1094 lines
43 KiB
JavaScript
1094 lines
43 KiB
JavaScript
// ═══════════════════════════════════════════════════════════════════════════
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// Story Summary - Prompt Injection (v5 - Two-Stage: L0 Locate → L1 Evidence)
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//
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// 命名规范：
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// - 存储层用 L0/L1/L2/L3（StateAtom/Chunk/Event/Fact）
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// - 装配层用语义名称：constraint/event/evidence/arc
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//
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// 架构变更（v4 → v5）：
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// - L0 和 L1 不再在同一个池子竞争
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// - recall.js 返回 {l0Selected[], l1ByFloor: Map} 而非 evidenceChunks[]
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// - 装配层按 L2→L0→L1 层级组织
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// - 预算以"L0 + USER top-1 + AI top-1"为原子单元
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// - 孤立 L1（无对应 L0）丢弃
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// - 孤立 L0（无对应 L1）保留
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//
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// 职责：
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// - 仅负责"构建注入文本"，不负责写入 extension_prompts
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// - 注入发生在 story-summary.js：GENERATION_STARTED 时写入 extension_prompts
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// ═══════════════════════════════════════════════════════════════════════════
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import { getContext } from "../../../../../../extensions.js";
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import { xbLog } from "../../../core/debug-core.js";
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import { getSummaryStore, getFacts, isRelationFact } from "../data/store.js";
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import { getVectorConfig, getSummaryPanelConfig, getSettings } from "../data/config.js";
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import { recallMemory } from "../vector/retrieval/recall.js";
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import { getMeta } from "../vector/storage/chunk-store.js";
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// Metrics
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import { formatMetricsLog, detectIssues } from "../vector/retrieval/metrics.js";
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const MODULE_ID = "summaryPrompt";
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// ─────────────────────────────────────────────────────────────────────────────
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// 召回失败提示节流
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// ─────────────────────────────────────────────────────────────────────────────
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let lastRecallFailAt = 0;
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const RECALL_FAIL_COOLDOWN_MS = 10_000;
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function canNotifyRecallFail() {
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const now = Date.now();
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if (now - lastRecallFailAt < RECALL_FAIL_COOLDOWN_MS) return false;
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lastRecallFailAt = now;
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return true;
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}
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// ─────────────────────────────────────────────────────────────────────────────
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// 预算常量
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// ─────────────────────────────────────────────────────────────────────────────
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const MAIN_BUDGET_MAX = 10000;
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const DISTANT_EVIDENCE_MAX = 2500;
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const RECENT_EVIDENCE_MAX = 5000;
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const TOTAL_BUDGET_MAX = 15000;
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const CONSTRAINT_MAX = 2000;
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const ARCS_MAX = 1500;
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const TOP_N_STAR = 5;
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// ─────────────────────────────────────────────────────────────────────────────
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// 工具函数
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// ─────────────────────────────────────────────────────────────────────────────
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/**
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* 估算文本 token 数量
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* @param {string} text - 输入文本
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* @returns {number} token 估算值
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*/
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function estimateTokens(text) {
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if (!text) return 0;
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const s = String(text);
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const zh = (s.match(/[\u4e00-\u9fff]/g) || []).length;
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return Math.ceil(zh + (s.length - zh) / 4);
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}
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/**
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* 带预算限制的行追加
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* @param {string[]} lines - 行数组
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* @param {string} text - 要追加的文本
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* @param {object} state - 预算状态 {used, max}
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* @returns {boolean} 是否追加成功
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*/
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function pushWithBudget(lines, text, state) {
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const t = estimateTokens(text);
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if (state.used + t > state.max) return false;
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lines.push(text);
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state.used += t;
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return true;
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}
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/**
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* 解析事件摘要中的楼层范围
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* @param {string} summary - 事件摘要
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* @returns {{start: number, end: number}|null} 楼层范围
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*/
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function parseFloorRange(summary) {
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if (!summary) return null;
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const match = String(summary).match(/\(#(\d+)(?:-(\d+))?\)/);
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if (!match) return null;
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const start = Math.max(0, parseInt(match[1], 10) - 1);
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const end = Math.max(0, (match[2] ? parseInt(match[2], 10) : parseInt(match[1], 10)) - 1);
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return { start, end };
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}
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/**
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* 清理事件摘要（移除楼层标记）
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* @param {string} summary - 事件摘要
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* @returns {string} 清理后的摘要
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*/
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function cleanSummary(summary) {
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return String(summary || "")
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.replace(/\s*\(#\d+(?:-\d+)?\)\s*$/, "")
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.trim();
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}
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/**
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* 标准化字符串
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* @param {string} s - 输入字符串
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* @returns {string} 标准化后的字符串
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*/
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function normalize(s) {
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return String(s || '')
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.normalize('NFKC')
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.replace(/[\u200B-\u200D\uFEFF]/g, '')
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.trim()
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.toLowerCase();
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}
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/**
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* 获取事件排序键
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* @param {object} event - 事件对象
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* @returns {number} 排序键
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*/
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function getEventSortKey(event) {
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const r = parseFloorRange(event?.summary);
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if (r) return r.start;
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const m = String(event?.id || "").match(/evt-(\d+)/);
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return m ? parseInt(m[1], 10) : Number.MAX_SAFE_INTEGER;
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}
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/**
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* 重新编号事件文本
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* @param {string} text - 原始文本
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* @param {number} newIndex - 新编号
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* @returns {string} 重新编号后的文本
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*/
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function renumberEventText(text, newIndex) {
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const s = String(text || "");
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return s.replace(/^(\s*)\d+(\.\s*(?:【)?)/, `$1${newIndex}$2`);
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}
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// ─────────────────────────────────────────────────────────────────────────────
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// 系统前导与后缀
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// ─────────────────────────────────────────────────────────────────────────────
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/**
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* 构建系统前导文本
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* @returns {string} 前导文本
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*/
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function buildSystemPreamble() {
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return [
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"以上是还留在眼前的对话",
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"以下是脑海里的记忆：",
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"• [定了的事] 这些是不会变的",
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"• 其余部分是过往经历的回忆碎片",
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"",
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"请内化这些记忆：",
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].join("\n");
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}
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/**
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* 构建后缀文本
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* @returns {string} 后缀文本
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*/
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function buildPostscript() {
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return [
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"",
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"这些记忆是真实的，请自然地记住它们。",
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].join("\n");
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}
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// ─────────────────────────────────────────────────────────────────────────────
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// [Constraints] L3 Facts 过滤与格式化
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// ─────────────────────────────────────────────────────────────────────────────
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/**
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* 获取已知角色集合
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* @param {object} store - 存储对象
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* @returns {Set<string>} 角色名称集合（标准化后）
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*/
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function getKnownCharacters(store) {
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const names = new Set();
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const arcs = store?.json?.arcs || [];
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for (const a of arcs) {
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if (a.name) names.add(normalize(a.name));
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}
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const main = store?.json?.characters?.main || [];
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for (const m of main) {
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const name = typeof m === 'string' ? m : m.name;
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if (name) names.add(normalize(name));
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}
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const { name1, name2 } = getContext();
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if (name1) names.add(normalize(name1));
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if (name2) names.add(normalize(name2));
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return names;
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}
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/**
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* 解析关系谓词中的目标
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* @param {string} predicate - 谓词
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* @returns {string|null} 目标名称
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*/
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function parseRelationTarget(predicate) {
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const match = String(predicate || '').match(/^对(.+)的/);
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return match ? match[1] : null;
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}
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/**
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* 按相关性过滤 facts
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* @param {object[]} facts - 所有 facts
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* @param {string[]} focusEntities - 焦点实体
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* @param {Set<string>} knownCharacters - 已知角色
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* @returns {object[]} 过滤后的 facts
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*/
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function filterConstraintsByRelevance(facts, focusEntities, knownCharacters) {
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if (!facts?.length) return [];
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const focusSet = new Set((focusEntities || []).map(normalize));
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return facts.filter(f => {
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if (f._isState === true) return true;
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if (isRelationFact(f)) {
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const from = normalize(f.s);
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const target = parseRelationTarget(f.p);
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const to = target ? normalize(target) : '';
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if (focusSet.has(from) || focusSet.has(to)) return true;
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return false;
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}
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const subjectNorm = normalize(f.s);
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if (knownCharacters.has(subjectNorm)) {
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return focusSet.has(subjectNorm);
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}
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return true;
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});
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}
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/**
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* 格式化 constraints 用于注入
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* @param {object[]} facts - 所有 facts
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* @param {string[]} focusEntities - 焦点实体
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* @param {Set<string>} knownCharacters - 已知角色
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* @returns {string[]} 格式化后的行
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*/
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function formatConstraintsForInjection(facts, focusEntities, knownCharacters) {
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const filtered = filterConstraintsByRelevance(facts, focusEntities, knownCharacters);
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if (!filtered.length) return [];
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return filtered
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.sort((a, b) => (b.since || 0) - (a.since || 0))
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.map(f => {
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const since = f.since ? ` (#${f.since + 1})` : '';
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if (isRelationFact(f) && f.trend) {
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return `- ${f.s} ${f.p}: ${f.o} [${f.trend}]${since}`;
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}
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return `- ${f.s}的${f.p}: ${f.o}${since}`;
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});
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}
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// ─────────────────────────────────────────────────────────────────────────────
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// 格式化函数
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// ─────────────────────────────────────────────────────────────────────────────
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/**
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* 格式化弧光行
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* @param {object} arc - 弧光对象
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* @returns {string} 格式化后的行
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*/
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function formatArcLine(arc) {
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const moments = (arc.moments || [])
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.map(m => (typeof m === "string" ? m : m.text))
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.filter(Boolean);
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if (moments.length) {
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return `- ${arc.name}：${moments.join(" → ")}`;
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}
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return `- ${arc.name}：${arc.trajectory}`;
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}
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/**
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* 格式化 L0 锚点行
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* @param {object} l0 - L0 对象
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* @returns {string} 格式化后的行
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*/
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function formatL0Line(l0) {
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return ` › #${l0.floor + 1} [📌] ${String(l0.text || l0.atom?.semantic || "").trim()}`;
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}
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/**
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* 格式化 L1 chunk 行（挂在 L0 下方）
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* @param {object} chunk - L1 chunk 对象
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* @param {boolean} isContext - 是否为上下文（USER 侧）
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* @returns {string} 格式化后的行
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*/
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function formatL1Line(chunk, isContext) {
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const { name1, name2 } = getContext();
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const speaker = chunk.isUser ? (name1 || "用户") : (chunk.speaker || name2 || "角色");
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const text = String(chunk.text || "").trim();
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const symbol = isContext ? "┌" : "›";
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return ` ${symbol} #${chunk.floor + 1} [${speaker}] ${text}`;
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}
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/**
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* 格式化因果事件行
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* @param {object} causalItem - 因果事件项
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* @returns {string} 格式化后的行
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*/
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function formatCausalEventLine(causalItem) {
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const ev = causalItem?.event || {};
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const depth = Math.max(1, Math.min(9, causalItem?._causalDepth || 1));
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const indent = " │" + " ".repeat(depth - 1);
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const prefix = `${indent}├─ 前因`;
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const time = ev.timeLabel ? `【${ev.timeLabel}】` : "";
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const people = (ev.participants || []).join(" / ");
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const summary = cleanSummary(ev.summary);
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const r = parseFloorRange(ev.summary);
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const floorHint = r ? `(#${r.start + 1}${r.end !== r.start ? `-${r.end + 1}` : ""})` : "";
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const lines = [];
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lines.push(`${prefix}${time}${people ? ` ${people}` : ""}`);
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const body = `${summary}${floorHint ? ` ${floorHint}` : ""}`.trim();
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lines.push(`${indent} ${body}`);
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return lines.join("\n");
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}
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// ─────────────────────────────────────────────────────────────────────────────
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// L0→L1 证据单元构建
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// ─────────────────────────────────────────────────────────────────────────────
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/**
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* @typedef {object} EvidenceUnit
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* @property {object} l0 - L0 锚点对象
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* @property {object|null} userL1 - USER 侧 top-1 L1 chunk
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* @property {object|null} aiL1 - AI 侧 top-1 L1 chunk
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* @property {number} totalTokens - 整个单元的 token 估算
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*/
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/**
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* 为一个 L0 构建证据单元
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* @param {object} l0 - L0 对象
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* @param {Map<number, object>} l1ByFloor - 楼层→L1配对映射
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* @returns {EvidenceUnit}
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*/
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function buildEvidenceUnit(l0, l1ByFloor) {
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const pair = l1ByFloor.get(l0.floor);
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const userL1 = pair?.userTop1 || null;
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const aiL1 = pair?.aiTop1 || null;
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// 预计算整个单元的 token 开销
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let totalTokens = estimateTokens(formatL0Line(l0));
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if (userL1) totalTokens += estimateTokens(formatL1Line(userL1, true));
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if (aiL1) totalTokens += estimateTokens(formatL1Line(aiL1, false));
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return { l0, userL1, aiL1, totalTokens };
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}
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/**
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* 格式化一个证据单元为文本行
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* @param {EvidenceUnit} unit - 证据单元
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* @returns {string[]} 文本行数组
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*/
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function formatEvidenceUnit(unit) {
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const lines = [];
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lines.push(formatL0Line(unit.l0));
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if (unit.userL1) {
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lines.push(formatL1Line(unit.userL1, true));
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}
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if (unit.aiL1) {
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lines.push(formatL1Line(unit.aiL1, false));
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}
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return lines;
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}
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// ─────────────────────────────────────────────────────────────────────────────
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// 事件证据收集
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// ─────────────────────────────────────────────────────────────────────────────
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/**
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* 为事件收集范围内的 L0 证据单元
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* @param {object} eventObj - 事件对象
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* @param {object[]} l0Selected - 所有选中的 L0
|
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* @param {Map<number, object>} l1ByFloor - 楼层→L1配对映射
|
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* @param {Set<string>} usedL0Ids - 已消费的 L0 ID 集合（会被修改）
|
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* @returns {EvidenceUnit[]} 该事件的证据单元列表
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*/
|
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function collectEvidenceForEvent(eventObj, l0Selected, l1ByFloor, usedL0Ids) {
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const range = parseFloorRange(eventObj?.summary);
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if (!range) return [];
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|
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const units = [];
|
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|
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for (const l0 of l0Selected) {
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if (usedL0Ids.has(l0.id)) continue;
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if (l0.floor < range.start || l0.floor > range.end) continue;
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const unit = buildEvidenceUnit(l0, l1ByFloor);
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units.push(unit);
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usedL0Ids.add(l0.id);
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}
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// 按楼层排序
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units.sort((a, b) => a.l0.floor - b.l0.floor);
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return units;
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}
|
||
|
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// ─────────────────────────────────────────────────────────────────────────────
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||
// 事件格式化（L2→L0→L1 层级）
|
||
// ─────────────────────────────────────────────────────────────────────────────
|
||
|
||
/**
|
||
* 格式化事件（含 L0→L1 证据）
|
||
* @param {object} eventItem - 事件召回项
|
||
* @param {number} idx - 编号
|
||
* @param {EvidenceUnit[]} evidenceUnits - 该事件的证据单元
|
||
* @param {Map<string, object>} causalById - 因果事件索引
|
||
* @returns {string} 格式化后的文本
|
||
*/
|
||
function formatEventWithEvidence(eventItem, idx, evidenceUnits, causalById) {
|
||
const ev = eventItem.event || {};
|
||
const time = ev.timeLabel || "";
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||
const title = String(ev.title || "").trim();
|
||
const people = (ev.participants || []).join(" / ").trim();
|
||
const summary = cleanSummary(ev.summary);
|
||
|
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const displayTitle = title || people || ev.id || "事件";
|
||
const header = time ? `${idx}.【${time}】${displayTitle}` : `${idx}. ${displayTitle}`;
|
||
|
||
const lines = [header];
|
||
if (people && displayTitle !== people) lines.push(` ${people}`);
|
||
lines.push(` ${summary}`);
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||
|
||
// 因果链
|
||
for (const cid of ev.causedBy || []) {
|
||
const c = causalById?.get(cid);
|
||
if (c) lines.push(formatCausalEventLine(c));
|
||
}
|
||
|
||
// L0→L1 证据单元
|
||
for (const unit of evidenceUnits) {
|
||
lines.push(...formatEvidenceUnit(unit));
|
||
}
|
||
|
||
return lines.join("\n");
|
||
}
|
||
|
||
// ─────────────────────────────────────────────────────────────────────────────
|
||
// 非向量模式
|
||
// ─────────────────────────────────────────────────────────────────────────────
|
||
|
||
/**
|
||
* 构建非向量模式注入文本
|
||
* @param {object} store - 存储对象
|
||
* @returns {string} 注入文本
|
||
*/
|
||
function buildNonVectorPrompt(store) {
|
||
const data = store.json || {};
|
||
const sections = [];
|
||
|
||
// [Constraints] L3 Facts
|
||
const allFacts = getFacts();
|
||
const constraintLines = allFacts
|
||
.filter(f => !f.retracted)
|
||
.sort((a, b) => (b.since || 0) - (a.since || 0))
|
||
.map(f => {
|
||
const since = f.since ? ` (#${f.since + 1})` : '';
|
||
if (isRelationFact(f) && f.trend) {
|
||
return `- ${f.s} ${f.p}: ${f.o} [${f.trend}]${since}`;
|
||
}
|
||
return `- ${f.s}的${f.p}: ${f.o}${since}`;
|
||
});
|
||
|
||
if (constraintLines.length) {
|
||
sections.push(`[定了的事] 已确立的事实\n${constraintLines.join("\n")}`);
|
||
}
|
||
|
||
// [Events] L2 Events
|
||
if (data.events?.length) {
|
||
const lines = data.events.map((ev, i) => {
|
||
const time = ev.timeLabel || "";
|
||
const title = ev.title || "";
|
||
const people = (ev.participants || []).join(" / ");
|
||
const summary = cleanSummary(ev.summary);
|
||
const header = time ? `${i + 1}.【${time}】${title || people}` : `${i + 1}. ${title || people}`;
|
||
return `${header}\n ${summary}`;
|
||
});
|
||
sections.push(`[剧情记忆]\n\n${lines.join("\n\n")}`);
|
||
}
|
||
|
||
// [Arcs]
|
||
if (data.arcs?.length) {
|
||
const lines = data.arcs.map(formatArcLine);
|
||
sections.push(`[人物弧光]\n${lines.join("\n")}`);
|
||
}
|
||
|
||
if (!sections.length) return "";
|
||
|
||
return (
|
||
`${buildSystemPreamble()}\n` +
|
||
`<剧情记忆>\n\n${sections.join("\n\n")}\n\n</剧情记忆>\n` +
|
||
`${buildPostscript()}`
|
||
);
|
||
}
|
||
|
||
/**
|
||
* 构建非向量模式注入文本（公开接口）
|
||
* @returns {string} 注入文本
|
||
*/
|
||
export function buildNonVectorPromptText() {
|
||
if (!getSettings().storySummary?.enabled) {
|
||
return "";
|
||
}
|
||
|
||
const store = getSummaryStore();
|
||
if (!store?.json) {
|
||
return "";
|
||
}
|
||
|
||
let text = buildNonVectorPrompt(store);
|
||
if (!text.trim()) {
|
||
return "";
|
||
}
|
||
|
||
const cfg = getSummaryPanelConfig();
|
||
if (cfg.trigger?.wrapperHead) text = cfg.trigger.wrapperHead + "\n" + text;
|
||
if (cfg.trigger?.wrapperTail) text = text + "\n" + cfg.trigger.wrapperTail;
|
||
|
||
return text;
|
||
}
|
||
|
||
// ─────────────────────────────────────────────────────────────────────────────
|
||
// 向量模式：预算装配
|
||
// ─────────────────────────────────────────────────────────────────────────────
|
||
|
||
/**
|
||
* 构建向量模式注入文本
|
||
* @param {object} store - 存储对象
|
||
* @param {object} recallResult - 召回结果
|
||
* @param {Map<string, object>} causalById - 因果事件索引
|
||
* @param {string[]} focusEntities - 焦点实体
|
||
* @param {object} meta - 元数据
|
||
* @param {object} metrics - 指标对象
|
||
* @returns {Promise<{promptText: string, injectionStats: object, metrics: object}>}
|
||
*/
|
||
async function buildVectorPrompt(store, recallResult, causalById, focusEntities, meta, metrics) {
|
||
const T_Start = performance.now();
|
||
|
||
const data = store.json || {};
|
||
const total = { used: 0, max: MAIN_BUDGET_MAX };
|
||
|
||
// 从 recallResult 解构
|
||
const l0Selected = recallResult?.l0Selected || [];
|
||
const l1ByFloor = recallResult?.l1ByFloor || new Map();
|
||
|
||
// 装配结果
|
||
const assembled = {
|
||
constraints: { lines: [], tokens: 0 },
|
||
directEvents: { lines: [], tokens: 0 },
|
||
relatedEvents: { lines: [], tokens: 0 },
|
||
distantEvidence: { lines: [], tokens: 0 },
|
||
recentEvidence: { lines: [], tokens: 0 },
|
||
arcs: { lines: [], tokens: 0 },
|
||
};
|
||
|
||
// 注入统计
|
||
const injectionStats = {
|
||
budget: { max: TOTAL_BUDGET_MAX, used: 0 },
|
||
constraint: { count: 0, tokens: 0, filtered: 0 },
|
||
arc: { count: 0, tokens: 0 },
|
||
event: { selected: 0, tokens: 0 },
|
||
evidence: { l0InEvents: 0, l1InEvents: 0, tokens: 0 },
|
||
distantEvidence: { units: 0, tokens: 0 },
|
||
recentEvidence: { units: 0, tokens: 0 },
|
||
};
|
||
|
||
const eventDetails = {
|
||
list: [],
|
||
directCount: 0,
|
||
relatedCount: 0,
|
||
};
|
||
|
||
// 已消费的 L0 ID 集合（事件区域消费后，evidence 区域不再重复）
|
||
const usedL0Ids = new Set();
|
||
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
// [Constraints] L3 Facts → 世界约束
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
|
||
const T_Constraint_Start = performance.now();
|
||
|
||
const allFacts = getFacts();
|
||
const knownCharacters = getKnownCharacters(store);
|
||
const constraintLines = formatConstraintsForInjection(allFacts, focusEntities, knownCharacters);
|
||
|
||
if (metrics) {
|
||
metrics.constraint.total = allFacts.length;
|
||
metrics.constraint.filtered = allFacts.length - constraintLines.length;
|
||
}
|
||
|
||
if (constraintLines.length) {
|
||
const constraintBudget = { used: 0, max: Math.min(CONSTRAINT_MAX, total.max - total.used) };
|
||
for (const line of constraintLines) {
|
||
if (!pushWithBudget(assembled.constraints.lines, line, constraintBudget)) break;
|
||
}
|
||
assembled.constraints.tokens = constraintBudget.used;
|
||
total.used += constraintBudget.used;
|
||
injectionStats.constraint.count = assembled.constraints.lines.length;
|
||
injectionStats.constraint.tokens = constraintBudget.used;
|
||
injectionStats.constraint.filtered = allFacts.length - constraintLines.length;
|
||
|
||
if (metrics) {
|
||
metrics.constraint.injected = assembled.constraints.lines.length;
|
||
metrics.constraint.tokens = constraintBudget.used;
|
||
metrics.constraint.samples = assembled.constraints.lines.slice(0, 3).map(line =>
|
||
line.length > 60 ? line.slice(0, 60) + '...' : line
|
||
);
|
||
metrics.timing.constraintFilter = Math.round(performance.now() - T_Constraint_Start);
|
||
}
|
||
} else if (metrics) {
|
||
metrics.timing.constraintFilter = Math.round(performance.now() - T_Constraint_Start);
|
||
}
|
||
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
// [Arcs] 人物弧光
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
|
||
if (data.arcs?.length && total.used < total.max) {
|
||
const { name1 } = getContext();
|
||
const userName = String(name1 || "").trim();
|
||
|
||
const relevant = new Set(
|
||
[userName, ...(focusEntities || [])]
|
||
.map(s => String(s || "").trim())
|
||
.filter(Boolean)
|
||
);
|
||
|
||
const filteredArcs = (data.arcs || []).filter(a => {
|
||
const n = String(a?.name || "").trim();
|
||
return n && relevant.has(n);
|
||
});
|
||
|
||
if (filteredArcs.length) {
|
||
const arcBudget = { used: 0, max: Math.min(ARCS_MAX, total.max - total.used) };
|
||
for (const a of filteredArcs) {
|
||
const line = formatArcLine(a);
|
||
if (!pushWithBudget(assembled.arcs.lines, line, arcBudget)) break;
|
||
}
|
||
assembled.arcs.tokens = arcBudget.used;
|
||
total.used += arcBudget.used;
|
||
injectionStats.arc.count = assembled.arcs.lines.length;
|
||
injectionStats.arc.tokens = arcBudget.used;
|
||
}
|
||
}
|
||
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
// [Events] L2 Events → 直接命中 + 相似命中 + 因果链 + L0→L1 证据
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
const eventHits = (recallResult?.events || []).filter(e => e?.event?.summary);
|
||
|
||
const candidates = [...eventHits].sort((a, b) => (b.similarity || 0) - (a.similarity || 0));
|
||
|
||
const selectedDirect = [];
|
||
const selectedRelated = [];
|
||
|
||
for (let candidateRank = 0; candidateRank < candidates.length; candidateRank++) {
|
||
const e = candidates[candidateRank];
|
||
|
||
if (total.used >= total.max) break;
|
||
|
||
const isDirect = e._recallType === "DIRECT";
|
||
|
||
// 收集该事件范围内的 L0→L1 证据单元
|
||
const evidenceUnits = collectEvidenceForEvent(e.event, l0Selected, l1ByFloor, usedL0Ids);
|
||
|
||
// 格式化事件（含证据）
|
||
const text = formatEventWithEvidence(e, 0, evidenceUnits, causalById);
|
||
const cost = estimateTokens(text);
|
||
|
||
// 预算检查：整个事件（含证据）作为原子单元
|
||
if (total.used + cost > total.max) {
|
||
// 尝试不带证据的版本
|
||
const textNoEvidence = formatEventWithEvidence(e, 0, [], causalById);
|
||
const costNoEvidence = estimateTokens(textNoEvidence);
|
||
|
||
if (total.used + costNoEvidence > total.max) {
|
||
continue;
|
||
}
|
||
|
||
// 放入不带证据的版本，归还已消费的 L0 ID
|
||
for (const unit of evidenceUnits) {
|
||
usedL0Ids.delete(unit.l0.id);
|
||
}
|
||
|
||
if (isDirect) {
|
||
selectedDirect.push({
|
||
event: e.event, text: textNoEvidence, tokens: costNoEvidence,
|
||
evidenceUnits: [], candidateRank,
|
||
});
|
||
} else {
|
||
selectedRelated.push({
|
||
event: e.event, text: textNoEvidence, tokens: costNoEvidence,
|
||
evidenceUnits: [], candidateRank,
|
||
});
|
||
}
|
||
|
||
injectionStats.event.selected++;
|
||
injectionStats.event.tokens += costNoEvidence;
|
||
total.used += costNoEvidence;
|
||
|
||
eventDetails.list.push({
|
||
title: e.event?.title || e.event?.id,
|
||
isDirect,
|
||
hasEvidence: false,
|
||
tokens: costNoEvidence,
|
||
similarity: e.similarity || 0,
|
||
l0Count: 0,
|
||
l1Count: 0,
|
||
});
|
||
|
||
continue;
|
||
}
|
||
|
||
// 预算充足，放入完整版本
|
||
const l0Count = evidenceUnits.length;
|
||
let l1Count = 0;
|
||
for (const unit of evidenceUnits) {
|
||
if (unit.userL1) l1Count++;
|
||
if (unit.aiL1) l1Count++;
|
||
}
|
||
|
||
if (isDirect) {
|
||
selectedDirect.push({
|
||
event: e.event, text, tokens: cost,
|
||
evidenceUnits, candidateRank,
|
||
});
|
||
} else {
|
||
selectedRelated.push({
|
||
event: e.event, text, tokens: cost,
|
||
evidenceUnits, candidateRank,
|
||
});
|
||
}
|
||
|
||
injectionStats.event.selected++;
|
||
injectionStats.event.tokens += cost;
|
||
injectionStats.evidence.l0InEvents += l0Count;
|
||
injectionStats.evidence.l1InEvents += l1Count;
|
||
total.used += cost;
|
||
|
||
eventDetails.list.push({
|
||
title: e.event?.title || e.event?.id,
|
||
isDirect,
|
||
hasEvidence: l0Count > 0,
|
||
tokens: cost,
|
||
similarity: e.similarity || 0,
|
||
l0Count,
|
||
l1Count,
|
||
});
|
||
}
|
||
|
||
// 排序
|
||
selectedDirect.sort((a, b) => getEventSortKey(a.event) - getEventSortKey(b.event));
|
||
selectedRelated.sort((a, b) => getEventSortKey(a.event) - getEventSortKey(b.event));
|
||
|
||
// 重新编号 + 星标
|
||
const directEventTexts = selectedDirect.map((it, i) => {
|
||
const numbered = renumberEventText(it.text, i + 1);
|
||
return it.candidateRank < TOP_N_STAR ? `⭐${numbered}` : numbered;
|
||
});
|
||
|
||
const relatedEventTexts = selectedRelated.map((it, i) => {
|
||
const numbered = renumberEventText(it.text, i + 1);
|
||
return it.candidateRank < TOP_N_STAR ? `⭐${numbered}` : numbered;
|
||
});
|
||
|
||
eventDetails.directCount = selectedDirect.length;
|
||
eventDetails.relatedCount = selectedRelated.length;
|
||
assembled.directEvents.lines = directEventTexts;
|
||
assembled.relatedEvents.lines = relatedEventTexts;
|
||
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
// [Evidence - Distant] 远期证据（已总结范围，未被事件消费的 L0→L1）
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
|
||
const lastSummarized = store.lastSummarizedMesId ?? -1;
|
||
const lastChunkFloor = meta?.lastChunkFloor ?? -1;
|
||
const keepVisible = store.keepVisibleCount ?? 3;
|
||
|
||
// 收集未被事件消费的 L0，按 rerankScore 降序
|
||
const remainingL0 = l0Selected
|
||
.filter(l0 => !usedL0Ids.has(l0.id))
|
||
.sort((a, b) => (b.rerankScore || 0) - (a.rerankScore || 0));
|
||
|
||
// 远期：floor <= lastSummarized
|
||
const distantL0 = remainingL0.filter(l0 => l0.floor <= lastSummarized);
|
||
|
||
if (distantL0.length && total.used < total.max) {
|
||
const distantBudget = { used: 0, max: Math.min(DISTANT_EVIDENCE_MAX, total.max - total.used) };
|
||
|
||
// 按楼层排序（时间顺序）
|
||
distantL0.sort((a, b) => a.floor - b.floor);
|
||
|
||
for (const l0 of distantL0) {
|
||
const unit = buildEvidenceUnit(l0, l1ByFloor);
|
||
|
||
// 原子单元预算检查
|
||
if (distantBudget.used + unit.totalTokens > distantBudget.max) continue;
|
||
|
||
const unitLines = formatEvidenceUnit(unit);
|
||
for (const line of unitLines) {
|
||
assembled.distantEvidence.lines.push(line);
|
||
}
|
||
distantBudget.used += unit.totalTokens;
|
||
usedL0Ids.add(l0.id);
|
||
injectionStats.distantEvidence.units++;
|
||
}
|
||
|
||
assembled.distantEvidence.tokens = distantBudget.used;
|
||
total.used += distantBudget.used;
|
||
injectionStats.distantEvidence.tokens = distantBudget.used;
|
||
}
|
||
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
// [Evidence - Recent] 近期证据（未总结范围，独立预算）
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
|
||
const recentStart = lastSummarized + 1;
|
||
const recentEnd = lastChunkFloor - keepVisible;
|
||
|
||
if (recentEnd >= recentStart) {
|
||
const recentL0 = remainingL0
|
||
.filter(l0 => !usedL0Ids.has(l0.id))
|
||
.filter(l0 => l0.floor >= recentStart && l0.floor <= recentEnd);
|
||
|
||
if (recentL0.length) {
|
||
const recentBudget = { used: 0, max: RECENT_EVIDENCE_MAX };
|
||
|
||
// 按楼层排序（时间顺序）
|
||
recentL0.sort((a, b) => a.floor - b.floor);
|
||
|
||
for (const l0 of recentL0) {
|
||
const unit = buildEvidenceUnit(l0, l1ByFloor);
|
||
|
||
if (recentBudget.used + unit.totalTokens > recentBudget.max) continue;
|
||
|
||
const unitLines = formatEvidenceUnit(unit);
|
||
for (const line of unitLines) {
|
||
assembled.recentEvidence.lines.push(line);
|
||
}
|
||
recentBudget.used += unit.totalTokens;
|
||
usedL0Ids.add(l0.id);
|
||
injectionStats.recentEvidence.units++;
|
||
}
|
||
|
||
assembled.recentEvidence.tokens = recentBudget.used;
|
||
injectionStats.recentEvidence.tokens = recentBudget.used;
|
||
}
|
||
}
|
||
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
// 按注入顺序拼接 sections
|
||
// ═══════════════════════════════════════════════════════════════════════
|
||
|
||
const T_Format_Start = performance.now();
|
||
|
||
const sections = [];
|
||
|
||
if (assembled.constraints.lines.length) {
|
||
sections.push(`[定了的事] 已确立的事实\n${assembled.constraints.lines.join("\n")}`);
|
||
}
|
||
if (assembled.directEvents.lines.length) {
|
||
sections.push(`[印象深的事] 记得很清楚\n\n${assembled.directEvents.lines.join("\n\n")}`);
|
||
}
|
||
if (assembled.relatedEvents.lines.length) {
|
||
sections.push(`[好像有关的事] 听说过或有点模糊\n\n${assembled.relatedEvents.lines.join("\n\n")}`);
|
||
}
|
||
if (assembled.distantEvidence.lines.length) {
|
||
sections.push(`[更早以前] 记忆里残留的老画面\n${assembled.distantEvidence.lines.join("\n")}`);
|
||
}
|
||
if (assembled.recentEvidence.lines.length) {
|
||
sections.push(`[近期] 清晰但还没整理\n${assembled.recentEvidence.lines.join("\n")}`);
|
||
}
|
||
if (assembled.arcs.lines.length) {
|
||
sections.push(`[这些人] 他们的弧光\n${assembled.arcs.lines.join("\n")}`);
|
||
}
|
||
|
||
if (!sections.length) {
|
||
if (metrics) {
|
||
metrics.timing.evidenceAssembly = Math.round(performance.now() - T_Start - (metrics.timing.constraintFilter || 0));
|
||
metrics.timing.formatting = 0;
|
||
}
|
||
return { promptText: "", injectionStats, metrics };
|
||
}
|
||
|
||
const promptText =
|
||
`${buildSystemPreamble()}\n` +
|
||
`<剧情记忆>\n\n${sections.join("\n\n")}\n\n</剧情记忆>\n` +
|
||
`${buildPostscript()}`;
|
||
|
||
if (metrics) {
|
||
metrics.formatting.sectionsIncluded = [];
|
||
if (assembled.constraints.lines.length) metrics.formatting.sectionsIncluded.push('constraints');
|
||
if (assembled.directEvents.lines.length) metrics.formatting.sectionsIncluded.push('direct_events');
|
||
if (assembled.relatedEvents.lines.length) metrics.formatting.sectionsIncluded.push('related_events');
|
||
if (assembled.distantEvidence.lines.length) metrics.formatting.sectionsIncluded.push('distant_evidence');
|
||
if (assembled.recentEvidence.lines.length) metrics.formatting.sectionsIncluded.push('recent_evidence');
|
||
if (assembled.arcs.lines.length) metrics.formatting.sectionsIncluded.push('arcs');
|
||
|
||
metrics.formatting.time = Math.round(performance.now() - T_Format_Start);
|
||
metrics.timing.formatting = metrics.formatting.time;
|
||
|
||
metrics.budget.total = total.used + (assembled.recentEvidence.tokens || 0);
|
||
metrics.budget.limit = TOTAL_BUDGET_MAX;
|
||
metrics.budget.utilization = Math.round(metrics.budget.total / TOTAL_BUDGET_MAX * 100);
|
||
metrics.budget.breakdown = {
|
||
constraints: assembled.constraints.tokens,
|
||
events: injectionStats.event.tokens,
|
||
distantEvidence: injectionStats.distantEvidence.tokens,
|
||
recentEvidence: injectionStats.recentEvidence.tokens,
|
||
arcs: assembled.arcs.tokens,
|
||
};
|
||
|
||
metrics.evidence.tokens = injectionStats.distantEvidence.tokens + injectionStats.recentEvidence.tokens;
|
||
metrics.evidence.assemblyTime = Math.round(
|
||
performance.now() - T_Start - (metrics.timing.constraintFilter || 0) - metrics.formatting.time
|
||
);
|
||
metrics.timing.evidenceAssembly = metrics.evidence.assemblyTime;
|
||
|
||
const totalFacts = allFacts.length;
|
||
metrics.quality.constraintCoverage = totalFacts > 0
|
||
? Math.round(assembled.constraints.lines.length / totalFacts * 100)
|
||
: 100;
|
||
metrics.quality.eventPrecisionProxy = metrics.event?.similarityDistribution?.mean || 0;
|
||
|
||
const totalL0Selected = l0Selected.length;
|
||
const l0WithL1 = l0Selected.filter(l0 => {
|
||
const pair = l1ByFloor.get(l0.floor);
|
||
return pair?.aiTop1 || pair?.userTop1;
|
||
}).length;
|
||
metrics.quality.l1AttachRate = totalL0Selected > 0
|
||
? Math.round(l0WithL1 / totalL0Selected * 100)
|
||
: 0;
|
||
|
||
metrics.quality.potentialIssues = detectIssues(metrics);
|
||
}
|
||
|
||
return { promptText, injectionStats, metrics };
|
||
}
|
||
|
||
// ─────────────────────────────────────────────────────────────────────────────
|
||
// 向量模式：召回 + 注入
|
||
// ─────────────────────────────────────────────────────────────────────────────
|
||
|
||
/**
|
||
* 构建向量模式注入文本（公开接口）
|
||
* @param {boolean} excludeLastAi - 是否排除最后的 AI 消息
|
||
* @param {object} hooks - 钩子函数
|
||
* @returns {Promise<{text: string, logText: string}>}
|
||
*/
|
||
export async function buildVectorPromptText(excludeLastAi = false, hooks = {}) {
|
||
const { postToFrame = null, echo = null, pendingUserMessage = null } = hooks;
|
||
|
||
if (!getSettings().storySummary?.enabled) {
|
||
return { text: "", logText: "" };
|
||
}
|
||
|
||
const { chat } = getContext();
|
||
const store = getSummaryStore();
|
||
|
||
if (!store?.json) {
|
||
return { text: "", logText: "" };
|
||
}
|
||
|
||
const allEvents = store.json.events || [];
|
||
const lastIdx = store.lastSummarizedMesId ?? 0;
|
||
const length = chat?.length || 0;
|
||
|
||
if (lastIdx >= length) {
|
||
return { text: "", logText: "" };
|
||
}
|
||
|
||
const vectorCfg = getVectorConfig();
|
||
if (!vectorCfg?.enabled) {
|
||
return { text: "", logText: "" };
|
||
}
|
||
|
||
const { chatId } = getContext();
|
||
const meta = chatId ? await getMeta(chatId) : null;
|
||
|
||
let recallResult = null;
|
||
let causalById = new Map();
|
||
|
||
try {
|
||
recallResult = await recallMemory(allEvents, vectorCfg, {
|
||
excludeLastAi,
|
||
pendingUserMessage,
|
||
});
|
||
|
||
recallResult = {
|
||
...recallResult,
|
||
events: recallResult?.events || [],
|
||
l0Selected: recallResult?.l0Selected || [],
|
||
l1ByFloor: recallResult?.l1ByFloor || new Map(),
|
||
causalChain: recallResult?.causalChain || [],
|
||
focusEntities: recallResult?.focusEntities || [],
|
||
metrics: recallResult?.metrics || null,
|
||
};
|
||
|
||
// 构建因果事件索引
|
||
causalById = new Map(
|
||
(recallResult.causalChain || [])
|
||
.map(c => [c?.event?.id, c])
|
||
.filter(x => x[0])
|
||
);
|
||
} catch (e) {
|
||
xbLog.error(MODULE_ID, "向量召回失败", e);
|
||
|
||
if (echo && canNotifyRecallFail()) {
|
||
const msg = String(e?.message || "未知错误").replace(/\s+/g, " ").slice(0, 200);
|
||
await echo(`/echo severity=warning 向量召回失败：${msg}`);
|
||
}
|
||
|
||
if (postToFrame) {
|
||
postToFrame({
|
||
type: "RECALL_LOG",
|
||
text: `\n[Vector Recall Failed]\n${String(e?.stack || e?.message || e)}\n`,
|
||
});
|
||
}
|
||
|
||
return { text: "", logText: `\n[Vector Recall Failed]\n${String(e?.stack || e?.message || e)}\n` };
|
||
}
|
||
|
||
const hasUseful =
|
||
(recallResult?.events?.length || 0) > 0 ||
|
||
(recallResult?.l0Selected?.length || 0) > 0 ||
|
||
(recallResult?.causalChain?.length || 0) > 0;
|
||
|
||
if (!hasUseful) {
|
||
if (echo && canNotifyRecallFail()) {
|
||
await echo(
|
||
"/echo severity=warning 向量召回失败：没有可用召回结果（请先在面板中生成向量，或检查指纹不匹配）"
|
||
);
|
||
}
|
||
if (postToFrame) {
|
||
postToFrame({
|
||
type: "RECALL_LOG",
|
||
text: "\n[Vector Recall Empty]\nNo recall candidates / vectors not ready.\n",
|
||
});
|
||
}
|
||
return { text: "", logText: "\n[Vector Recall Empty]\nNo recall candidates / vectors not ready.\n" };
|
||
}
|
||
|
||
const { promptText, metrics: promptMetrics } = await buildVectorPrompt(
|
||
store,
|
||
recallResult,
|
||
causalById,
|
||
recallResult?.focusEntities || [],
|
||
meta,
|
||
recallResult?.metrics || null
|
||
);
|
||
|
||
const cfg = getSummaryPanelConfig();
|
||
let finalText = String(promptText || "");
|
||
if (cfg.trigger?.wrapperHead) finalText = cfg.trigger.wrapperHead + "\n" + finalText;
|
||
if (cfg.trigger?.wrapperTail) finalText = finalText + "\n" + cfg.trigger.wrapperTail;
|
||
|
||
const metricsLogText = promptMetrics ? formatMetricsLog(promptMetrics) : '';
|
||
|
||
if (postToFrame) {
|
||
postToFrame({ type: "RECALL_LOG", text: metricsLogText });
|
||
}
|
||
|
||
return { text: finalText, logText: metricsLogText };
|
||
}
|