/**
 * 场景裂变 API
 * 
 * 将一张产品图批量融合到多个场景图中
 * 支持多种生图模型：阿里生图、RUXA、Gemini、既梦
 */

import { NextResponse } from "next/server";
import { z } from "zod";
import { auth } from "@/app/(auth)/auth";
import { db } from "@/lib/db";
import { generatedImage } from "@/lib/db/schema";
import { getEnabledAiModelsWithProvider, getSystemSetting } from "@/lib/db/queries";
import { uploadFile } from "@/lib/storage/service";
import sharp from "sharp";
import { createAlibabaImage } from "@/lib/ai/providers/alibaba-image";
import { createGeminiImage } from "@/lib/ai/providers/gemini-image";
import { createVolcanoVision } from "@/lib/ai/providers/volcano-vision";
import { createRuxaImage } from "@/lib/ai/providers/ruxa-image";

// 请求体 Schema
const sceneFusionRequestSchema = z.object({
  productImage: z.string().min(1, "产品图不能为空"),
  productName: z.string().optional(), // 产品名称（如"沙发"）
  aspectRatio: z.string().optional(), // 图片比例（如"1:1", "4:3", "auto"）
  imageSize: z.string().optional(), // 图片分辨率（如"1K", "2K", "4K"）
  scenes: z.array(z.object({
    id: z.string(),
    image: z.string().min(1, "场景图不能为空"),
    targetName: z.string().optional(), // 背景中需要被替换的物体名称（如"椅子"）
    customPrompt: z.string().optional(),
  })).min(1, "至少需要一个场景图").max(20, "最多支持20个场景图"),
});

// 默认提示词（当数据库未配置时使用）- 使用"参考"的表述方式
const FALLBACK_PROMPT = "请参考第一张图片中的产品，将其自然地融合到第二张图片的场景中。要求：1)保持产品的整体外观、颜色、形状和设计风格与第一张图一致；2)调整产品的大小和角度以适应场景；3)注意光影和透视关系使融合自然。";

/**
 * 获取场景裂变配置
 */
async function getSceneFusionConfig() {
  try {
    const setting = await getSystemSetting({ key: "scene_fusion_config" });
    if (setting?.value) {
      const config = setting.value as {
        enabled?: boolean;
        defaultPrompt?: string;
        maxScenes?: number;
        modelId?: string;
      };
      return {
        enabled: config.enabled ?? true,
        defaultPrompt: config.defaultPrompt || FALLBACK_PROMPT,
        maxScenes: config.maxScenes ?? 10,
        modelId: config.modelId || "",
      };
    }
  } catch (error) {
    console.error("[SceneFusion] Failed to load config:", error);
  }
  
  return {
    enabled: true,
    defaultPrompt: FALLBACK_PROMPT,
    maxScenes: 10,
    modelId: "",
  };
}

/**
 * 创建缩略图
 */
async function createThumbnail(buffer: Buffer): Promise<Buffer> {
  try {
    const thumbnailBuffer = await sharp(buffer)
      .resize(400, 400, { fit: "inside", withoutEnlargement: true })
      .jpeg({ quality: 80 })
      .toBuffer();
    return thumbnailBuffer;
  } catch (error) {
    console.error("[SceneFusion] Failed to create thumbnail:", error);
    return buffer;
  }
}

/**
 * 生成唯一文件名
 */
function generateFilename(prefix: string, extension: string): string {
  const timestamp = Date.now();
  const random = Math.random().toString(36).substring(2, 8);
  return `${prefix}-${timestamp}-${random}.${extension}`;
}

/**
 * 将 Base64 图片上传到 S3 获取 URL
 */
async function uploadBase64ToS3(base64Data: string, prefix: string = "scene-fusion"): Promise<string> {
  try {
    // 移除 data URL 前缀
    const base64Clean = base64Data.replace(/^data:image\/\w+;base64,/, "");
    const buffer = Buffer.from(base64Clean, "base64");
    
    const filename = generateFilename(`${prefix}-ref`, "png");
    const result = await uploadFile(filename, buffer.buffer.slice(buffer.byteOffset, buffer.byteOffset + buffer.byteLength));
    console.log(`[SceneFusion] Uploaded reference image to: ${result.url}`);
    return result.url;
  } catch (error) {
    console.error("[SceneFusion] Failed to upload reference image:", error);
    throw error;
  }
}

/**
 * 下载图片并上传到 S3
 */
async function downloadAndUploadToS3(
  imageUrl: string,
  prefix: string = "scene-fusion"
): Promise<{ thumbnail: string; original: string }> {
  try {
    console.log("[SceneFusion] Downloading image from:", imageUrl.substring(0, 100) + "...");
    
    const response = await fetch(imageUrl);
    if (!response.ok) {
      throw new Error(`Failed to download image: ${response.status}`);
    }
    
    const buffer = Buffer.from(await response.arrayBuffer());
    console.log(`[SceneFusion] Downloaded image, size: ${buffer.length} bytes`);
    
    // 创建缩略图
    const thumbnailBuffer = await createThumbnail(buffer);
    
    // 上传原图
    const originalFilename = generateFilename(`${prefix}-orig`, "png");
    const originalResult = await uploadFile(originalFilename, buffer.buffer.slice(buffer.byteOffset, buffer.byteOffset + buffer.byteLength));
    console.log(`[SceneFusion] Uploaded original to: ${originalResult.url}`);
    
    // 上传缩略图
    const thumbnailFilename = generateFilename(`${prefix}-thumb`, "jpg");
    const thumbnailArrayBuffer = new Uint8Array(thumbnailBuffer).buffer;
    const thumbnailResult = await uploadFile(thumbnailFilename, thumbnailArrayBuffer);
    console.log(`[SceneFusion] Uploaded thumbnail to: ${thumbnailResult.url}`);
    
    return {
      original: originalResult.url,
      thumbnail: thumbnailResult.url,
    };
  } catch (error) {
    console.error("[SceneFusion] Failed to download/upload image:", error);
    throw error;
  }
}

/**
 * 根据 aspectRatio 和 imageSize 计算实际尺寸
 * @param aspectRatio - 宽高比，如 "1:1", "4:3", "16:9", "auto"
 * @param imageSize - 分辨率等级，如 "1K", "2K", "4K"
 * @returns 尺寸字符串，如 "1024*1024"，或 undefined（auto 模式）
 */
function calculateSize(aspectRatio: string, imageSize: string): string | undefined {
  // auto 模式：不设置尺寸，让 API 根据输入图片自动决定
  if (aspectRatio === "auto") {
    return undefined;
  }
  
  // 根据分辨率等级确定基准像素
  const baseSizeMap: Record<string, number> = {
    "1K": 1024,
    "2K": 1536,
    "4K": 2048,
  };
  const baseSize = baseSizeMap[imageSize] || 1536;
  
  // 根据比例计算宽高
  const ratioMap: Record<string, [number, number]> = {
    "1:1": [1, 1],
    "4:3": [4, 3],
    "3:4": [3, 4],
    "16:9": [16, 9],
    "9:16": [9, 16],
  };
  
  const ratio = ratioMap[aspectRatio];
  if (!ratio) {
    return undefined;
  }
  
  const [w, h] = ratio;
  // 保持总像素接近 baseSize * baseSize，同时维持比例
  const scale = Math.sqrt((baseSize * baseSize) / (w * h));
  let width = Math.round(w * scale);
  let height = Math.round(h * scale);
  
  // 确保宽高在 512-2048 范围内
  const clamp = (v: number) => Math.max(512, Math.min(2048, v));
  width = clamp(width);
  height = clamp(height);
  
  return `${width}*${height}`;
}

/**
 * 调用阿里生图 API
 */
async function callAlibabaImageAPI(
  baseURL: string,
  apiKey: string,
  modelId: string,
  productImageUrl: string,
  sceneImageUrl: string,
  prompt: string,
  size?: string
): Promise<string> {
  // 构建消息内容：产品图 + 场景图 + 提示词
  const content = [
    { image: productImageUrl },
    { image: sceneImageUrl },
    { text: prompt },
  ];
  
  const requestBody = {
    model: modelId,
    input: {
      messages: [
        {
          role: "user",
          content,
        },
      ],
    },
    parameters: {
      n: 1,
      ...(size && { size }),
      prompt_extend: true,
      watermark: false,
    },
  };
  
  console.log(`[SceneFusion][${modelId}] Request Debug:
    - Index: Scene ${sceneImageUrl.substring(sceneImageUrl.length-15)}
    - Product URL: ${productImageUrl}
    - Scene URL: ${sceneImageUrl}
    - Size: ${size || 'auto'}
    - Prompt: ${prompt}
  `);
  
  const response = await fetch(baseURL, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${apiKey}`,
    },
    body: JSON.stringify(requestBody),
  });
  
  const data = await response.json();
  
  // 打印完整响应用于调试
  console.log(`[SceneFusion][${modelId}] Full API Response:`, JSON.stringify(data, null, 2));
  
  if (!response.ok || data.code) {
    console.error("[SceneFusion] API Error Response:", JSON.stringify(data, null, 2));
    throw new Error(data.message || (data.code ? `Error ${data.code}: ${data.message}` : `API request failed: ${response.status}`));
  }
  
  // 提取生成的图片 URL
  const choices = data.output?.choices;
  if (!choices || choices.length === 0) {
    console.error("[SceneFusion] No choices in response, output:", data.output);
    throw new Error("No images in response");
  }
  
  const imageContent = choices[0]?.message?.content;
  console.log(`[SceneFusion] Image content array:`, JSON.stringify(imageContent, null, 2));
  
  if (!imageContent || imageContent.length === 0) {
    throw new Error("No image content in response");
  }
  
  // 遍历所有内容项，找到 image 类型的
  let generatedImageUrl: string | undefined;
  for (const item of imageContent) {
    if (item.image) {
      generatedImageUrl = item.image;
      console.log(`[SceneFusion] Found image URL in content item`);
      break;
    }
  }
  
  if (!generatedImageUrl) {
    console.error("[SceneFusion] No image URL found in content:", imageContent);
    throw new Error("No image URL in response");
  }
  
  // 检查返回的图片 URL 是否与输入相同（可能是 API 返回了原图）
  if (generatedImageUrl === productImageUrl || generatedImageUrl === sceneImageUrl) {
    console.warn(`[SceneFusion] ⚠️ WARNING: API returned same URL as input!`);
    console.warn(`[SceneFusion] - Generated URL: ${generatedImageUrl}`);
    console.warn(`[SceneFusion] - Product URL: ${productImageUrl}`);
    console.warn(`[SceneFusion] - Scene URL: ${sceneImageUrl}`);
  }
  
  console.log("[SceneFusion] Generated image URL:", generatedImageUrl.substring(0, 100) + "...");
  return generatedImageUrl;
}

/**
 * 构建智能提示词
 * @param defaultPrompt - 默认提示词模板
 * @param productName - 产品名称（如"沙发"）
 * @param targetName - 背景中需要被替换的物体名称（如"椅子"）
 * @param customPrompt - 用户补充的关键词
 */
function buildPrompt(
  defaultPrompt: string,
  productName?: string,
  targetName?: string,
  customPrompt?: string
): string {
  let prompt = defaultPrompt;
  
  // 如果用户提供了具体的产品名称和被替换物体名称，构建更精确的提示词
  // 使用"参考图1"的表述方式，并强调产品的视觉特征
  if (productName && targetName) {
    prompt = `请参考第一张图片中的${productName}，将其自然地融合到第二张图片的场景中，替换掉场景中的${targetName}。要求：1)保持${productName}的整体外观、颜色、形状和设计风格与第一张图一致；2)调整${productName}的大小和角度以适应场景；3)注意光影和透视关系使融合自然。`;
  } else if (productName) {
    prompt = `请参考第一张图片中的${productName}，将其自然地融合到第二张图片的场景中。要求：1)保持${productName}的整体外观、颜色、形状和设计风格与第一张图一致；2)调整${productName}的大小和角度以适应场景；3)注意光影和透视关系使融合自然。`;
  } else if (targetName) {
    prompt = `请参考第一张图片中的产品，将其自然地融合到第二张图片的场景中，替换掉场景中的${targetName}。要求：1)保持产品的整体外观、颜色、形状和设计风格与第一张图一致；2)调整产品的大小和角度以适应场景；3)注意光影和透视关系使融合自然。`;
  }
  
  // 添加用户补充的关键词
  if (customPrompt) {
    prompt = `${prompt} 补充要求：${customPrompt}`;
  }
  
  return prompt;
}

/**
 * 通用场景处理函数 - 根据 provider 类型调用不同的实现
 */
async function processSceneWithProvider(
  productImageUrl: string,
  sceneImageUrl: string,
  productName: string | undefined,
  targetName: string | undefined,
  customPrompt: string | undefined,
  defaultPrompt: string,
  provider: { type: string; baseUrl: string; apiKey: string },
  modelId: string,
  aspectRatio?: string,
  imageSize?: string
): Promise<{ thumbnail: string; original: string; prompt: string }> {
  // 构建智能提示词
  const prompt = buildPrompt(defaultPrompt, productName, targetName, customPrompt);
  
  console.log(`[SceneFusion] Built prompt: ${prompt}`);
  console.log(`[SceneFusion] Provider type: ${provider.type}`);
  
  // 根据 provider 类型选择不同的处理逻辑
  switch (provider.type) {
    case "alibaba-image":
      return processWithAlibabaImage(productImageUrl, sceneImageUrl, prompt, provider, modelId, aspectRatio, imageSize);
    
    case "ruxa-image":
      return processWithRuxaImage(productImageUrl, sceneImageUrl, prompt, provider, modelId, aspectRatio, imageSize);

    case "gemini":
      return processWithGemini(productImageUrl, sceneImageUrl, prompt, provider, modelId, aspectRatio, imageSize);
    
    case "volcano-vision":
      return processWithVolcanoVision(productImageUrl, sceneImageUrl, prompt, provider, modelId, aspectRatio, imageSize);
    
    default:
      throw new Error(`不支持的模型类型: ${provider.type}`);
  }
}

/**
 * 使用阿里生图模型处理
 */
async function processWithAlibabaImage(
  productImageUrl: string,
  sceneImageUrl: string,
  prompt: string,
  provider: { baseUrl: string; apiKey: string },
  modelId: string,
  aspectRatio?: string,
  imageSize?: string
): Promise<{ thumbnail: string; original: string; prompt: string }> {
  // 计算尺寸
  const size = calculateSize(aspectRatio || "auto", imageSize || "2K");
  
  // 调用阿里生图 API
  const generatedImageUrl = await callAlibabaImageAPI(
    provider.baseUrl,
    provider.apiKey,
    modelId,
    productImageUrl,
    sceneImageUrl,
    prompt,
    size
  );
  
  // 下载并上传到 S3
  const uploaded = await downloadAndUploadToS3(generatedImageUrl, "scene-fusion-alibaba");
  
  return { ...uploaded, prompt };
}

/**
 * 使用 Gemini 模型处理
 */
async function processWithGemini(
  productImageUrl: string,
  sceneImageUrl: string,
  prompt: string,
  provider: { baseUrl: string; apiKey: string },
  modelId: string,
  aspectRatio?: string,
  imageSize?: string
): Promise<{ thumbnail: string; original: string; prompt: string }> {
  console.log(`[SceneFusion][Gemini] Processing with model: ${modelId}`);
  
  // 创建 Gemini provider
  const geminiProvider = createGeminiImage({
    baseURL: provider.baseUrl,
    apiKey: provider.apiKey,
  });
  
  // 构建消息格式（Gemini 使用 OpenAI 兼容格式）
  const messages = [
    {
      role: "user",
      content: [
        { type: "image_url", image_url: { url: productImageUrl } },
        { type: "image_url", image_url: { url: sceneImageUrl } },
        { type: "text", text: prompt },
      ],
    },
  ];
  
  // 调用 Gemini API
  const result = await geminiProvider.chat(modelId).doGenerate({
    messages,
    imageParams: {
      aspectRatio: aspectRatio || "auto",
      imageSize: imageSize || "2K",
      imageCount: 1,
    },
  });
  
  // 解析返回的 Markdown 格式图片
  const { thumbnail, original } = parseImageFromMarkdown(result.text);
  
  return { thumbnail, original, prompt };
}

/**
 * 使用 RUXA 模型处理
 */
async function processWithRuxaImage(
  productImageUrl: string,
  sceneImageUrl: string,
  prompt: string,
  provider: { baseUrl: string; apiKey: string },
  modelId: string,
  aspectRatio?: string,
  imageSize?: string
): Promise<{ thumbnail: string; original: string; prompt: string }> {
  console.log(`[SceneFusion][RUXA] Processing with model: ${modelId}`);

  const ruxaProvider = createRuxaImage({
    baseURL: provider.baseUrl,
    apiKey: provider.apiKey,
  });

  const messages = [
    {
      role: "user",
      content: [
        { type: "image_url", image_url: { url: productImageUrl } },
        { type: "image_url", image_url: { url: sceneImageUrl } },
        { type: "text", text: prompt },
      ],
    },
  ];

  const result = await ruxaProvider.chat(modelId).doGenerate({
    messages,
    imageParams: {
      aspectRatio: aspectRatio || "auto",
      imageSize: imageSize || "2K",
      imageCount: 1,
    },
  });

  const { thumbnail, original } = parseImageFromMarkdown(result.text);
  return { thumbnail, original, prompt };
}

/**
 * 使用既梦/火山模型处理
 */
async function processWithVolcanoVision(
  productImageUrl: string,
  sceneImageUrl: string,
  prompt: string,
  provider: { baseUrl: string; apiKey: string },
  modelId: string,
  aspectRatio?: string,
  imageSize?: string
): Promise<{ thumbnail: string; original: string; prompt: string }> {
  console.log(`[SceneFusion][Volcano] Processing with model: ${modelId}`);
  
  // 创建 Volcano Vision provider
  const volcanoProvider = createVolcanoVision({
    baseURL: provider.baseUrl,
    apiKey: provider.apiKey,
  });
  
  // 构建消息格式
  const messages = [
    {
      role: "user",
      content: [
        { type: "image_url", image_url: { url: productImageUrl } },
        { type: "image_url", image_url: { url: sceneImageUrl } },
        { type: "text", text: prompt },
      ],
    },
  ];
  
  // 调用 Volcano Vision API
  const result = await volcanoProvider.chat(modelId).doGenerate({
    messages,
    imageParams: {
      aspectRatio: aspectRatio || "auto",
      imageSize: imageSize || "2K",
      imageCount: 1,
    },
  });
  
  // 解析返回的 Markdown 格式图片
  const { thumbnail, original } = parseImageFromMarkdown(result.text);
  
  return { thumbnail, original, prompt };
}

/**
 * 从 Markdown 格式解析图片 URL
 * 格式: ![thumb|||originalUrl|||size](thumbnailUrl)
 */
function parseImageFromMarkdown(markdown: string): { thumbnail: string; original: string } {
  console.log(`[SceneFusion] Parsing markdown: ${markdown.substring(0, 200)}...`);
  
  // 匹配 ![thumb|||originalUrl|||size](thumbnailUrl) 格式
  const match = markdown.match(/!\[thumb\|\|\|([^|]+)\|\|\|[^\]]*\]\(([^)]+)\)/);
  if (match) {
    return {
      original: match[1],
      thumbnail: match[2],
    };
  }
  
  // 尝试匹配普通图片格式 ![alt](url)
  const simpleMatch = markdown.match(/!\[[^\]]*\]\(([^)]+)\)/);
  if (simpleMatch) {
    return {
      original: simpleMatch[1],
      thumbnail: simpleMatch[1],
    };
  }
  
  throw new Error("无法从响应中解析图片 URL");
}

/**
 * 处理单个场景 (保留旧函数用于兼容)
 */
async function processScene(
  productImageUrl: string,
  sceneImageUrl: string,
  productName: string | undefined,
  targetName: string | undefined,
  customPrompt: string | undefined,
  defaultPrompt: string,
  baseURL: string,
  apiKey: string,
  modelId: string,
  size?: string
): Promise<{ thumbnail: string; original: string; prompt: string }> {
  // 构建智能提示词
  const prompt = buildPrompt(defaultPrompt, productName, targetName, customPrompt);
  
  console.log(`[SceneFusion] Built prompt: ${prompt}`);
  
  // 调用阿里生图 API
  const generatedImageUrl = await callAlibabaImageAPI(
    baseURL,
    apiKey,
    modelId,
    productImageUrl,
    sceneImageUrl,
    prompt,
    size
  );
  
  // 下载并上传到 S3
  const uploaded = await downloadAndUploadToS3(generatedImageUrl, "scene-fusion");
  
  return { ...uploaded, prompt };
}

export async function POST(request: Request) {
  try {
    // 1. 认证
    const session = await auth();
    if (!session?.user?.id) {
      return NextResponse.json(
        { error: "未登录" },
        { status: 401 }
      );
    }
    
    // 2. 获取场景裂变配置
    const config = await getSceneFusionConfig();
    
    if (!config.enabled) {
      return NextResponse.json(
        { error: "场景裂变功能已被管理员禁用" },
        { status: 403 }
      );
    }
    
    // 3. 解析请求体
    const json = await request.json();
    const parseResult = sceneFusionRequestSchema.safeParse(json);
    
    if (!parseResult.success) {
      return NextResponse.json(
        { error: parseResult.error.errors[0].message },
        { status: 400 }
      );
    }
    
    const { productImage, productName, aspectRatio, imageSize, scenes } = parseResult.data;
    
    // 计算输出尺寸
    const size = calculateSize(aspectRatio || "auto", imageSize || "2K");
    console.log(`[SceneFusion] Output settings: aspectRatio=${aspectRatio || 'auto'}, imageSize=${imageSize || '2K'}, calculated size=${size || 'auto'}`);
    
    // 检查场景数量限制
    if (scenes.length > config.maxScenes) {
      return NextResponse.json(
        { error: `最多只能添加 ${config.maxScenes} 个场景` },
        { status: 400 }
      );
    }
    
    console.log(`[SceneFusion] Processing ${scenes.length} scenes for user ${session.user.id}`);
    console.log(`[SceneFusion] Product name: ${productName || '(not specified)'}`);
    console.log(`[SceneFusion] Using default prompt: ${config.defaultPrompt.substring(0, 50)}...`);
    console.log(`[SceneFusion] Configured model ID: ${config.modelId || '(auto - default alibaba)'}`);
    
    // 4. 获取生图模型配置
    const allModels = await getEnabledAiModelsWithProvider();
    
    let selectedModel: typeof allModels[0] | undefined;
    
    // 如果配置了指定的模型ID，优先使用
    if (config.modelId) {
      selectedModel = allModels.find(
        (m) => m.model.id === config.modelId && m.model.isEnabled
      );
      if (!selectedModel) {
        console.warn(`[SceneFusion] Configured model ${config.modelId} not found or disabled, falling back to default`);
      }
    }
    
    // 如果没有配置或配置的模型不可用，使用默认的阿里生图模型
    if (!selectedModel) {
      // 按优先级查找：alibaba-image > ruxa-image > gemini > volcano-vision
      const imageProviderTypes = ["alibaba-image", "ruxa-image", "gemini", "volcano-vision"];
      for (const providerType of imageProviderTypes) {
        selectedModel = allModels.find(
          (m) => m.provider.type === providerType && m.model.isEnabled
        );
        if (selectedModel) break;
      }
    }
    
    if (!selectedModel) {
      return NextResponse.json(
        { error: "未配置可用的生图模型，请联系管理员" },
        { status: 500 }
      );
    }
    
    const { provider, model } = selectedModel;
    console.log(`[SceneFusion] Using model: ${model.displayName} (${model.modelId}) - Provider: ${provider.type}`);
    
    // 4. 预处理：将 Base64 图片上传到 S3
    let productImageUrl = productImage;
    if (productImage.startsWith("data:")) {
      productImageUrl = await uploadBase64ToS3(productImage, "scene-fusion-product");
    }
    
    const processedScenes = await Promise.all(
      scenes.map(async (scene) => {
        let sceneImageUrl = scene.image;
        if (scene.image.startsWith("data:")) {
          sceneImageUrl = await uploadBase64ToS3(scene.image, "scene-fusion-scene");
        }
        return {
          ...scene,
          imageUrl: sceneImageUrl,
        };
      })
    );
    
    // 6. 串行处理所有场景，每次间隔5秒
    const results = [];
    
    // 6. 创建流式响应，每完成一张图就立即发送给前端
    const stream = new ReadableStream({
      async start(controller) {
        const encoder = new TextEncoder();
        
        try {
          // 发送初始消息
          controller.enqueue(encoder.encode(JSON.stringify({ type: "start", total: processedScenes.length }) + "\n"));
          
          let successCount = 0;
          let failCount = 0;
          
          for (let i = 0; i < processedScenes.length; i++) {
            const scene = processedScenes[i];
            
            console.log(`[SceneFusion] ========== Processing scene ${i + 1}/${processedScenes.length} ==========`);
            console.log(`[SceneFusion] Scene ID: ${scene.id}`);
            console.log(`[SceneFusion] Product Image URL: ${productImageUrl.substring(0, 80)}...`);
            console.log(`[SceneFusion] Scene Image URL: ${scene.imageUrl.substring(0, 80)}...`);
            console.log(`[SceneFusion] Target Name: ${scene.targetName || '(not specified)'}`);
            console.log(`[SceneFusion] Custom Prompt: ${scene.customPrompt || '(none)'}`);
            console.log(`[SceneFusion] Provider Type: ${provider.type}`);
            
            // 如果不是第一张图，等待5秒
            if (i > 0) {
              console.log(`[SceneFusion] Waiting 5 seconds before processing...`);
              await new Promise((resolve) => setTimeout(resolve, 5000));
            }
            
            try {
              // 使用新的通用处理函数，支持多种模型类型
              const result = await processSceneWithProvider(
                productImageUrl,
                scene.imageUrl,
                productName,
                scene.targetName,
                scene.customPrompt,
                config.defaultPrompt,
                { type: provider.type, baseUrl: provider.baseUrl, apiKey: provider.apiKey },
                model.modelId,
                aspectRatio,
                imageSize
              );
              
              // 将分辨率等级用于数据库存储
              const dbImageSize = imageSize || "2K";
              
              // 保存到数据库（chatId 和 messageId 设为 null，因为场景裂变不关联聊天）
              try {
                await db.insert(generatedImage).values({
                  userId: session.user.id,
                  chatId: null, // 场景裂变不关联聊天
                  messageId: null, // 场景裂变不关联消息
                  thumbnailUrl: result.thumbnail,
                  originalUrl: result.original,
                  imageSize: dbImageSize,
                  prompt: `[场景裂变] ${result.prompt}`,
                  modelId: model.modelId,
                });
                console.log(`[SceneFusion] ✅ Saved image to gallery: ${result.original.substring(0, 80)}...`);
              } catch (dbError) {
                console.error("[SceneFusion] ❌ Failed to save to gallery:", dbError);
              }
              
              successCount++;
              
              // 立即发送完成的结果给前端
              controller.enqueue(encoder.encode(JSON.stringify({
                type: "result",
                data: {
                  id: scene.id,
                  status: "completed" as const,
                  result: result.thumbnail, // 返回缩略图用于预览
                  originalUrl: result.original, // 原图用于下载
                },
              }) + "\n"));
              
            } catch (error) {
              console.error(`[SceneFusion] Failed to process scene ${scene.id}:`, error);
              failCount++;
              
              // 立即发送失败的结果给前端
              controller.enqueue(encoder.encode(JSON.stringify({
                type: "result",
                data: {
                  id: scene.id,
                  status: "failed" as const,
                  error: error instanceof Error ? error.message : "处理失败",
                },
              }) + "\n"));
            }
          }
          
          // 发送完成消息
          console.log(`[SceneFusion] Completed: ${successCount} success, ${failCount} failed`);
          controller.enqueue(encoder.encode(JSON.stringify({
            type: "done",
            summary: {
              total: processedScenes.length,
              success: successCount,
              failed: failCount,
            },
          }) + "\n"));
          
        } catch (error) {
          console.error("[SceneFusion] Stream error:", error);
          // 发送错误消息
          controller.enqueue(encoder.encode(JSON.stringify({
            type: "error",
            error: error instanceof Error ? error.message : "处理失败",
          }) + "\n"));
        } finally {
          controller.close();
        }
      },
    });
    
    return new Response(stream, {
      headers: {
        "Content-Type": "text/event-stream",
        "Cache-Control": "no-cache",
        "Connection": "keep-alive",
      },
    });
  } catch (error) {
    console.error("[SceneFusion] Unexpected error:", error);
    return NextResponse.json(
      { error: error instanceof Error ? error.message : "处理失败" },
      { status: 500 }
    );
  }
}