src/composables/useLeaderboardData.js

import { ref, computed, reactive } from 'vue'
import { parseCsvContent, processModelNames } from '@/utils/csvUtils.js'

// 全局状态对象，用于在多个组件间共享
const globalState = reactive({
  leaderboard: [],
  csvHeaders: [],
  loading: true,
  error: null,
  // 排序状态：当前排序列（key）与方向（true = 降序）
  sortKey: '',
  sortDesc: true,
  visibleColumns: [],
  dataGroups: [],
  selectedDataName: '',
  selectedDataNameChart: '',
  modelTypeGroups: [],
  selectedModelType: [], // 改为数组支持多选
  DEFAULT_CSV_PATH: '/filtered.csv',
  // 默认隐藏的列
  DEFAULT_HIDDEN: new Set(['seq_len', 'uniform_entropy', 'entropy_gain', 'information_capacity', 'data_name', 'model_size (B)'])
})

// 模型类型映射对象：键为模型类型，值为包含的 model_series 数组
const modelTypeMapping = {
  'Qwen3': ['Qwen3'],
  'Qwen2.5': ['Qwen2.5'],
  'Qwen2': ['Qwen2'],
  'Qwen1.5': ['Qwen1.5'],
  'Llama-3': ['Llama-3.1', 'Llama-3.2'],
  'InternLM2.5': ['Internlm2.5'],
  'GLM-4': ['GLM-4', 'GLM-4'],
  'Seed-OSS': ['Seed-OSS'],
  'Gemma-3': ['Gemma-3'],
  'Hunyuan': ['Hunyuan'],
  'Qwen2 (MoE)': ['Qwen2 (MoE)'],
  'Qwen1.5 (MoE)': ['Qwen1.5 (MoE)'],
  'DeepSeek-V3.1': ['DeepSeek-V3.1-Base'],
  'DeepSeek-V2': ['DeepSeek-V2'],
  'GLM-4.5': ['GLM-4.5-Air-Base', 'GLM-4.5-Base'],
  'Llama-4': ['Llama-4']
}

const MoEModelSeries = ['Qwen2', 'Qwen1.5']

const strtSymbolSeries = ['Qwen2 (MoE)', 'Qwen1.5 (MoE)', 'DeepSeek-V3.1', 'DeepSeek-V2', 'GLM-4.5', "Llama-4"]

// const autoShowSeries = ['Qwen3', 'Llama-3', 'InternLM2.5', 'GLM-4', 'Seed-OSS', 'Gemma-3', 'Hunyuan', 'DeepSeek-V3.1', 'DeepSeek-V2', 'GLM-4.5']
const autoShowSeries = ["*"]

// 表头显示名称映射（raw header -> 显示名），可以在此添加或由用户修改
const headerDisplayMap = reactive({
  'rank': 'Rank',
  'model_name': 'Model Name',
  'model_series': 'Model Series',
  'model_size (B)': 'Model Size (B)',
  'constant': 'Text Size',
  'conditional_entropy': 'Negative Log-Likelihood',
  'BF16_TFLOPs': 'FLOPs (G)',
  'ic': ' Information Capacity',
  'model_source': 'Tested by'
})

// 数据集名称显示映射（raw data_name -> 显示名）
const dataNameDisplayMap = reactive({
  'data_part_0000': 'Mixed text',
  'eng_Latn_000_00027_long': 'FinePDFs-en',
  'IndustryCorpus_batch_aa_long': 'Ch-FineWeb-Edu',
  'CC-MAIN-2013-20_train-00000-of-00014_long': 'FineWeb-Edu',
  'NextCoderDataset_v1_long': 'NextCoder',
})


// 默认选择模式为Model
const selectedMode = ref('Model')

// 可选择的列（包含 rank，如果需要）
const selectableColumns = computed(() => {
  if (!globalState.csvHeaders || globalState.csvHeaders.length === 0) return []
  return globalState.csvHeaders.filter(h => !globalState.DEFAULT_HIDDEN.has(h))
})

// 模型类型分组（从映射对象中获取）
const modelTypeGroups = computed(() => {
  return Object.keys(modelTypeMapping)
})

// 对 leaderboard 做基于 sortKey/sortDesc 的排序视图（不改变原始 globalState.leaderboard）
const sortedLeaderboard = computed(() => {
  if (!globalState.leaderboard || globalState.leaderboard.length === 0) return []
  const key = globalState.sortKey
  const desc = !!globalState.sortDesc
  const arr = [...globalState.leaderboard]
  if (!key || key === '') return arr
  arr.sort((a, b) => {
    const va = a[key]
    const vb = b[key]
    // null/undefined push to end
    if (va == null && vb == null) return 0
    if (va == null) return 1
    if (vb == null) return -1
    const na = Number(va)
    const nb = Number(vb)
    if (Number.isFinite(na) && Number.isFinite(nb)) {
      return desc ? (nb - na) : (na - nb)
    }
    try {
      return desc ? String(vb).localeCompare(String(va)) : String(va).localeCompare(String(vb))
    } catch (e) {
      return 0
    }
  })
  return arr
})

// 根据 selectedDataName 和 selectedModelType 过滤 leaderboard，用于表格渲染
const filteredLeaderboard = computed(() => {
  if (!globalState.leaderboard || globalState.leaderboard.length === 0) return []
  // 从已排序的视图开始过滤
  let filtered = sortedLeaderboard.value

  // 过滤数据集
  if (globalState.selectedDataName && globalState.selectedDataName !== 'all') {
    filtered = filtered.filter(r => String(r['data_name'] ?? '') === String(globalState.selectedDataName))
  }

  // 过滤模型类型（支持多选）
  // 特殊值 '__none__' 表示用户明确选择了“清除”——此时应返回空结果
  const sel = globalState.selectedModelType
  if (Array.isArray(sel)) {
    if (sel.includes('__none__')) return []
    if (sel.length > 0) {
      filtered = filtered.filter(r => sel.includes(String(r['model_type'] ?? '')))
    }
  }
  // 重新分配 rank 基于当前过滤和排序后的顺序
  return filtered.map((item, index) => ({ ...item, rank: index + 1 }))
})

// 计算每个 model_series 的 IC 平均值，返回数组，元素格式为 { ModelSeries, IC }
const modelSeriesICAvg = computed(() => {
  const rows = globalState.leaderboard || []
  const selData = globalState.selectedDataName
  const selModelTypes = globalState.selectedModelType

  // 以 modelTypeMapping 的 key 为行（即用户划分好的 ModelSeries）来生成平均值
  const out = []
  const keys = Object.keys(modelTypeMapping)

  // 如果用户显式清空选择，直接返回空数组
  if (Array.isArray(selModelTypes) && selModelTypes.includes('__none__')) return []

  for (const key of keys) {
    // 当有选中的 model types 时，只处理被选中的那些 key
    if (Array.isArray(selModelTypes) && selModelTypes.length > 0) {
      // 如果 selectedModelType 包含元素，但不包含当前 key，则跳过
      if (!selModelTypes.includes(key)) continue
    }

    const mappedSeries = new Set(modelTypeMapping[key] || [])
    // 也把 key 自身加入集合（保险）
    mappedSeries.add(key)

    // 聚合该 key 下所有匹配 series 的 IC
    let sum = 0
    let count = 0
    let constant = 0
    let modelSource = ''
    for (const r of rows) {
      // Dataset 过滤
      if (selData && selData !== 'all') {
        if (String(r['data_name'] ?? '') !== String(selData)) continue
      }
      const seriesName = String(r['model_series'] ?? '').trim()
      if (!seriesName) continue
      if (!mappedSeries.has(seriesName)) continue
      const icRaw = r['ic']
      const n = Number(icRaw)
      if (!Number.isFinite(n)) continue
      constant = Number(r['constant']) || 0
      sum += n
      count += 1
      modelSource = r['model_source']
    }
    if (count === 0) continue
    const avg = sum / count
    out.push({ ModelSeries: key, IC: Number(avg.toFixed(4)), Constant: constant ,ModelSource: modelSource })
  }

  // 根据 sortKey 和 sortDesc 进行排序
  const key = globalState.sortKey
  const desc = !!globalState.sortDesc
  if (key && key !== '') {
    out.sort((a, b) => {
      let va, vb
      if (key === 'ic') {
        va = a.IC
        vb = b.IC
      } else if (key === 'constant') {
        va = a.Constant
        vb = b.Constant
      } else {
        va = a[key]
        vb = b[key]
      }
      // null/undefined push to end
      if (va == null && vb == null) return 0
      if (va == null) return 1
      if (vb == null) return -1
      const na = Number(va)
      const nb = Number(vb)
      if (Number.isFinite(na) && Number.isFinite(nb)) {
        return desc ? (nb - na) : (na - nb)
      }
      try {
        return desc ? String(vb).localeCompare(String(va)) : String(va).localeCompare(String(vb))
      } catch (e) {
        return 0
      }
    })
  } else {
    // 默认按 IC 降序排序
    out.sort((a, b) => b.IC - a.IC)
  }
  return out
})

// 点击表头切换排序：循环 降序 -> 升序
function setSortKey(h) {
  if (!h) return
  if (globalState.sortKey !== h) {
    globalState.sortKey = h
    globalState.sortDesc = true
    return
  }
  // same key, toggle between desc and asc
  globalState.sortDesc = !globalState.sortDesc
}

// 计算当前应该显示的列（不含 rank）
const displayedColumns = computed(() => {
  if (!globalState.csvHeaders || globalState.csvHeaders.length === 0) return []
  // csvHeaders includes 'rank' at idx 0
  console.log('csvHeaders:', globalState.csvHeaders)
  const all = globalState.csvHeaders
  return all.filter(h => globalState.visibleColumns.includes(h))
})


// init
async function fetchAndLoadCsv(path = globalState.DEFAULT_CSV_PATH) {
  globalState.loading = true
  globalState.error = null

  try {
    const res = await fetch(path)
    if (!res.ok) throw new Error(`Failed to fetch CSV (${res.status})`)
    const txt = await res.text()
    const { headers, rows } = parseCsvContent(txt)
    processModelNames(rows)
    if (!headers || headers.length === 0) { globalState.leaderboard = []; globalState.loading = false; return }

    // 选择用于排序/显示的分数字段（优先 information_capacity, ic, 然后尝试 numeric-like fields）
    const scoreKey = headers.find(h => ['information_capacity', 'ic', 'score'].includes(h)) || headers.find(h => /capacity|score|ic/i.test(h)) || headers[0]
    // 默认以最后一列升序排序（如果不存在则回退到 scoreKey），不直接在 rows 上预排序
    const defaultKey = headers.length > 0 ? headers[headers.length - 1] : scoreKey
    globalState.sortKey = defaultKey || ''
    globalState.sortDesc = true


    // 预处理步骤：
    for (const r of rows) {
      // 预处理步骤：
      //   1. 筛选ModelSeries 我们现有的已经指定了一些模型的系列，但是这些系列并不一定完全包含我们的数据，所以，将系列之外的模型新增到key-value映射中，key和value都对应的是model_series名称

      const seriesName = String(r['model_series'] ?? '').trim()
      // console.log('Processing series name:', seriesName, Object.values(modelTypeMapping).flat().includes(seriesName))
      if (!Object.values(modelTypeMapping).flat().includes(seriesName)) {
        modelTypeMapping[seriesName] = [seriesName]
      }

      // 2. 模型来源处理，如果Model Name后缀为[[xxxx]]，则将来源为xxxx否则为TeleAI，这个来源是新的属性
      const name = r['model_name'] || ''
      const sourceMatch = name.match(/\[\[(.+?)\]\]$/)
      if (sourceMatch) {
        r['model_source'] = sourceMatch[1]
        // 去掉 model_name 末尾的 [[xxxx]]
        r['model_name'] = name.replace(/\[\[(.+?)\]\]$/, '').trim()
      } else {
        r['model_source'] = 'TeleAI'
      }

      // 3. 判断模型开头是否在 MoEModelSeries 中，是则在 判断尾部是否为-A{number}B这样的格式
      for (const moePrefix of MoEModelSeries) {
        if (name.startsWith(moePrefix)) {
          // console.log('Checking MoE model name:', name,name.match(/-A(\d+(?:\.\d+)?)B/))
          const moeSuffixMatch = name.match(/-A(.+)B$/)
          if (moeSuffixMatch) {
            // 更改 model_series 显示名称 为 moePrefix + ' (MoE)'
            r['model_series'] = `${moePrefix} (MoE)`
            // console.log('Detected MoE model, updated series:', r['model_series'])
          }
        }
      }

      // 4. 根据 model_series 推断 model_type
      let modelType = ''

      for (const [type, series] of Object.entries(modelTypeMapping)) {
        if (series.includes(r['model_series'])) {
          modelType = type
          break
        }
      }
      r['model_type'] = modelType

      // 5. 修改model_series为model_type的值
      r['model_series'] = modelType

    }

    // 确保关键列按顺序显示
    const preferred = ['model_name', 'model_series', 'model_size (B)', 'seq_len', 'uniform_entropy', 'constant', 'conditional_entropy', 'entropy_gain', 'BF16_TFLOPs', 'information_capacity', 'ic','model_source']
    const ordered = []
    for (const p of preferred) if (headers.includes(p) && !ordered.includes(p)) ordered.push(p)
    for (const h of headers) if (!ordered.includes(h)) ordered.push(h)
    globalState.csvHeaders = ['rank', ...ordered, 'model_source']

    globalState.leaderboard = rows.map((r, idx) => {
      
      const modelType = r['model_type']
      
      // 修改 BF16_TFLOPs：先 /1024 再 *1000
      const originalTFLOPs = Number(r['BF16_TFLOPs']) || 0
      const modifiedTFLOPs = (originalTFLOPs / 1024) * 1000
      return { rank: idx + 1, model_type: modelType, ...r, BF16_TFLOPs: modifiedTFLOPs }
    })

    // console.log('Loaded leaderboard with', globalState.leaderboard.length, 'rows.', globalState.leaderboard )

    // 构建 data_name 分组（保持出现顺序，不包含空）
    const seen = new Set()
    const groups = []
    for (const r of rows) {
      const dn = r['data_name']
      if (dn == null) continue
      const s = String(dn)
      if (s.trim() === '') continue
      if (!seen.has(s)) { seen.add(s); groups.push(s) }
    }
    globalState.dataGroups = groups

    // 构建 model_type 分组
    globalState.modelTypeGroups = Object.keys(modelTypeMapping)

    // 默认显示第一个数据集
    if (globalState.dataGroups.length > 0) {
      globalState.selectedDataName = globalState.dataGroups[0]
      globalState.selectedDataNameChart = globalState.dataGroups[0]
    }

    // 默认模型类型：默认全选（使筛选 UI 初始为所有模型被勾选）
    if (globalState.modelTypeGroups.length > 0) {
      globalState.selectedModelType = [...globalState.modelTypeGroups]
    }

    // 初始化可见列：默认显示所有可选列（不包含默认隐藏列），包括 rank
    globalState.visibleColumns = ['rank', ...ordered.filter(h => !globalState.DEFAULT_HIDDEN.has(h)), 'model_source']

    // 数字格式化
    const numericFloatCols = new Set(['uniform_entropy', 'conditional_entropy', 'entropy_gain', 'information_capacity', 'ic', 'constant', 'BF16_TFLOPs'])
    const numericIntCols = new Set(['seq_len'])
    // attach formatter per row for rendering convenience (non-reactive simple values)
    for (const row of globalState.leaderboard) {
      row._formatted = {}
      for (const h of ordered) {
        const raw = row[h]
        if (raw == null || raw === '') { row._formatted[h] = ''; continue }
        if (numericIntCols.has(h)) {
          const n = Number(raw)
          row._formatted[h] = Number.isFinite(n) ? String(Math.round(n)) : raw
        } else if (numericFloatCols.has(h)) {
          const n = Number(raw)
          if (h === 'ic') {
            row._formatted[h] = Number.isFinite(n) ? n.toFixed(4) : raw
          }
          else if (h === 'constant') {
            row._formatted[h] = Number.isFinite(n) ? n.toFixed(2) : raw
          }
          else {
            row._formatted[h] = Number.isFinite(n) ? n.toFixed(3) : raw
          }
        } else {
          row._formatted[h] = raw
        }
      }
    }
  } catch (e) {
    console.error(e)
    globalState.error = e && e.message ? e.message : String(e)
  } finally {
    globalState.loading = false
  }
}

function selectAll() {
  // 复制一份可选列到 visibleColumns
  globalState.visibleColumns = [...selectableColumns.value]
}

function clearAll() {
  globalState.visibleColumns = []
}

function selectAllModelTypes() {
  globalState.selectedModelType = [...modelTypeGroups.value]
}

function clearAllModelTypes() {
  // 使用特殊标记表示用户显式地清空选择（区别于未选择任何项）
  globalState.selectedModelType = ['__none__']
}

function formatCell(h, model) {
  if (!model) return ''
  if (model._formatted && model._formatted[h] !== undefined) return model._formatted[h]
  return model[h]
}

// 初始化函数，在组件挂载时调用
function init() {
  fetchAndLoadCsv()
}

export function useLeaderboardData() {
  return {
    // 状态
    leaderboard: computed(() => globalState.leaderboard),
    csvHeaders: computed(() => globalState.csvHeaders),
    loading: computed(() => globalState.loading),
    error: computed(() => globalState.error),
    visibleColumns: computed({
      get: () => globalState.visibleColumns,
      set: (v) => globalState.visibleColumns = v
    }),
    selectedMode: computed({
      get: () => selectedMode.value,
      set: (v) => selectedMode.value = v
    }),
    selectableColumns,
    autoShowSeries,
    strtSymbolSeries,
    headerDisplayMap: computed(() => headerDisplayMap),
    dataNameDisplayMap: computed(() => dataNameDisplayMap),
    dataGroups: computed(() => globalState.dataGroups),
    selectedDataName: computed({
      get: () => globalState.selectedDataName,
      set: (v) => globalState.selectedDataName = v
    }),
    selectedDataNameChart: computed({
      get: () => globalState.selectedDataNameChart,
      set: (v) => globalState.selectedDataNameChart = v
    }),
    modelTypeGroups: computed(() => globalState.modelTypeGroups),
    selectedModelType: computed({
      get: () => globalState.selectedModelType,
      set: (v) => {
        // 当用户通过 UI 勾选真实模型类型时，移除 '__none__' 标记
        if (Array.isArray(v) && v.some(x => x !== '__none__')) {
          globalState.selectedModelType = v.filter(x => x !== '__none__')
        } else {
          globalState.selectedModelType = v
        }
      }
    }),
    filteredLeaderboard,
    displayedColumns,
    modelSeriesICAvg,
    // 函数
    fetchAndLoadCsv,
    selectAll,
    clearAll,
    selectAllModelTypes,
    clearAllModelTypes,
    // 排序相关
    sortKey: computed(() => globalState.sortKey),
    sortDesc: computed(() => globalState.sortDesc),
    setSortKey,
    formatCell,
    init
  }
}