import { NextRequest, NextResponse } from "next/server";
import { auth } from "@/app/(auth)/auth";
import { fetchImageBufferFromUrl } from "@/lib/ai/rmbg/service";
import { uploadFile } from "@/lib/storage/service";

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

const DEFAULT_WIDTH = 790;
const DEFAULT_HEIGHT = 1300;
const MAX_DIMENSION = 4096;

function bufferToArrayBuffer(buffer: Buffer): ArrayBuffer {
  return buffer.buffer.slice(
    buffer.byteOffset,
    buffer.byteOffset + buffer.byteLength,
  ) as ArrayBuffer;
}

function normalizeDimension(value: unknown, fallback: number) {
  const next = Math.round(Number(value));
  if (!Number.isFinite(next) || next <= 0) return fallback;
  return Math.min(MAX_DIMENSION, Math.max(64, next));
}

function normalizeFit(value: unknown) {
  const fit = String(value || "").trim();
  return fit === "contain" ? "contain" : "cover-top";
}

async function createThumbnailBuffer(buffer: Buffer) {
  const sharp = (await import("sharp")).default;
  return sharp(buffer, { failOn: "none" })
    .resize(500, null, {
      fit: "inside",
      withoutEnlargement: true,
    })
    .jpeg({ quality: 82, mozjpeg: true })
    .toBuffer();
}

export async function POST(request: NextRequest) {
  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().catch(() => ({}))) as Record<string, unknown>;
    const imageUrl = String(body.imageUrl || "").trim();
    if (!/^https?:\/\//i.test(imageUrl)) {
      return NextResponse.json({ success: false, error: "缺少有效图片地址" }, { status: 400 });
    }

    const width = normalizeDimension(body.width, DEFAULT_WIDTH);
    const height = normalizeDimension(body.height, DEFAULT_HEIGHT);
    const fit = normalizeFit(body.fit);
    const sourceBuffer = await fetchImageBufferFromUrl(imageUrl);
    const sharp = (await import("sharp")).default;
    const pipeline = sharp(sourceBuffer, { failOn: "none" }).rotate();
    const normalizedBuffer =
      fit === "contain"
        ? await pipeline
            .resize(width, height, {
              fit: "contain",
              position: "centre",
              background: { r: 255, g: 255, b: 255, alpha: 1 },
              withoutEnlargement: false,
            })
            .png()
            .toBuffer()
        : await pipeline
            .resize(width, height, {
              fit: "cover",
              position: "top",
              withoutEnlargement: false,
            })
            .png()
            .toBuffer();
    const thumbnailBuffer = await createThumbnailBuffer(normalizedBuffer);
    const suffix = `${Date.now()}-${Math.random().toString(36).slice(2, 8)}`;
    const [originalUpload, thumbnailUpload] = await Promise.all([
      uploadFile(`agent-detail-normalized-${suffix}.png`, bufferToArrayBuffer(normalizedBuffer)),
      uploadFile(`agent-detail-normalized-thumb-${suffix}.jpg`, bufferToArrayBuffer(thumbnailBuffer)),
    ]);

    return NextResponse.json({
      success: true,
      data: {
        originalUrl: originalUpload.url,
        thumbnailUrl: thumbnailUpload.url,
        imageSize: `${width}x${height}`,
      },
    });
  } catch (error) {
    console.error("[Agent Detail Image Normalize] Failed:", error);
    return NextResponse.json(
      {
        success: false,
        error: error instanceof Error ? error.message : "详情图尺寸归一化失败",
      },
      { status: 500 },
    );
  }
}