services/routes/ai.js

const Router = require('koa-router');
const fetch = require('node-fetch');
const { query } = require('../config/database');
const { toRelativeUrl } = require('../utils/image-url');
const { requireStaffAuth } = require('../middleware/auth');
const { sanitizeKeyword, sanitizeImageUrl, sanitizeImageBase64, makeCacheKey, LRU, TokenBucket } = require('../utils/ai-utils');
require('dotenv').config();

const router = new Router();

const AI_API_KEY = process.env.DASHSCOPE_API_KEY;
const AI_API_URL = 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions';
if (!AI_API_KEY) {
  console.error('DASHSCOPE_API_KEY is not set - AI features will fail')
}

const cache = new LRU(200, 5 * 60 * 1000)
const bucket = new TokenBucket(20, 1)

async function callQwen(model, body, timeoutMs) {
  const response = await fetch(AI_API_URL, {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${AI_API_KEY}`,
      'Content-Type': 'application/json'
    },
    body: JSON.stringify(body),
    timeout: timeoutMs || 30000
  })
  if (!response.ok) {
    const err = new Error(`AI 服务调用失败: ${response.status}`)
    err.status = response.status
    err.body = await response.text()
    throw err
  }
  return response.json()
}

function mapAIError(err) {
  if (err.status === 401) return { code: 500, message: 'API Key 无效，请检查密钥配置' }
  if (err.status === 403) return { code: 500, message: 'API 调用被拒绝，请检查账户权限' }
  if (err.status === 429) return { code: 500, message: 'API 调用次数超限，请稍后重试' }
  if (err.status === 503) return { code: 500, message: 'AI 服务暂时不可用，请稍后重试' }
  if (err.message && err.message.includes('timeout')) return { code: 503, message: 'AI 服务响应超时，请稍后重试' }
  if (err.message && err.message.includes('ENOTFOUND')) return { code: 503, message: '无法连接到 AI 服务，请检查网络' }
  if (err.message && err.message.includes('ECONNRESET')) return { code: 503, message: 'AI 服务连接中断，请稍后重试' }
  return { code: 503, message: 'AI 服务异常，请稍后重试' }
}

function tryParseJSON(text) {
  if (!text) return null
  const md = text.match(/```(?:json)?\s*([\s\S]*?)```/)
  const jsonStr = md ? md[1].trim() : (text.match(/\{[\s\S]*\}/)?.[0] || text)
  try { return JSON.parse(jsonStr) } catch { return null }
}

router.post('/generate-product', requireStaffAuth(), async (ctx) => {
  if (!AI_API_KEY) {
    ctx.status = 500
    ctx.body = { code: 500, message: 'AI 功能未配置（缺少 DASHSCOPE_API_KEY）' }
    return
  }
  if (!bucket.take()) {
    ctx.status = 429
    ctx.body = { code: 429, message: 'AI 调用过于频繁，请稍后重试' }
    return
  }

  const { imageUrl, keywords } = ctx.request.body || {}

  const kw = sanitizeKeyword(keywords)
  if (kw.error) { ctx.status = 400; ctx.body = { code: 400, message: kw.error }; return }
  const url = sanitizeImageUrl(imageUrl)
  if (url.error) { ctx.status = 400; ctx.body = { code: 400, message: url.error }; return }
  if (!kw.value && !url.value) { ctx.status = 400; ctx.body = { code: 400, message: '请提供图片或关键词' }; return }

  const cacheKey = makeCacheKey('gen', { kw: kw.value, url: url.value })
  const hit = cache.get(cacheKey)
  if (hit) {
    ctx.body = { code: 200, message: '生成成功', data: hit, cached: true }
    return
  }

  let prompt = '你是一个专业的便利店商品管理助手。'
  if (url.value) prompt += `\n请分析这张商品图片：${url.value}`
  if (kw.value) prompt += `\n关键词：${kw.value}`
  prompt += `
请生成商品的详细信息，返回JSON格式，不要包含其他内容：
{
  "name": "商品名称（简洁明了，2-10字）",
  "category": "商品分类（请从以下选择：饮料,零食,日用品,食品,生鲜,烟酒,其他）",
  "description": "商品详细描述（50-100字，突出产品特点）",
  "suggestedPrice": 建议售价（数字）
}`

  try {
    const data = await callQwen('qwen3.5-flash', {
      model: 'qwen3.5-flash',
      messages: [{ role: 'user', content: prompt }],
      temperature: 0.7,
      max_tokens: 500
    }, 30000)
    const aiResponse = data.choices?.[0]?.message?.content
    if (!aiResponse) { ctx.status = 500; ctx.body = { code: 500, message: 'AI 服务返回为空' }; return }
    const productInfo = tryParseJSON(aiResponse)
    if (!productInfo) { ctx.status = 500; ctx.body = { code: 500, message: '无法解析 AI 响应格式' }; return }
    cache.set(cacheKey, productInfo)
    ctx.body = { code: 200, message: '生成成功', data: productInfo }
  } catch (error) {
    const mapped = mapAIError(error)
    ctx.status = mapped.code
    ctx.body = mapped
  }
});

router.post('/recognize-product', requireStaffAuth(), async (ctx) => {
  if (!AI_API_KEY) {
    ctx.status = 500
    ctx.body = { code: 500, message: 'AI 功能未配置（缺少 DASHSCOPE_API_KEY）' }
    return
  }
  if (!bucket.take()) {
    ctx.status = 429
    ctx.body = { code: 429, message: 'AI 调用过于频繁，请稍后重试' }
    return
  }

  const { imageBase64, imageUrl } = ctx.request.body || {}

  let inputImageUrl = ''
  if (imageBase64) {
    const b = sanitizeImageBase64(imageBase64)
    if (b.error) { ctx.status = 400; ctx.body = { code: 400, message: b.error }; return }
    inputImageUrl = `data:image/jpeg;base64,${b.value}`
  }
  if (!inputImageUrl && imageUrl) {
    const u = sanitizeImageUrl(imageUrl)
    if (u.error) { ctx.status = 400; ctx.body = { code: 400, message: u.error }; return }
    inputImageUrl = u.value
  }
  if (!inputImageUrl) { ctx.status = 400; ctx.body = { code: 400, message: '请提供商品图片' }; return }

  const cacheKey = makeCacheKey('recog', { img: inputImageUrl.slice(0, 4096) })
  const hit = cache.get(cacheKey)
  if (hit) {
    ctx.body = { code: 200, message: '识别成功', data: hit, cached: true }
    return
  }

  const prompt = `你是一个专业的便利店商品识别助手。请分析这张商品图片，识别出商品信息。
请返回JSON格式的商品信息，只返回一个最可能的商品：
{
  "name": "商品名称（根据图片识别，如果无法确定则返回空字符串）",
  "category": "商品分类（从以下选择：饮料,零食,日用品,食品,生鲜,烟酒,其他，如果无法确定则返回空字符串）",
  "description": "商品描述（根据图片识别，突出产品特点，如果无法确定则返回空字符串）",
  "suggestedPrice": 数字（根据市场价估算，如果无法确定则返回0）,
  "confidence": 0到1之间的数字（识别置信度）
}`;

  try {
    const data = await callQwen('qwen3.5-omni', {
      model: 'qwen3.5-omni',
      messages: [{
        role: 'user',
        content: [
          { type: 'image_url', image_url: { url: inputImageUrl } },
          { type: 'text', text: prompt }
        ]
      }],
      temperature: 0.3,
      max_tokens: 500
    }, 60000)

    const aiResponse = data.choices?.[0]?.message?.content
    if (!aiResponse) { ctx.status = 500; ctx.body = { code: 500, message: 'AI 服务返回为空' }; return }
    const productInfo = tryParseJSON(aiResponse)
    if (!productInfo) { ctx.status = 500; ctx.body = { code: 500, message: '无法解析 AI 响应格式' }; return }

    const keyword = (productInfo.name || '').slice(0, 50)
    let matchedGoods = []
    if (keyword) {
      const dbResult = await query(
        'SELECT id, name, price, unit, category_id, images, stock, pricing_type, is_hot, is_new, description FROM goods WHERE name LIKE ? LIMIT 20',
        [`%${keyword}%`]
      )
      matchedGoods = dbResult
    }

    const { processGoodsImages } = require('../utils/image-url')
    matchedGoods = processGoodsImages(matchedGoods)

    const result = { aiInfo: productInfo, matchedGoods }
    cache.set(cacheKey, result)
    ctx.body = { code: 200, message: '识别成功', data: result }
  } catch (error) {
    const mapped = mapAIError(error)
    ctx.status = mapped.code
    ctx.body = mapped
  }
});

module.exports = router.routes();