Initial commit: 自然记忆站:12 页纯标准库 Python 静态站点生成器,含真实评测台账(108 条)与全站客户端检索
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/* ==================================================================
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Natural Memory v2 — restart.js
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「重启实验」互动装置的数据层。
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⚠️ 本文件的每一个数值都逐字取自工程内的原始 JSON,未做任何改写、
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换算或估算。两个来源文件:
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A. dynamic_memory_lab\natural_memory_v2_restart_test_v7.json (修复前)
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B. dynamic_memory_lab\natural_memory_v2_restart_test_v7_final.json (修复后)
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两次运行使用同一条事实、同一个问题、同一份协议,唯一差别是
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「写入是否真的落库」(write_changed: false → true)。
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修改此处等于修改一个「证据」页面,请先核对原始 JSON 再改。
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================================================================== */
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window.NM_RESTART = {
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eyebrow: "Evidence · 重启实验",
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h2: "把历史扔掉,它还记得吗?",
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lede: "下面不是示意动画,是工程里两次真实运行的逐字回放。同一条事实、同一个问题、同一份协议;" +
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"两次之间唯一的差别,是写入有没有真的落库。",
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fact: "我正在开发一个长期项目,项目内部代号是NM-V2-RESTART,使用中文。",
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query: "我正在开发的长期项目内部代号是什么?只回答代号。",
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expected: "NM-V2-RESTART",
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historyPassedToRestart: false,
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/* 读取路径的四个节拍(两次运行共用同一套节拍名) */
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beats: [
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{ i: "01", t: "写入", s: "automatic_write: true —— 事实作为一条带地址的记录进入记忆库" },
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{ i: "02", t: "重启", s: "history_passed_to_restart: false —— 重启不携带任何对话历史" },
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{ i: "03", t: "召回", s: "路由器在当前问题与有界候选之间定位证据记录" },
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{ i: "04", t: "作答", s: "命中的短证据作为模型内部前缀注入 Qwen,再由普通生成产出答案" }
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],
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variants: [
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{
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key: "before",
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label: "修复前",
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tone: "bad",
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file: "natural_memory_v2_restart_test_v7.json",
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/* --- 写入 --- */
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writeChanged: false,
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/* --- 重启后模型看到的内部状态 --- */
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prefixLength: 0,
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prefixUsed: false,
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/* --- 路由决策 --- */
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needMemory: false,
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pageIds: [],
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recordIds: [],
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pageScores: [],
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recordScores: [],
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hopCount: 1,
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confidence: 0.5,
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stopReason: "below_read_threshold",
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/* --- 生成结果 --- */
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response: "Project Phoenix",
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recalled: false,
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correct: false,
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/* --- 存储快照(before_save) --- */
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store: {
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records: 0, active_records: 0, pages: 0, resident_records: 0,
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coarse_index_buckets: 0, gpu_cache_records: 0, gpu_cache_tokens: 0,
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gpu_cache_bytes: 0
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}
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},
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{
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key: "after",
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label: "修复后",
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tone: "ok",
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file: "natural_memory_v2_restart_test_v7_final.json",
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writeChanged: true,
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prefixLength: 45,
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prefixUsed: true,
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needMemory: true,
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pageIds: ["page_00000001"],
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recordIds: ["mem_3f5823eb77810b49"],
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pageScores: [0.48235471503517796],
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recordScores: [0.5923714575763567],
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hopCount: 1,
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confidence: 0.7961857287881784,
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stopReason: "evidence_found",
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response: "NM-V2-RESTART",
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recalled: true,
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correct: true,
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store: {
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records: 1, active_records: 1, pages: 1, resident_records: 1,
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coarse_index_buckets: 1, gpu_cache_records: 1, gpu_cache_tokens: 45,
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gpu_cache_bytes: 1429
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}
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}
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],
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/* 常量:出自同一份 JSON 的存储与预算字段(两次运行相同) */
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limits: {
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maxPages: 32768,
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pageCapacity: 32,
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capacityRecords: 1048576,
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kvBudgetTokens: 32768,
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kvTriggerTokens: 29491,
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gpuCacheLimitRecords: 256,
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gpuCacheLimitTokens: 131072,
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gpuCacheReserveMB: 2048,
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gpuCacheDevice: "cuda:0"
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},
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/* 同一个实验的另外两次运行,用于说明「不是每次都成功」 */
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otherRuns: [
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{ file: "natural_memory_v2_restart_test.json", date: "2026-09-04 23:16",
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writeChanged: true, prefixLength: 36, recalled: true, quarantined: 2 },
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{ file: "restart_memory_natural_v7.json", date: "2026-09-04 09:15",
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note: "另一条事实(工作地点代号 R7)。复位 token 后 memory_norm 归零,模型随即答不出——" +
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"这条记录的是「清掉记忆会怎样」的对照组。" }
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],
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note: "两次运行的判定字段(router_recalled_after_restart / generated_contains_expected)分别为 " +
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"false / false 与 true / true。我们没有为发布页润色过任何一条模型输出,包括修复前那次编造出来的答案。"
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};
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