refactor: statusbar、companion、herdr 外掛改名加上 jsc- 前綴
Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
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co-authored by
Claude Sonnet 5.5
Claude Sonnet 5.5
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58e2b2d26a
@@ -0,0 +1,201 @@
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import type { Clock, Fs } from './io'
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import { readJson, writeJson } from './io'
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export type Layer = 'episodic' | 'semantic' | 'emotional' | 'procedural' | 'reflection'
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export interface Pad {
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p: number
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a: number
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d: number
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}
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export interface Memory {
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id: number
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layer: Layer
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text: string
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/** 重要度 1–10 */
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importance: number
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source: string
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createdAt: number
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lastAccess: number
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accessCount: number
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emotion?: Pad
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}
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export interface MemoryDoc {
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items: Memory[]
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nextId: number
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/** 自上次鞏固以來累積的重要度 */
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pending: number
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lastConsolidated: number
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/** 已被反思涵蓋的最大記憶編號 */
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reflectedUpTo?: number
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}
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export const HALF_LIFE_H = 72
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export const TOP_K = 6
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export const WEIGHTS = { recency: 1, importance: 1, relevance: 2, emotion: 0.5 }
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/** 累積重要度達此值就鞏固 */
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export const CONSOLIDATE_THRESHOLD = 30
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/** 保留率低於此值即遺忘 */
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export const FORGET_BELOW = 0.1
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/** 穩定度基準（小時） */
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const BASE_STABILITY_H = 24
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const HOUR = 3600_000
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/** 穩定度（小時）隨重要度與取用次數成長 */
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export const stability = (m: Pick<Memory, 'importance' | 'accessCount'>) =>
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BASE_STABILITY_H * m.importance * (1 + Math.log1p(m.accessCount))
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/** 保留率：自最近一次取用起算 */
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export function retention(m: Memory, now: number): number {
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const h = Math.max(0, now - m.lastAccess) / HOUR
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return Math.exp(-h / stability(m))
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}
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const tokens = (s: string) => {
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const out = new Set<string>()
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const latin = s.toLowerCase().match(/[a-z0-9]+/g) ?? []
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for (const w of latin) out.add(w)
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const cjk = s.replace(/[^一-鿿]/g, '')
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for (let i = 0; i < cjk.length; i++) {
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out.add(cjk[i]!)
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if (i + 1 < cjk.length) out.add(cjk.slice(i, i + 2))
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}
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return out
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}
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function relevance(query: string, text: string): number {
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const q = tokens(query)
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if (!q.size) return 0
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const t = tokens(text)
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let hit = 0
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for (const w of q) if (t.has(w)) hit++
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return hit / q.size
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}
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function moodFit(a?: Pad, b?: Pad): number {
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if (!a || !b) return 0
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const dist = Math.hypot(a.p - b.p, a.a - b.a, a.d - b.d) / Math.hypot(2, 2, 2)
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return 1 - dist
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}
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export function score(m: Memory, query: string, now: number, mood?: Pad): number {
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const recency = Math.pow(0.5, Math.max(0, now - m.lastAccess) / HOUR / HALF_LIFE_H)
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return (
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WEIGHTS.recency * recency +
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WEIGHTS.importance * (m.importance / 10) +
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WEIGHTS.relevance * relevance(query, m.text) +
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WEIGHTS.emotion * moodFit(m.emotion, mood)
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)
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}
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/** 疑似金鑰的字串在寫入前遮蔽 */
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export function redact(s: string): string {
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return s
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.replace(/\b(sk|pk|ghp|gho|xox[bap]|AKIA)[-_A-Za-z0-9]{12,}/g, '[已過濾]')
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.replace(/\b[A-Za-z0-9+/_-]{32,}\b/g, '[已過濾]')
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}
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export type Summarize = (items: Memory[]) => string
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/** 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 */
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const defaultSummarize: Summarize = items =>
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items
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.slice(0, 5)
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.map(i => i.text)
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.join('；')
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export interface MemoryStore {
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add(input: { layer: Layer; text: string; importance: number; source: string; emotion?: Pad }): Promise<Memory>
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/** 檢索前 6 筆，並更新取用紀錄 */
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recall(query: string, mood?: Pad): Promise<Memory[]>
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/** 累積達門檻、會話結束或手動 reflect 時鞏固 */
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consolidate(opts?: { force?: boolean; summarize?: Summarize }): Promise<{ ran: boolean; forgotten: number; reflection?: Memory }>
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all(): Promise<Memory[]>
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pending(): Promise<number>
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}
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export function createMemory(fs: Fs, clock: Clock, path: string): MemoryStore {
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const load = () => readJson<MemoryDoc>(fs, path, { items: [], nextId: 1, pending: 0, lastConsolidated: 0 })
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const save = (d: MemoryDoc) => writeJson(fs, path, d)
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return {
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async add(i) {
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const d = await load()
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const now = clock()
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const m: Memory = {
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id: d.nextId++,
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layer: i.layer,
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text: redact(i.text),
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importance: Math.min(10, Math.max(1, i.importance)),
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source: i.source,
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createdAt: now,
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lastAccess: now,
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accessCount: 0,
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emotion: i.emotion,
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}
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d.items.push(m)
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d.pending += m.importance
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await save(d)
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return m
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},
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async recall(query, mood) {
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const d = await load()
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const now = clock()
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const top = d.items
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.map(m => ({ m, s: score(m, query, now, mood) }))
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.sort((a, b) => b.s - a.s || b.m.id - a.m.id)
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.slice(0, TOP_K)
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.map(x => x.m)
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for (const m of top) {
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m.lastAccess = now
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m.accessCount++
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}
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if (top.length) await save(d)
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return top
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},
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async consolidate(opts = {}) {
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const d = await load()
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const now = clock()
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if (!opts.force && d.pending < CONSOLIDATE_THRESHOLD) return { ran: false, forgotten: 0 }
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// 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
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const fresh = d.items.filter(m => m.layer !== 'reflection' && m.id > (d.reflectedUpTo ?? 0))
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let reflection: Memory | undefined
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if (fresh.length) {
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const top = [...fresh].sort((a, b) => b.importance - a.importance || b.id - a.id)
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reflection = {
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id: d.nextId++,
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layer: 'reflection',
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text: redact((opts.summarize ?? defaultSummarize)(top)),
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importance: Math.min(10, Math.max(...top.map(t => t.importance)) + 1),
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source: `reflect:${top.map(t => t.id).join(',')}`,
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createdAt: now,
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lastAccess: now,
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accessCount: 0,
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}
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d.items.push(reflection)
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}
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d.reflectedUpTo = d.nextId - 1
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// 遺忘：保留率過低的記憶淘汰（反思本身不在本輪淘汰）
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const before = d.items.length
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d.items = d.items.filter(m => m === reflection || retention(m, now) >= FORGET_BELOW)
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d.pending = 0
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d.lastConsolidated = now
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await save(d)
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return { ran: true, forgotten: before - d.items.length, reflection }
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},
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async all() {
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return (await load()).items
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},
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async pending() {
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return (await load()).pending
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},
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}
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}
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