import type { Clock, Fs } from './io'
import { readJson, writeJson } from './io'
import { MEMORY as R } from './rules'

export type Layer = 'episodic' | 'semantic' | 'emotional' | 'procedural' | 'reflection'

/** 暫時：場景結束或 7 天衰減；可升級：30 天降權、90 天未檢索封存；長期與鎖定：不衰減 */
export type Kind = 'temp' | 'upgradable' | 'long' | 'locked'
export type Status = 'active' | 'archived'

export interface Pad {
  p: number
  a: number
  d: number
}

export interface Memory {
  id: number
  layer: Layer
  kind: Kind
  status: Status
  text: string
  /** 初始重要度 1–10（I_eff 以一半換算到 1–5 量表） */
  importance: number
  source: string
  createdAt: number
  lastAccess: number
  accessCount: number
  /** 建立當下的回合序號，新鮮度以回合數衰減 */
  seq: number
  /** 最近一次被檢索的回合序號 */
  hitSeq?: number
  emotion?: Pad
  /** 編碼時的情緒峰值 0–100 */
  peak?: number
  /** 類別加成（忌妒、重逢），由 categoryBonus 算出 */
  bonus?: number
  /** 原典記憶：新鮮度固定為 1 */
  canon?: boolean
  /** 負向事件；未解時每日加權（反覆思量） */
  negative?: boolean
  resolvedAt?: number
  /** 危險內容：只留安全摘要，不升級 */
  danger?: boolean
  archivedAt?: number
}

export interface Loop {
  id: number
  text: string
  askedSeq: number
  askedAt: number
  status: 'open' | 'answered' | 'timeout'
}

export interface MemoryDoc {
  items: Memory[]
  nextId: number
  /** 自上次鞏固以來累積的重要度 */
  pending: number
  lastConsolidated: number
  /** 已被反思涵蓋的最大記憶編號 */
  reflectedUpTo?: number
  /** 回合序號：每次檢索（每個使用者回合）加一 */
  seq?: number
  loops?: Loop[]
}

export const TOP_K = 6
/** 累積重要度達此值就鞏固 */
export const CONSOLIDATE_THRESHOLD = 30
const HOUR = 3600_000
const DAY = 24 * HOUR

const clamp = (x: number, lo: number, hi: number) => Math.min(hi, Math.max(lo, x))

/** 有效重要度 I_eff：初始重要度 + 情緒峰值 / 40 + 類別加成，限制在 1–5 */
export const iEff = (m: Pick<Memory, 'importance' | 'peak' | 'bonus'>) =>
  clamp(m.importance / 2 + (m.peak ?? 0) / R.peakDiv + (m.bonus ?? 0), R.weightMin, R.weightMax)

const decay = (dSeq: number) => Math.pow(0.5, Math.max(0, dSeq) / R.halfSeq)

/** 新鮮度 F：原典固定 1；其餘 0.5^(Δseq/200)，被檢索到時至少回到 0.8 後再繼續衰減 */
export function freshness(m: Pick<Memory, 'seq' | 'hitSeq' | 'canon'>, seq: number): number {
  if (m.canon) return 1
  const raw = decay(seq - m.seq)
  return m.hitSeq === undefined ? raw : Math.max(raw, R.floor * decay(seq - m.hitSeq))
}

/** 存取加成 A：命中越多越高，有上限 */
export const access = (m: Pick<Memory, 'accessCount'>) => 1 + R.accessStep * Math.min(m.accessCount, R.accessCap)

/** 反覆思量：未解的負向事件每日 +20%，上限 3 倍 */
export function rumination(m: Pick<Memory, 'negative' | 'resolvedAt' | 'createdAt'>, now: number): number {
  if (!m.negative || m.resolvedAt !== undefined) return 1
  return Math.min(R.ruminateCap, 1 + R.ruminatePerDay * (Math.max(0, now - m.createdAt) / DAY))
}

/** 可升級記憶滿 30 天仍未升級就降權 */
const demotion = (m: Pick<Memory, 'kind' | 'createdAt'>, now: number) =>
  m.kind === 'upgradable' && now - m.createdAt >= R.demoteDays * DAY ? R.demoteFactor : 1

/** 記憶權重 W = I_eff × F × A（再乘反覆思量與降權） */
export const weight = (m: Memory, seq: number, now: number) =>
  iEff(m) * freshness(m, seq) * access(m) * rumination(m, now) * demotion(m, now)

/** 此刻是否該封存：暫時記憶滿 7 天；可升級記憶 90 天未檢索。長期與鎖定記憶永不 */
export function shouldArchive(m: Memory, now: number): boolean {
  if (m.status === 'archived') return false
  if (m.kind === 'temp') return now - m.createdAt >= R.tempDays * DAY
  if (m.kind === 'upgradable') return now - m.lastAccess >= R.archiveDays * DAY
  return false
}

/** 類別加成：忌妒敏感度或想念累積速度 ≥ 0.65 的角色，對應事件 +1 */
export function categoryBonus(kind: 'jealous' | 'reunion', params?: { jealous?: number; miss?: number }): number {
  const v = kind === 'jealous' ? params?.jealous : params?.miss
  return v !== undefined && v / 100 >= R.bonusThreshold ? 1 : 0
}

const DANGER = /自殺|自傷|自殘|割腕|輕生|想死|結束生命|殺人|縱火|製毒|suicide|self[- ]?harm/i
export const isDanger = (text: string) => DANGER.test(text)
const SAFE_SUMMARY = '（安全事件摘要）對話中出現危險內容，已不保留原文'

const tokens = (s: string) => {
  const out = new Set<string>()
  const latin = s.toLowerCase().match(/[a-z0-9]+/g) ?? []
  for (const w of latin) out.add(w)
  const cjk = s.replace(/[^一-鿿]/g, '')
  for (let i = 0; i < cjk.length; i++) {
    out.add(cjk[i]!)
    if (i + 1 < cjk.length) out.add(cjk.slice(i, i + 2))
  }
  return out
}

function relevance(query: string, text: string): number {
  const q = tokens(query)
  if (!q.size) return 0
  const t = tokens(text)
  let hit = 0
  for (const w of q) if (t.has(w)) hit++
  return hit / q.size
}

function moodFit(a?: Pad, b?: Pad): number {
  if (!a || !b) return 0
  const dist = Math.hypot(a.p - b.p, a.a - b.a, a.d - b.d) / Math.hypot(2, 2, 2)
  return 1 - dist
}

/** RRF 融合：fused(id) = Σ 1 / (k + rank)，rank 從 1 起算；每份排名由好到壞的記憶編號 */
export function rrf(rankings: number[][]): Map<number, number> {
  const out = new Map<number, number>()
  for (const list of rankings) list.forEach((id, i) => out.set(id, (out.get(id) ?? 0) + 1 / (R.rrfK + i + 1)))
  return out
}

/** 外部檢索器（例如語意相似度）：回傳由好到壞的記憶編號；目前沒有內建，介面保留 */
export type Retriever = (query: string, items: Memory[]) => number[]

export interface RecallOpts {
  /** 釋懷速度 0–1，決定心情一致加權的大小；預設 0.5 */
  recover?: number
  extra?: Retriever[]
}

/** 疑似金鑰的字串在寫入前遮蔽 */
export function redact(s: string): string {
  return s
    .replace(/\b(sk|pk|ghp|gho|xox[bap]|AKIA)[-_A-Za-z0-9]{12,}/g, '[已過濾]')
    .replace(/\b[A-Za-z0-9+/_-]{32,}\b/g, '[已過濾]')
}

export type Summarize = (items: Memory[]) => string

/** 預設摘要：不呼叫模型，直接串接重點；實際反思文字可由外部注入模型版 */
const defaultSummarize: Summarize = items =>
  items
    .slice(0, 5)
    .map(i => i.text)
    .join('；')

export interface AddInput {
  layer: Layer
  text: string
  importance: number
  source: string
  emotion?: Pad
  kind?: Kind
  peak?: number
  bonus?: number
  canon?: boolean
  negative?: boolean
}

export interface MemoryStore {
  add(input: AddInput): Promise<Memory>
  /** 前 6 筆：關鍵字（可併入外部檢索器）經 RRF 融合 × W + 心情一致加權；回合序號加一並更新取用紀錄 */
  recall(query: string, mood?: Pad, opts?: RecallOpts): Promise<Memory[]>
  /** 累積達門檻、會話結束或手動 reflect 時鞏固；過期的記憶封存而不刪除 */
  consolidate(opts?: { force?: boolean; summarize?: Summarize }): Promise<{ ran: boolean; archived: number; reflection?: Memory }>
  /** 場景結束：暫時記憶封存 */
  endScene(): Promise<number>
  /** 未解負向事件標為已解（apology、soothe 或情緒消退時）；不給編號就是全部 */
  resolve(ids?: number[]): Promise<number>
  /** 她提了一個問題，開始計算開放迴路 */
  openLoop(text: string): Promise<Loop>
  /** 使用者這句話回應了哪些開放迴路 */
  respond(text: string): Promise<number>
  loops(): Promise<Loop[]>
  /** 每回合必帶：近 7 天權重最高的 3 筆、未解的負向事件、未收尾的對話 */
  core(): Promise<{ recent: Memory[]; unresolved: Memory[]; loops: Loop[] }>
  /** 全部記憶（含已封存），任何記憶都不刪除 */
  all(): Promise<Memory[]>
  pending(): Promise<number>
}

/** 回覆中最後一個問句；沒有就回 null */
export function lastQuestion(reply: string): string | null {
  const qs = reply.match(/[^。！？!?\n]*[？?]/g)
  const q = qs?.[qs.length - 1]?.trim()
  return q ? q.slice(0, 120) : null
}

export function createMemory(fs: Fs, clock: Clock, path: string): MemoryStore {
  const normalize = (d: MemoryDoc): MemoryDoc => {
    d.seq ??= 0
    d.loops ??= []
    for (const m of d.items) {
      m.kind ??= m.layer === 'episodic' && m.importance < 5 ? 'temp' : 'upgradable'
      m.status ??= 'active'
      m.seq ??= d.seq
    }
    return d
  }
  const load = async () => normalize(await readJson<MemoryDoc>(fs, path, { items: [], nextId: 1, pending: 0, lastConsolidated: 0 }))
  const save = (d: MemoryDoc) => writeJson(fs, path, d)

  // 升級與封存：回傳變動筆數
  function lifecycle(d: MemoryDoc, now: number): number {
    let n = 0
    for (const m of d.items) {
      if (m.status !== 'active') continue
      if (m.kind === 'upgradable' && !m.danger && m.accessCount >= R.upgradeHits) m.kind = 'long'
      else if (shouldArchive(m, now)) {
        m.status = 'archived'
        m.archivedAt = now
        n++
      }
    }
    return n
  }

  return {
    async add(i) {
      const d = await load()
      const now = clock()
      const danger = isDanger(i.text)
      const m: Memory = {
        id: d.nextId++,
        layer: i.layer,
        kind: danger ? 'temp' : (i.kind ?? (i.layer === 'episodic' && i.importance < 5 ? 'temp' : 'upgradable')),
        status: 'active',
        text: danger ? SAFE_SUMMARY : redact(i.text),
        importance: clamp(i.importance, 1, 10),
        source: i.source,
        createdAt: now,
        lastAccess: now,
        accessCount: 0,
        seq: d.seq!,
        emotion: danger ? undefined : i.emotion,
        peak: i.peak,
        bonus: i.bonus,
        canon: i.canon,
        negative: i.negative,
        danger: danger || undefined,
      }
      d.items.push(m)
      d.pending += m.importance
      await save(d)
      return m
    },

    async recall(query, mood, opts = {}) {
      const d = await load()
      const now = clock()
      d.seq!++
      lifecycle(d, now)
      for (const l of d.loops!) {
        if (l.status === 'open' && d.seq! - l.askedSeq >= R.loopTurns) l.status = 'timeout'
      }
      const active = d.items.filter(m => m.status === 'active')
      const w = new Map(active.map(m => [m.id, weight(m, d.seq!, now)]))
      const hits = active
        .map(m => ({ m, r: relevance(query, m.text) }))
        .filter(x => x.r > 0)
        .sort((a, b) => b.r - a.r || b.m.id - a.m.id)
        .map(x => x.m.id)
      // 查無關鍵字命中時退回依權重排序，讓核心記憶仍能帶出
      const base = hits.length || opts.extra?.length ? hits : [...active].sort((a, b) => w.get(b.id)! - w.get(a.id)! || b.id - a.id).map(m => m.id)
      const lists = [base, ...(opts.extra ?? []).map(f => f(query, active))]
      const fused = rrf(lists)
      const top1 = lists.length / (R.rrfK + 1)
      const wm = R.moodBase + R.moodSlope * (1 - (opts.recover ?? 0.5))
      const top = active
        .filter(m => fused.has(m.id))
        .map(m => ({ m, s: (fused.get(m.id)! / top1) * w.get(m.id)! + wm * moodFit(m.emotion, mood) }))
        .sort((a, b) => b.s - a.s || b.m.id - a.m.id)
        .slice(0, TOP_K)
        .map(x => x.m)
      for (const m of top) {
        m.lastAccess = now
        m.accessCount++
        m.hitSeq = d.seq
      }
      lifecycle(d, now)
      // 空的記憶檔不為了回合序號而建立
      if (d.items.length || d.loops!.length) await save(d)
      return top
    },

    async consolidate(opts = {}) {
      const d = await load()
      const now = clock()
      if (!opts.force && d.pending < CONSOLIDATE_THRESHOLD) return { ran: false, archived: 0 }

      // 反思：把上次鞏固後新增、尚未被反思涵蓋的記憶濃縮成一筆
      const fresh = d.items.filter(m => m.layer !== 'reflection' && m.id > (d.reflectedUpTo ?? 0) && !m.danger)
      let reflection: Memory | undefined
      if (fresh.length) {
        const top = [...fresh].sort((a, b) => b.importance - a.importance || b.id - a.id)
        reflection = {
          id: d.nextId++,
          layer: 'reflection',
          kind: 'upgradable',
          status: 'active',
          text: redact((opts.summarize ?? defaultSummarize)(top)),
          importance: Math.min(10, Math.max(...top.map(t => t.importance)) + 1),
          source: `reflect:${top.map(t => t.id).join(',')}`,
          createdAt: now,
          lastAccess: now,
          accessCount: 0,
          seq: d.seq!,
        }
        d.items.push(reflection)
      }

      d.reflectedUpTo = d.nextId - 1
      const archived = lifecycle(d, now)
      d.pending = 0
      d.lastConsolidated = now
      await save(d)
      return { ran: true, archived, reflection }
    },

    async endScene() {
      const d = await load()
      const now = clock()
      let n = 0
      for (const m of d.items) {
        if (m.status === 'active' && m.kind === 'temp') {
          m.status = 'archived'
          m.archivedAt = now
          n++
        }
      }
      if (n) await save(d)
      return n
    },

    async resolve(ids) {
      const d = await load()
      const now = clock()
      let n = 0
      for (const m of d.items) {
        if (m.negative && m.resolvedAt === undefined && (!ids || ids.includes(m.id))) {
          m.resolvedAt = now
          n++
        }
      }
      if (n) await save(d)
      return n
    },

    async openLoop(text) {
      const d = await load()
      const l: Loop = { id: (d.loops!.reduce((x, y) => Math.max(x, y.id), 0)) + 1, text: redact(text), askedSeq: d.seq!, askedAt: clock(), status: 'open' }
      d.loops!.push(l)
      await save(d)
      return l
    },

    async respond(text) {
      const d = await load()
      let n = 0
      for (const l of d.loops!) {
        if (l.status === 'open' && relevance(l.text, text) > 0) {
          l.status = 'answered'
          n++
        }
      }
      if (n) await save(d)
      return n
    },

    async loops() {
      return (await load()).loops!
    },

    async core() {
      const d = await load()
      const now = clock()
      const active = d.items.filter(m => m.status === 'active')
      const recent = active
        .filter(m => now - m.createdAt <= 7 * DAY)
        .sort((a, b) => weight(b, d.seq!, now) - weight(a, d.seq!, now) || b.id - a.id)
        .slice(0, 3)
      const unresolved = active.filter(m => m.negative && m.resolvedAt === undefined)
      return { recent, unresolved, loops: d.loops!.filter(l => l.status === 'open') }
    },

    async all() {
      return (await load()).items
    },
    async pending() {
      return (await load()).pending
    },
  }
}