c/miniprogram/pages/recommend/index.js

const { request } = require('../../utils/request')

const REC_TYPES = [
  {
    key: 'current',
    label: '当前状态推荐',
    desc: '基于你最近一次饮食状态，用随机森林给出当前最匹配的食谱。',
    scene: '日常实时决策',
    requirement: '建议先填写今天的体重、体脂、摄入和消耗'
  },
  {
    key: 'health',
    label: '健康状态推荐',
    desc: '按体脂、摄入和运动平衡进行规则评分，优先推荐营养结构更均衡的方案。',
    scene: '想吃得更健康',
    requirement: '推荐先有基础饮食状态数据'
  },
  {
    key: 'history',
    label: '历史计划推荐',
    desc: '根据近一段时间的体重和摄入趋势，给出偏减脂或偏增肌的策略型推荐。',
    scene: '需要阶段性调整',
    requirement: '至少有 3 天历史记录'
  },
  {
    key: 'goal',
    label: '未来目标推荐',
    desc: '围绕你的目标（减脂/增肌/生酮/维持）进行宏量营养匹配。',
    scene: '目标导向饮食',
    requirement: '可跟随个人资料，也可手动指定目标'
  },
  {
    key: 'occupation',
    label: '职业行业推荐',
    desc: '根据职业活动强度和作息特点，推荐更贴近日常能量需求的食谱。',
    scene: '工作日场景优化',
    requirement: '可跟随个人资料，也可手动指定职业'
  }
]

const TOP_K_OPTIONS = [
  { value: 3, label: '3 条' },
  { value: 5, label: '5 条' },
  { value: 10, label: '10 条' }
]

const GOAL_OPTIONS = [
  { value: '', label: '跟随个人资料（推荐）' },
  { value: 'lose_fat', label: '减脂（lose_fat）' },
  { value: 'gain_muscle', label: '增肌（gain_muscle）' },
  { value: 'keto', label: '生酮（keto）' },
  { value: 'maintain', label: '维持（maintain）' }
]

const OCCUPATION_OPTIONS = [
  { value: '', label: '跟随个人资料（推荐）' },
  { value: 'office', label: '办公室（office）' },
  { value: 'developer', label: '程序员（developer）' },
  { value: 'fitness', label: '健身行业（fitness）' },
  { value: 'teacher', label: '教师（teacher）' },
  { value: 'student', label: '学生（student）' },
  { value: 'manual', label: '体力劳动（manual）' }
]

Page({
  data: {
    recType: 'current',
    recTypes: REC_TYPES,
    activeType: REC_TYPES[0],
    selectedLabel: REC_TYPES[0].label,
    topK: 5,
    topKLabel: '5 条',
    topKOptions: TOP_K_OPTIONS,
    goalValue: '',
    goalLabel: GOAL_OPTIONS[0].label,
    goalOptions: GOAL_OPTIONS,
    occupationValue: '',
    occupationLabel: OCCUPATION_OPTIONS[0].label,
    occupationOptions: OCCUPATION_OPTIONS,
    loading: false,
    payload: null,
    summary: null,
    errorText: '',
    lastUpdatedAt: ''
  },

  onShow() {
    this.fetchRecommend()
  },

  onTypeChange(e) {
    const idx = Number(e.detail.value)
    const item = this.data.recTypes[idx]
    if (!item) return
    this.setData({
      recType: item.key,
      selectedLabel: item.label,
      activeType: item
    })
    this.fetchRecommend()
  },

  onTopKChange(e) {
    const idx = Number(e.detail.value)
    const item = this.data.topKOptions[idx]
    if (!item) return
    this.setData({ topK: item.value, topKLabel: item.label })
    this.fetchRecommend()
  },

  onGoalChange(e) {
    const idx = Number(e.detail.value)
    const item = this.data.goalOptions[idx]
    if (!item) return
    this.setData({ goalValue: item.value, goalLabel: item.label })
    this.fetchRecommend()
  },

  onOccupationChange(e) {
    const idx = Number(e.detail.value)
    const item = this.data.occupationOptions[idx]
    if (!item) return
    this.setData({ occupationValue: item.value, occupationLabel: item.label })
    this.fetchRecommend()
  },

  buildUrl() {
    const topK = this.data.topK || 5
    const type = this.data.recType
    if (type === 'current') return `/recommend/current?top_k=${topK}`
    if (type === 'health') return `/recommend/health?top_k=${topK}`
    if (type === 'history') return `/recommend/plan/history?top_k=${topK}`
    if (type === 'goal') {
      const extra = this.data.goalValue ? `&goal=${encodeURIComponent(this.data.goalValue)}` : ''
      return `/recommend/plan/goal?top_k=${topK}${extra}`
    }
    const occ = this.data.occupationValue ? `&occupation=${encodeURIComponent(this.data.occupationValue)}` : ''
    return `/recommend/plan/occupation?top_k=${topK}${occ}`
  },

  buildSummary(items = []) {
    if (!items.length) return null
    const totalCalories = items.reduce((sum, row) => sum + Number(row.calories || 0), 0)
    const totalProtein = items.reduce((sum, row) => sum + Number(row.protein || 0), 0)
    return {
      count: items.length,
      avgCalories: Math.round((totalCalories / items.length) * 10) / 10,
      avgProtein: Math.round((totalProtein / items.length) * 10) / 10
    }
  },

  formatNow() {
    const d = new Date()
    const pad = (n) => String(n).padStart(2, '0')
    return `${pad(d.getHours())}:${pad(d.getMinutes())}:${pad(d.getSeconds())}`
  },

  async fetchRecommend() {
    this.setData({ loading: true, errorText: '' })
    try {
      const payload = await request({ url: this.buildUrl() })
      const items = payload && Array.isArray(payload.items) ? payload.items : []
      const normalizedItems = items.map((row, idx) => {
        const score = Number(row.rf_score ?? row.score ?? 0)
        return {
          ...row,
          rank: idx + 1,
          displayScore: score.toFixed(1)
        }
      })
      this.setData({
        payload: { ...payload, items: normalizedItems },
        summary: this.buildSummary(normalizedItems),
        lastUpdatedAt: this.formatNow(),
        errorText: ''
      })
    } catch (err) {
      this.setData({
        payload: null,
        summary: null,
        errorText: (err && err.message) || '推荐请求失败，请稍后重试'
      })
    } finally {
      this.setData({ loading: false })
    }
  }
})