import { NextResponse } from "next/server";
import { z } from "zod";
import { auth } from "@/app/(auth)/auth";
import { callQwen3Vl } from "@/lib/ai/qwen3-vl";

export const runtime = "nodejs";
export const maxDuration = 120;

const requestSchema = z.object({
  imageUrl: z.string().min(1, "图片地址不能为空"),
  originalText: z.string().min(1, "原文不能为空"),
  currentText: z.string().optional(),
  title: z.string().optional(),
  pageTexts: z.array(z.string()).optional(),
  audience: z.string().optional(),
  usageScenario: z.string().optional(),
  coreNeed: z.string().optional(),
  productName: z.string().optional(),
  workflowSummary: z.string().optional(),
  workflowPrompt: z.string().optional(),
  userPrompt: z.string().optional(),
  presetName: z.string().optional(),
});

interface SuggestionItem {
  text: string;
  reason?: string;
}

function parseJsonText(raw: string): any | null {
  if (!raw) return null;

  const trimmed = raw.trim();
  try {
    return JSON.parse(trimmed);
  } catch {
    // continue
  }

  const markdownJsonMatch = trimmed.match(/```json\s*([\s\S]*?)\s*```/i);
  if (markdownJsonMatch?.[1]) {
    try {
      return JSON.parse(markdownJsonMatch[1]);
    } catch {
      // continue
    }
  }

  const objectMatch = trimmed.match(/\{[\s\S]*\}/);
  if (objectMatch?.[0]) {
    try {
      return JSON.parse(objectMatch[0]);
    } catch {
      // continue
    }
  }

  return null;
}

function normalizeText(value?: string | null, maxLength = 240) {
  return String(value || "").replace(/\s+/g, " ").trim().slice(0, maxLength);
}

function countMeaningfulChars(value: string) {
  return normalizeText(value, 500).replace(/\s+/g, "").length;
}

function uniqueStrings(values: string[]) {
  return Array.from(new Set(values.map((item) => normalizeText(item, 240)).filter(Boolean)));
}

function sanitizeSuggestions(items: unknown[], originalText: string): SuggestionItem[] {
  const seen = new Set<string>();
  const normalizedOriginal = normalizeText(originalText, 240);
  const suggestions: SuggestionItem[] = [];

  for (const entry of items) {
    const raw =
      entry && typeof entry === "object" && !Array.isArray(entry)
        ? (entry as Record<string, unknown>)
        : null;
    const text = normalizeText(raw?.text as string, 120);
    if (!text || seen.has(text)) {
      continue;
    }
    seen.add(text);
    suggestions.push({
      text,
      reason: normalizeText((raw?.reason as string) || "", 60) || undefined,
    });
    if (suggestions.length >= 5) {
      break;
    }
  }

  if (suggestions.length === 0 && normalizedOriginal) {
    return [{ text: normalizedOriginal, reason: "原文保留" }];
  }

  return suggestions;
}

function buildSuggestionPrompt(params: {
  originalText: string;
  currentText: string;
  title: string;
  pageTexts: string[];
  audience: string;
  usageScenario: string;
  coreNeed: string;
  productName: string;
  workflowSummary: string;
  workflowPrompt: string;
  userPrompt: string;
  presetName: string;
}) {
  const baseText = params.currentText || params.originalText;
  const targetLength = Math.max(2, countMeaningfulChars(baseText));
  const tolerance = Math.max(2, Math.min(8, Math.round(targetLength * 0.35)));
  const minLength = Math.max(2, targetLength - tolerance);
  const maxLength = targetLength + tolerance;
  const pageTexts = uniqueStrings(params.pageTexts).slice(0, 12);

  return [
    "你是电商营销设计里的文案微调助手，要根据图片内容和上下文，为图片中的单条文案生成可直接替换的备选句。",
    "请特别注意：",
    "1. 输出 5 条中文备选文案。",
    "2. 文案字数必须接近原文，尽量控制在接近范围内。",
    `3. 当前目标文案长度参考：约 ${targetLength} 字，可接受范围 ${minLength}-${maxLength} 字（按不含空格的视觉字数理解）。`,
    "4. 风格要让用户向往和代入，少一些直接叫卖式表达，少用专业术语，多用大白话，多写体感和生活感。",
    "5. 要结合给定的人群、场景、核心需求和整页语境，但不要脱离原文所在层级。",
    "6. 如果原文看起来更像品牌名、型号、编号、价格或固定信息，就不要强行写成夸张广告词，应给更稳妥、接近原意的版本。",
    "7. 不要输出解释性长文，不要加引号、编号、emoji。",
    "8. 只返回 JSON，格式必须是：{\"suggestions\":[{\"text\":\"...\",\"reason\":\"...\"}]}。",
    "",
    `当前模块：${params.presetName || "详情替换结果图改字"}`,
    `图片区域标题：${params.title || "未命名结果图"}`,
    `待改原文：${params.originalText}`,
    params.currentText && params.currentText !== params.originalText
      ? `当前输入框内容：${params.currentText}`
      : "",
    params.productName ? `产品名称：${params.productName}` : "",
    params.audience ? `目标人群：${params.audience}` : "",
    params.usageScenario ? `使用场景：${params.usageScenario}` : "",
    params.coreNeed ? `核心需求：${params.coreNeed}` : "",
    params.userPrompt ? `用户补充提示词：${params.userPrompt}` : "",
    params.workflowSummary ? `工作流摘要：${params.workflowSummary}` : "",
    params.workflowPrompt ? `工作流风格要求：${params.workflowPrompt}` : "",
    pageTexts.length > 0 ? `当前整页其它文案参考：${pageTexts.join(" / ")}` : "",
    "",
    "请输出 5 条能直接替换这条文字的候选文案，每条都要贴合图片语境。",
  ]
    .filter(Boolean)
    .join("\n");
}

export async function POST(request: Request) {
  try {
    const session = await auth();
    if (!session?.user?.id) {
      return NextResponse.json({ success: false, error: "未登录" }, { status: 401 });
    }

    const body = await request.json();
    const parsed = requestSchema.safeParse(body);
    if (!parsed.success) {
      return NextResponse.json(
        { success: false, error: parsed.error.errors[0]?.message || "参数错误" },
        { status: 400 }
      );
    }

    const imageUrl = normalizeText(parsed.data.imageUrl, 2000);
    if (!/^https?:\/\//i.test(imageUrl)) {
      return NextResponse.json(
        { success: false, error: "仅支持 URL 图片，不允许 base64 传输" },
        { status: 400 }
      );
    }

    const originalText = normalizeText(parsed.data.originalText, 120);
    const currentText = normalizeText(parsed.data.currentText, 120);
    const prompt = buildSuggestionPrompt({
      originalText,
      currentText,
      title: normalizeText(parsed.data.title, 120),
      pageTexts: Array.isArray(parsed.data.pageTexts) ? parsed.data.pageTexts : [],
      audience: normalizeText(parsed.data.audience, 120),
      usageScenario: normalizeText(parsed.data.usageScenario, 120),
      coreNeed: normalizeText(parsed.data.coreNeed, 120),
      productName: normalizeText(parsed.data.productName, 120),
      workflowSummary: normalizeText(parsed.data.workflowSummary, 500),
      workflowPrompt: normalizeText(parsed.data.workflowPrompt, 800),
      userPrompt: normalizeText(parsed.data.userPrompt, 300),
      presetName: normalizeText(parsed.data.presetName, 80),
    });

    const result = await callQwen3Vl({
      imageUrl,
      prompt,
      temperature: 0.5,
      maxTokens: 900,
      timeoutMs: 50000,
      retries: 1,
    });

    const parsedJson = parseJsonText(result.text || "");
    const suggestions = sanitizeSuggestions(parsedJson?.suggestions || [], originalText);

    if (suggestions.length === 0) {
      return NextResponse.json(
        { success: false, error: "未生成可用文案建议" },
        { status: 500 }
      );
    }

    return NextResponse.json({
      success: true,
      data: {
        suggestions,
        model: result.model,
      },
    });
  } catch (error) {
    console.error("[Canvas Text Copy Suggestions] Error:", error);
    return NextResponse.json(
      {
        success: false,
        error: error instanceof Error ? error.message : "文案建议生成失败",
      },
      { status: 500 }
    );
  }
}