,
  productImageCount: number,
): ReplacementProductIdentityProfile | null {
  const jsonText = extractJsonObject(value);
  if (!jsonText) return null;

  try {
    const parsed = JSON.parse(jsonText) as Record<string, unknown>;
    const rawViews = Array.isArray(parsed.viewSummaries)
      ? parsed.viewSummaries
      : Array.isArray(parsed.views)
        ? parsed.views
        : [];
    const viewSummaries = rawViews
      .map((value) => {
        if (!value || typeof value !== "object" || Array.isArray(value)) {
          return null;
        }
        const record = value as Record<string, unknown>;
        const [imageIndex] = normalizeReplacementProductImageIndexes(
          [record.imageIndex ?? record.index],
          productImageCount,
          1,
        );
        if (!imageIndex) return null;
        return {
          imageIndex,
          cameraSummary: normalizeText(
            record.cameraSummary ?? record.camera ?? record.view,
            120,
          ),
          visibleStructure: normalizeText(
            record.visibleStructure ?? record.visibleFeatures ?? record.structure,
            180,
          ),
        } satisfies ReplacementProductViewSummary;
      })
      .filter((value): value is ReplacementProductViewSummary => Boolean(value))
      .filter(
        (value, index, values) =>
          values.findIndex((candidate) => candidate.imageIndex === value.imageIndex) === index,
      )
      .slice(0, Math.max(0, Math.floor(productImageCount)));

    const identitySummary = normalizeText(
      parsed.identitySummary ?? parsed.productSummary ?? parsed.identity,
      260,
    );
    const structureSummary = normalizeText(
      parsed.structureSummary ?? parsed.structuralInvariants ?? parsed.structure,
      520,
    );
    const structuralRisks = normalizeText(
      parsed.structuralRisks ?? parsed.forbiddenMutations ?? parsed.risks,
      320,
    );

    if (!identitySummary && !structureSummary && viewSummaries.length === 0) {
      return null;
    }

    return {
      identitySummary,
      structureSummary,
      structuralRisks,
      viewSummaries,
    };
  } catch {
    return null;
  }
}

export function buildReplacementProductIdentityAnalysisPrompt(productImageCount: number) {
  const safeCount = Math.max(1, Math.floor(productImageCount));
  return [
    "你是商品结构身份分析器。下面按顺序提供同一商品的多角度产品图。",
    `共有 ${safeCount} 张图，图片编号从 1 到 ${safeCount}。`,
    "只分析商品本身，不分析透明背景、白边、阴影或后期抠图瑕疵。",
    "identitySummary：概括商品类别、整体轮廓、材质、颜色和稳定识别特征。",
    "structureSummary：列出不可改变的几何拓扑，包括构件数量、左右对应关系、腿/支架/横梁/侧框/层板/把手/转轴的形状、粗细、连接点、开口方向、排列和比例。不要把不同视角下的同一构件误判为不同设计。",
    "structuralRisks：列出最容易被生成模型误画的结构，以及必须禁止的新增、删除、弯曲、分叉、熔合、悬空、错接、镜像和左右不一致。",
    "viewSummaries：逐图说明拍摄角度、可见面和最清楚展示的结构，imageIndex 必须使用 1 开始的原始图片编号。",
    "对于桌、椅、柜架、置物架等家具，必须明确腿型和框架拓扑，例如口字型、K/X/A/V 型或直腿；不得含糊写成‘保持结构一致’。",
    "只返回严格 JSON，不要解释。",
    '{"identitySummary":"不超过100字","structureSummary":"不超过220字","structuralRisks":"不超过140字","viewSummaries":[{"imageIndex":1,"cameraSummary":"不超过50字","visibleStructure":"不超过80字"}]}',
  ].join("\n");
}

export function formatReplacementProductIdentityProfile(
  profile: ReplacementProductIdentityProfile,
) {
  return [
    profile.identitySummary ? `商品身份：${profile.identitySummary}` : "",
    profile.structureSummary ? `结构拓扑：${profile.structureSummary}` : "",
    profile.structuralRisks ? `高风险误画：${profile.structuralRisks}` : "",
    ...profile.viewSummaries.map(
      (view) =>
        `产品图${view.imageIndex}：${[view.cameraSummary, view.visibleStructure]
          .filter(Boolean)
          .join("；")}`,
    ),
  ]
    .filter(Boolean)
    .join("\n");
}

export function buildReplacementProductStructureLockLines(params: {
  productImageCount: number;
  identitySummary?: string | null;
  structureSummary?: string | null;
  structuralRisks?: string | null;
}) {
  if (params.productImageCount <= 0) return [];

  return [
    "【产品结构身份锁（高于旧详情图中的旧产品结构）】",
    params.identitySummary ? `目标商品身份：${params.identitySummary}` : "",
    params.structureSummary ? `目标商品结构拓扑：${params.structureSummary}` : "",
    params.structuralRisks ? `重点防错：${params.structuralRisks}` : "",
    "前面的产品输入图共同定义要换入的新产品；最后一张详情底板只决定新产品在页面中的拍摄角度、朝向、占比、位置和透视，绝不决定新产品的腿型、支撑杆拓扑、构件数量或连接方式。",
    "必须逐项核对商品主体外轮廓、构件数量、左右对应关系、粗细、直线/曲线方向、开口方向，以及腿、支架、横梁、侧框、层板、把手和转轴的真实连接点；所有可见构件必须连续、合理承重且前后一致。",
    "对于桌、椅、柜架和置物架，严禁把口字型框架改成 K/X/A/V 型或相反，严禁新增、删除、弯曲、分叉、熔合、悬空、错接、镜像任何腿和横梁，严禁左右两侧生成不同结构。",
    "旧详情图里的旧商品结构必须完整移除，不得与新产品结构混合。结构准确优先于风格化和无痕融合；无法兼顾时宁可减少改动，也不能改造产品结构。",
  ].filter(Boolean);
}