微软小冰的颜值鉴定接口

rockswang

把我的老铁机器人的颜值鉴定接口源码放出来,逻辑都在execute函数里面,看不懂也不解释了。

const sharp = require('sharp')
const _ = require('lodash')

const { sendMsg, Recent, localPic } = require('../qq_api')
const { rp, UA, auraCdChk, num } = require('../utils')

module.exports = {
  name: '颜值',
  tags: ['exec', 'aura', 'group', 'cd'],
  keywords: ['好看吗'],
  usage: ['(发照片后) [botNick_]颜值鉴定', '我好看吗?', '@某用户 好看吗'],
  value: { 冷却时间: { def: '20秒', chk: auraCdChk } },
  help: '给照片中人物的颜值打分。AT某用户可鉴定他/她的头像,发送“我好看吗”则鉴定自己的头像。\n☍ 数据接口:微软小冰 https://ux.xiaoice.com/beautyv3',
  execute: async ({ name, bot, user, msg: { content: cont, ats = [], pics: [pic] = [] }, g }) => {
    cont = cont.replace(/(鉴定|的|\?|?)/, '')
    if (cont === '我' || ats.length) {
      const q = cont === '我' ? user : ats[0]
      pic = { url: `http://q1.qlogo.cn/g?b=qq&nk=${q}&s=640` }
    } else if (!pic) {
      pic = await Recent.get('pic', user, g)
      if (!pic) { // 需要补发照片
        Recent.set('cmd', user, g, name)
        return sendMsg(bot, g, user, '[at]颜值鉴定需要你提供包含人脸的照片,请在20秒内发出'), 'WAITING_PIC' // eslint-disable-line
      }
      Recent.del('pic', user, g)
    }
    ;(async () => { // 异步执行,避免指令执行时间过长
      try {
        const opts = {
          jar: rp.jar(),
          headers: { 'User-Agent': UA }
        }
        let [res, buf] = await Promise.all([
          rp.head('https://ux.xiaoice.com/beautyv3', opts), // 小冰颜值首页,访问此页面仅用于填充cookies,HEAD比GET速度更快
          rp.get(pic.url, { encoding: null })]) // 获取图像数据
        // 从cookies中提取TraceId参数
        const TraceId = JSON.parse(decodeURIComponent(opts.jar.getCookies('http://ux.xiaoice.com').find(c => c.key === 'logInfo').value)).tid
        // 对非动画gif,大于200K或大于30万像素的,则缩小至30万像素以节省流量
        const img = sharp(buf)
        const { format, width, height } = await img.metadata()
        if (format !== 'gif' && ((buf.length > 200000) || width * height > 300000)) {
          const nw = ~~Math.sqrt(width * 300000 / height)
          if (nw < width) buf = await img.resize(nw).jpeg({ quality: 75, chromaSubsampling: '4:2:0' }).toBuffer()
        }
        // base64方式上传图片
        _.merge(opts, {
          headers: { 'Content-Type': 'application/x-www-form-urlencoded', Referer: 'https://ux.xiaoice.com/beautyv3' },
          body: buf.toString('base64')
        })
        res = await rp.post('https://ux.xiaoice.com/api/image/UploadBase64?exp=1', opts)
        res = JSON.parse(res) // 应答体JSON格式,包含上传后的图片host和uri
        const MsgId = Date.now()
        // 调用颜值鉴定接口,一般需要10秒以上,需设定较长的超时时间
        _.merge(opts, {
          json: true,
          timeout: 45000,
          headers: { 'Content-Type': 'application/json' },
          body: { MsgId, CreateTime: ~~(MsgId / 1000), TraceId, Content: { imageUrl: res.Host + res.Url } }
        })
        res = await rp.post('https://ux.xiaoice.com/api/imageAnalyze/Process?service=beauty', opts)
        // 成功获取到鉴定结果
        const { imageUrl, metadata, text } = res.content
        let txt = text
        if (metadata.score) {
          txt = `👆上面${{ male: '帅哥', female: '美女' }[metadata.gender]}的颜值有${metadata.score}分!👏`
          if (metadata.FBR_Cnt) {
            const fbr = Object.entries(metadata).reduce((o, [k, v]) => {
              const mch = /^FBR_(Key|Score)(\d+)$/.exec(k)
              if (mch) (o[+mch[2]] = o[+mch[2]] || {})[mch[1]] = v
              return o
            }, [])
            txt += `\n评分详情:\n${num(fbr.map(f => `${f.Key}:${f.Score}分`)).join('\n')}`
          }
          txt += `\n⭐${text}`
          if (metadata.Comment_Improve) txt += `\n💡${metadata.Comment_Improve}`
        }
        const lpic = await localPic(imageUrl)
        sendMsg(bot, g, user, txt, lpic)
      } catch (e) {
        sendMsg(bot, g, user, `[at]颜值鉴定失败,错误:${e.message}`)
      }
    })()
    return sendMsg(bot, g, user, `[at]正在鉴定颜值,大约需要20~30秒,请稍候`), 'OK' // eslint-disable-line
  }
}
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