董海洋
202 lines
7.9 KiB
JavaScript
202 lines
7.9 KiB
JavaScript
const Router = require('koa-router');
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const fetch = require('node-fetch');
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const { query } = require('../config/database');
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const { toRelativeUrl } = require('../utils/image-url');
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const { requireStaffAuth } = require('../middleware/auth');
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const { sanitizeKeyword, sanitizeImageUrl, sanitizeImageBase64, makeCacheKey, LRU, TokenBucket } = require('../utils/ai-utils');
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require('dotenv').config();
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const router = new Router();
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const AI_API_KEY = process.env.DASHSCOPE_API_KEY;
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const AI_API_URL = 'https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions';
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if (!AI_API_KEY) {
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console.error('DASHSCOPE_API_KEY is not set - AI features will fail')
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}
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const cache = new LRU(200, 5 * 60 * 1000)
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const bucket = new TokenBucket(20, 1)
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async function callQwen(model, body, timeoutMs) {
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const response = await fetch(AI_API_URL, {
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method: 'POST',
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headers: {
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'Authorization': `Bearer ${AI_API_KEY}`,
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'Content-Type': 'application/json'
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},
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body: JSON.stringify(body),
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timeout: timeoutMs || 30000
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})
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if (!response.ok) {
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const err = new Error(`AI 服务调用失败: ${response.status}`)
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err.status = response.status
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err.body = await response.text()
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throw err
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}
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return response.json()
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}
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function mapAIError(err) {
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if (err.status === 401) return { code: 500, message: 'API Key 无效，请检查密钥配置' }
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if (err.status === 403) return { code: 500, message: 'API 调用被拒绝，请检查账户权限' }
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if (err.status === 429) return { code: 500, message: 'API 调用次数超限，请稍后重试' }
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if (err.status === 503) return { code: 500, message: 'AI 服务暂时不可用，请稍后重试' }
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if (err.message && err.message.includes('timeout')) return { code: 503, message: 'AI 服务响应超时，请稍后重试' }
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if (err.message && err.message.includes('ENOTFOUND')) return { code: 503, message: '无法连接到 AI 服务，请检查网络' }
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if (err.message && err.message.includes('ECONNRESET')) return { code: 503, message: 'AI 服务连接中断，请稍后重试' }
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return { code: 503, message: 'AI 服务异常，请稍后重试' }
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}
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function tryParseJSON(text) {
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if (!text) return null
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const md = text.match(/```(?:json)?\s*([\s\S]*?)```/)
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const jsonStr = md ? md[1].trim() : (text.match(/\{[\s\S]*\}/)?.[0] || text)
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try { return JSON.parse(jsonStr) } catch { return null }
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}
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router.post('/generate-product', requireStaffAuth(), async (ctx) => {
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if (!AI_API_KEY) {
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ctx.status = 500
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ctx.body = { code: 500, message: 'AI 功能未配置（缺少 DASHSCOPE_API_KEY）' }
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return
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}
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if (!bucket.take()) {
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ctx.status = 429
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ctx.body = { code: 429, message: 'AI 调用过于频繁，请稍后重试' }
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return
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}
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const { imageUrl, keywords } = ctx.request.body || {}
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const kw = sanitizeKeyword(keywords)
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if (kw.error) { ctx.status = 400; ctx.body = { code: 400, message: kw.error }; return }
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const url = sanitizeImageUrl(imageUrl)
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if (url.error) { ctx.status = 400; ctx.body = { code: 400, message: url.error }; return }
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if (!kw.value && !url.value) { ctx.status = 400; ctx.body = { code: 400, message: '请提供图片或关键词' }; return }
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const cacheKey = makeCacheKey('gen', { kw: kw.value, url: url.value })
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const hit = cache.get(cacheKey)
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if (hit) {
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ctx.body = { code: 200, message: '生成成功', data: hit, cached: true }
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return
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}
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let prompt = '你是一个专业的便利店商品管理助手。'
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if (url.value) prompt += `\n请分析这张商品图片：${url.value}`
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if (kw.value) prompt += `\n关键词：${kw.value}`
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prompt += `
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请生成商品的详细信息，返回JSON格式，不要包含其他内容：
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{
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"name": "商品名称（简洁明了，2-10字）",
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"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）",
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"description": "商品详细描述（50-100字，突出产品特点）",
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"suggestedPrice": 建议售价（数字）
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}`
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try {
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const data = await callQwen('qwen3.5-flash', {
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model: 'qwen3.5-flash',
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messages: [{ role: 'user', content: prompt }],
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temperature: 0.7,
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max_tokens: 500
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}, 30000)
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const aiResponse = data.choices?.[0]?.message?.content
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if (!aiResponse) { ctx.status = 500; ctx.body = { code: 500, message: 'AI 服务返回为空' }; return }
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const productInfo = tryParseJSON(aiResponse)
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if (!productInfo) { ctx.status = 500; ctx.body = { code: 500, message: '无法解析 AI 响应格式' }; return }
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cache.set(cacheKey, productInfo)
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ctx.body = { code: 200, message: '生成成功', data: productInfo }
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} catch (error) {
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const mapped = mapAIError(error)
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ctx.status = mapped.code
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ctx.body = mapped
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}
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});
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router.post('/recognize-product', requireStaffAuth(), async (ctx) => {
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if (!AI_API_KEY) {
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ctx.status = 500
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ctx.body = { code: 500, message: 'AI 功能未配置（缺少 DASHSCOPE_API_KEY）' }
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return
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}
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if (!bucket.take()) {
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ctx.status = 429
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ctx.body = { code: 429, message: 'AI 调用过于频繁，请稍后重试' }
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return
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}
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const { imageBase64, imageUrl } = ctx.request.body || {}
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let inputImageUrl = ''
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if (imageBase64) {
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const b = sanitizeImageBase64(imageBase64)
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if (b.error) { ctx.status = 400; ctx.body = { code: 400, message: b.error }; return }
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inputImageUrl = `data:image/jpeg;base64,${b.value}`
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}
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if (!inputImageUrl && imageUrl) {
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const u = sanitizeImageUrl(imageUrl)
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if (u.error) { ctx.status = 400; ctx.body = { code: 400, message: u.error }; return }
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inputImageUrl = u.value
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}
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if (!inputImageUrl) { ctx.status = 400; ctx.body = { code: 400, message: '请提供商品图片' }; return }
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const cacheKey = makeCacheKey('recog', { img: inputImageUrl.slice(0, 4096) })
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const hit = cache.get(cacheKey)
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if (hit) {
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ctx.body = { code: 200, message: '识别成功', data: hit, cached: true }
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return
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}
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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。
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请返回JSON格式的商品信息，只返回一个最可能的商品：
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{
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"name": "商品名称（根据图片识别，如果无法确定则返回空字符串）",
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"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）",
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"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）",
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"suggestedPrice": 数字（根据市场价估算，如果无法确定则返回0）,
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"confidence": 0到1之间的数字（识别置信度）
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}`;
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try {
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const data = await callQwen('qwen3.5-omni', {
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model: 'qwen3.5-omni',
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messages: [{
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role: 'user',
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content: [
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{ type: 'image_url', image_url: { url: inputImageUrl } },
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{ type: 'text', text: prompt }
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]
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}],
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temperature: 0.3,
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max_tokens: 500
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}, 60000)
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const aiResponse = data.choices?.[0]?.message?.content
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if (!aiResponse) { ctx.status = 500; ctx.body = { code: 500, message: 'AI 服务返回为空' }; return }
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const productInfo = tryParseJSON(aiResponse)
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if (!productInfo) { ctx.status = 500; ctx.body = { code: 500, message: '无法解析 AI 响应格式' }; return }
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const keyword = (productInfo.name || '').slice(0, 50)
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let matchedGoods = []
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if (keyword) {
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const dbResult = await query(
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'SELECT id, name, price, unit, category_id, images, stock, pricing_type, is_hot, is_new, description FROM goods WHERE name LIKE ? LIMIT 20',
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[`%${keyword}%`]
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)
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matchedGoods = dbResult
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}
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const { processGoodsImages } = require('../utils/image-url')
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matchedGoods = processGoodsImages(matchedGoods)
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const result = { aiInfo: productInfo, matchedGoods }
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cache.set(cacheKey, result)
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ctx.body = { code: 200, message: '识别成功', data: result }
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} catch (error) {
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const mapped = mapAIError(error)
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ctx.status = mapped.code
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ctx.body = mapped
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}
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});
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module.exports = router.routes(); |