LittleWhiteBox/modules/story-summary/generate/prompt.js

// ═══════════════════════════════════════════════════════════════════════════
// Story Summary - Prompt Injection (v4 - 统一命名)
//
// 命名规范：
// - 存储层用 L0/L1/L2/L3（StateAtom/Chunk/Event/Fact）
// - 装配层用语义名称：constraint/event/evidence/arc
//
// 职责：
// - 仅负责"构建注入文本"，不负责写入 extension_prompts
// - 注入发生在 story-summary.js：GENERATION_STARTED 时写入 extension_prompts
// ═══════════════════════════════════════════════════════════════════════════

import { getContext } from "../../../../../../extensions.js";
import { xbLog } from "../../../core/debug-core.js";
import { getSummaryStore, getFacts, isRelationFact } from "../data/store.js";
import { getVectorConfig, getSummaryPanelConfig, getSettings } from "../data/config.js";
import { recallMemory } from "../vector/retrieval/recall.js";
import { getChunksByFloors, getAllChunkVectors, getAllEventVectors, getMeta } from "../vector/storage/chunk-store.js";

// Metrics
import { formatMetricsLog, detectIssues } from "../vector/retrieval/metrics.js";

const MODULE_ID = "summaryPrompt";

// ─────────────────────────────────────────────────────────────────────────────
// 召回失败提示节流
// ─────────────────────────────────────────────────────────────────────────────

let lastRecallFailAt = 0;
const RECALL_FAIL_COOLDOWN_MS = 10_000;

function canNotifyRecallFail() {
    const now = Date.now();
    if (now - lastRecallFailAt < RECALL_FAIL_COOLDOWN_MS) return false;
    lastRecallFailAt = now;
    return true;
}

// ─────────────────────────────────────────────────────────────────────────────
// 预算常量
// ─────────────────────────────────────────────────────────────────────────────

const MAIN_BUDGET_MAX = 10000;
const DISTANT_EVIDENCE_MAX = 2500;
const RECENT_EVIDENCE_MAX = 5000;
const TOTAL_BUDGET_MAX = 15000;
const CONSTRAINT_MAX = 2000;
const ARCS_MAX = 1500;
const TOP_N_STAR = 5;

// ─────────────────────────────────────────────────────────────────────────────
// 工具函数
// ─────────────────────────────────────────────────────────────────────────────

/**
 * 估算文本 token 数量
 * @param {string} text - 输入文本
 * @returns {number} token 估算值
 */
function estimateTokens(text) {
    if (!text) return 0;
    const s = String(text);
    const zh = (s.match(/[\u4e00-\u9fff]/g) || []).length;
    return Math.ceil(zh + (s.length - zh) / 4);
}

/**
 * 带预算限制的行追加
 * @param {string[]} lines - 行数组
 * @param {string} text - 要追加的文本
 * @param {object} state - 预算状态 {used, max}
 * @returns {boolean} 是否追加成功
 */
function pushWithBudget(lines, text, state) {
    const t = estimateTokens(text);
    if (state.used + t > state.max) return false;
    lines.push(text);
    state.used += t;
    return true;
}

/**
 * 计算余弦相似度
 * @param {number[]} a - 向量A
 * @param {number[]} b - 向量B
 * @returns {number} 相似度
 */
function cosineSimilarity(a, b) {
    if (!a?.length || !b?.length || a.length !== b.length) return 0;
    let dot = 0, nA = 0, nB = 0;
    for (let i = 0; i < a.length; i++) {
        dot += a[i] * b[i];
        nA += a[i] * a[i];
        nB += b[i] * b[i];
    }
    return nA && nB ? dot / (Math.sqrt(nA) * Math.sqrt(nB)) : 0;
}

/**
 * 解析事件摘要中的楼层范围
 * @param {string} summary - 事件摘要
 * @returns {{start: number, end: number}|null} 楼层范围
 */
function parseFloorRange(summary) {
    if (!summary) return null;
    const match = String(summary).match(/\(#(\d+)(?:-(\d+))?\)/);
    if (!match) return null;
    const start = Math.max(0, parseInt(match[1], 10) - 1);
    const end = Math.max(0, (match[2] ? parseInt(match[2], 10) : parseInt(match[1], 10)) - 1);
    return { start, end };
}

/**
 * 清理事件摘要（移除楼层标记）
 * @param {string} summary - 事件摘要
 * @returns {string} 清理后的摘要
 */
function cleanSummary(summary) {
    return String(summary || "")
        .replace(/\s*\(#\d+(?:-\d+)?\)\s*$/, "")
        .trim();
}

/**
 * 标准化字符串
 * @param {string} s - 输入字符串
 * @returns {string} 标准化后的字符串
 */
function normalize(s) {
    return String(s || '')
        .normalize('NFKC')
        .replace(/[\u200B-\u200D\uFEFF]/g, '')
        .trim()
        .toLowerCase();
}

// ─────────────────────────────────────────────────────────────────────────────
// 上下文配对工具函数
// ─────────────────────────────────────────────────────────────────────────────

/**
 * 获取 chunk 的上下文楼层
 * @param {object} chunk - chunk 对象
 * @returns {number} 上下文楼层（-1 表示无）
 */
function getContextFloor(chunk) {
    if (chunk.isAnchorVirtual) return -1;
    return chunk.isUser ? chunk.floor + 1 : chunk.floor - 1;
}

/**
 * 选择上下文 chunk
 * @param {object[]} candidates - 候选 chunks
 * @param {object} mainChunk - 主 chunk
 * @returns {object|null} 选中的上下文 chunk
 */
function pickContextChunk(candidates, mainChunk) {
    if (!candidates?.length) return null;
    const targetIsUser = !mainChunk.isUser;
    const opposite = candidates.find(c => c.isUser === targetIsUser);
    if (opposite) return opposite;
    return candidates[0];
}

/**
 * 格式化上下文 chunk 行
 * @param {object} chunk - chunk 对象
 * @param {boolean} isAbove - 是否在上方
 * @returns {string} 格式化后的行
 */
function formatContextChunkLine(chunk, isAbove) {
    const { name1, name2 } = getContext();
    const speaker = chunk.isUser ? (name1 || "用户") : (chunk.speaker || name2 || "角色");
    const text = String(chunk.text || "").trim();
    const symbol = isAbove ? "┌" : "└";
    return `  ${symbol} #${chunk.floor + 1} [${speaker}] ${text}`;
}

// ─────────────────────────────────────────────────────────────────────────────
// 系统前导与后缀
// ─────────────────────────────────────────────────────────────────────────────

/**
 * 构建系统前导文本
 * @returns {string} 前导文本
 */
function buildSystemPreamble() {
    return [
        "以上是还留在眼前的对话",
        "以下是脑海里的记忆：",
        "• [定了的事] 这些是不会变的",
        "• 其余部分是过往经历的回忆碎片",
        "",
        "请内化这些记忆：",
    ].join("\n");
}

/**
 * 构建后缀文本
 * @returns {string} 后缀文本
 */
function buildPostscript() {
    return [
        "",
        "这些记忆是真实的，请自然地记住它们。",
    ].join("\n");
}

// ─────────────────────────────────────────────────────────────────────────────
// [Constraints] L3 Facts 过滤与格式化
// ─────────────────────────────────────────────────────────────────────────────

/**
 * 获取已知角色集合
 * @param {object} store - 存储对象
 * @returns {Set<string>} 角色名称集合（标准化后）
 */
function getKnownCharacters(store) {
    const names = new Set();

    const arcs = store?.json?.arcs || [];
    for (const a of arcs) {
        if (a.name) names.add(normalize(a.name));
    }

    const main = store?.json?.characters?.main || [];
    for (const m of main) {
        const name = typeof m === 'string' ? m : m.name;
        if (name) names.add(normalize(name));
    }

    const { name1, name2 } = getContext();
    if (name1) names.add(normalize(name1));
    if (name2) names.add(normalize(name2));

    return names;
}

/**
 * 解析关系谓词中的目标
 * @param {string} predicate - 谓词
 * @returns {string|null} 目标名称
 */
function parseRelationTarget(predicate) {
    const match = String(predicate || '').match(/^对(.+)的/);
    return match ? match[1] : null;
}

/**
 * 按相关性过滤 facts
 * @param {object[]} facts - 所有 facts
 * @param {string[]} focusEntities - 焦点实体
 * @param {Set<string>} knownCharacters - 已知角色
 * @returns {object[]} 过滤后的 facts
 */
function filterConstraintsByRelevance(facts, focusEntities, knownCharacters) {
    if (!facts?.length) return [];

    const focusSet = new Set((focusEntities || []).map(normalize));

    return facts.filter(f => {
        // isState 的 facts 始终保留
        if (f._isState === true) return true;

        // 关系类 facts：检查 from/to 是否在焦点中
        if (isRelationFact(f)) {
            const from = normalize(f.s);
            const target = parseRelationTarget(f.p);
            const to = target ? normalize(target) : '';

            if (focusSet.has(from) || focusSet.has(to)) return true;
            return false;
        }

        // 其他 facts：检查主体是否在焦点中
        const subjectNorm = normalize(f.s);
        if (knownCharacters.has(subjectNorm)) {
            return focusSet.has(subjectNorm);
        }

        return true;
    });
}

/**
 * 格式化 constraints 用于注入
 * @param {object[]} facts - 所有 facts
 * @param {string[]} focusEntities - 焦点实体
 * @param {Set<string>} knownCharacters - 已知角色
 * @returns {string[]} 格式化后的行
 */
function formatConstraintsForInjection(facts, focusEntities, knownCharacters) {
    const filtered = filterConstraintsByRelevance(facts, focusEntities, knownCharacters);

    if (!filtered.length) return [];

    return filtered
        .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}`;
        });
}

// ─────────────────────────────────────────────────────────────────────────────
// 格式化函数
// ─────────────────────────────────────────────────────────────────────────────

/**
 * 格式化弧光行
 * @param {object} arc - 弧光对象
 * @returns {string} 格式化后的行
 */
function formatArcLine(arc) {
    const moments = (arc.moments || [])
        .map(m => (typeof m === "string" ? m : m.text))
        .filter(Boolean);

    if (moments.length) {
        return `- ${arc.name}：${moments.join(" → ")}`;
    }
    return `- ${arc.name}：${arc.trajectory}`;
}

/**
 * 格式化 evidence chunk 完整行
 * @param {object} chunk - chunk 对象
 * @returns {string} 格式化后的行
 */
function formatEvidenceFullLine(chunk) {
    const { name1, name2 } = getContext();

    if (chunk.isAnchorVirtual) {
        return `› #${chunk.floor + 1} [📌] ${String(chunk.text || "").trim()}`;
    }

    const speaker = chunk.isUser ? (name1 || "用户") : (chunk.speaker || name2 || "角色");
    return `› #${chunk.floor + 1} [${speaker}] ${String(chunk.text || "").trim()}`;
}

/**
 * 格式化因果事件行
 * @param {object} causalItem - 因果事件项
 * @param {Map} causalById - 因果事件索引
 * @returns {string} 格式化后的行
 */
function formatCausalEventLine(causalItem, causalById) {
    const ev = causalItem?.event || {};
    const depth = Math.max(1, Math.min(9, causalItem?._causalDepth || 1));
    const indent = "  │" + "  ".repeat(depth - 1);
    const prefix = `${indent}├─ 前因`;

    const time = ev.timeLabel ? `【${ev.timeLabel}】` : "";
    const people = (ev.participants || []).join(" / ");
    const summary = cleanSummary(ev.summary);

    const r = parseFloorRange(ev.summary);
    const floorHint = r ? `(#${r.start + 1}${r.end !== r.start ? `-${r.end + 1}` : ""})` : "";

    const lines = [];
    lines.push(`${prefix}${time}${people ? ` ${people}` : ""}`);
    const body = `${summary}${floorHint ? ` ${floorHint}` : ""}`.trim();
    lines.push(`${indent}  ${body}`);

    const evidence = causalItem._evidenceChunk;
    if (evidence) {
        const speaker = evidence.speaker || "角色";
        const text = String(evidence.text || "").trim();
        lines.push(`${indent}  › #${evidence.floor + 1} [${speaker}] ${text}`);
    }

    return lines.join("\n");
}

/**
 * 重新编号事件文本
 * @param {string} text - 原始文本
 * @param {number} newIndex - 新编号
 * @returns {string} 重新编号后的文本
 */
function renumberEventText(text, newIndex) {
    const s = String(text || "");
    return s.replace(/^(\s*)\d+(\.\s*(?:【)?)/, `$1${newIndex}$2`);
}

/**
 * 获取事件排序键
 * @param {object} event - 事件对象
 * @returns {number} 排序键
 */
function getEventSortKey(event) {
    const r = parseFloorRange(event?.summary);
    if (r) return r.start;
    const m = String(event?.id || "").match(/evt-(\d+)/);
    return m ? parseInt(m[1], 10) : Number.MAX_SAFE_INTEGER;
}

// ─────────────────────────────────────────────────────────────────────────────
// 按楼层分组装配 evidence（修复上下文重复）
// ─────────────────────────────────────────────────────────────────────────────

/**
 * 按楼层装配 evidence
 * @param {object[]} evidenceCandidates - 候选 evidence
 * @param {Map} contextChunksByFloor - 上下文 chunks 索引
 * @param {object} budget - 预算状态
 * @returns {{lines: string[], anchorCount: number, contextPairsCount: number}}
 */
function assembleEvidenceByFloor(evidenceCandidates, contextChunksByFloor, budget) {
    if (!evidenceCandidates?.length) {
        return { lines: [], anchorCount: 0, contextPairsCount: 0 };
    }

    // 1. 按楼层分组
    const byFloor = new Map();
    for (const c of evidenceCandidates) {
        const arr = byFloor.get(c.floor) || [];
        arr.push(c);
        byFloor.set(c.floor, arr);
    }

    // 2. 楼层内按 chunkIdx 排序
    for (const [, chunks] of byFloor) {
        chunks.sort((a, b) => (a.chunkIdx ?? 0) - (b.chunkIdx ?? 0));
    }

    // 3. 按楼层顺序装配
    const floorsSorted = Array.from(byFloor.keys()).sort((a, b) => a - b);

    const lines = [];
    let anchorCount = 0;
    let contextPairsCount = 0;

    for (const floor of floorsSorted) {
        const chunks = byFloor.get(floor);
        if (!chunks?.length) continue;

        // 分离锚点虚拟 chunks 和真实 chunks
        const anchorChunks = chunks.filter(c => c.isAnchorVirtual);
        const realChunks = chunks.filter(c => !c.isAnchorVirtual);

        // 锚点直接输出（不需要上下文）
        for (const c of anchorChunks) {
            const line = formatEvidenceFullLine(c);
            if (!pushWithBudget(lines, line, budget)) {
                return { lines, anchorCount, contextPairsCount };
            }
            anchorCount++;
        }

        // 真实 chunks 按楼层统一处理
        if (realChunks.length > 0) {
            const firstChunk = realChunks[0];
            const pairFloor = getContextFloor(firstChunk);
            const pairCandidates = contextChunksByFloor.get(pairFloor) || [];
            const contextChunk = pickContextChunk(pairCandidates, firstChunk);

            // 上下文在前
            if (contextChunk && contextChunk.floor < floor) {
                const contextLine = formatContextChunkLine(contextChunk, true);
                if (!pushWithBudget(lines, contextLine, budget)) {
                    return { lines, anchorCount, contextPairsCount };
                }
                contextPairsCount++;
            }

            // 输出该楼层所有真实 chunks
            for (const c of realChunks) {
                const line = formatEvidenceFullLine(c);
                if (!pushWithBudget(lines, line, budget)) {
                    return { lines, anchorCount, contextPairsCount };
                }
            }

            // 上下文在后
            if (contextChunk && contextChunk.floor > floor) {
                const contextLine = formatContextChunkLine(contextChunk, false);
                if (!pushWithBudget(lines, contextLine, budget)) {
                    return { lines, anchorCount, contextPairsCount };
                }
                contextPairsCount++;
            }
        }
    }

    return { lines, anchorCount, contextPairsCount };
}

// ─────────────────────────────────────────────────────────────────────────────
// 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} 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, injectionLogText: string, injectionStats: object, metrics: object}>}
 */
async function buildVectorPrompt(store, recallResult, causalById, focusEntities = [], meta = null, metrics = null) {
    const T_Start = performance.now();

    const { chatId } = getContext();
    const data = store.json || {};
    const total = { used: 0, max: MAIN_BUDGET_MAX };

    // 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: { attached: 0, tokens: 0 },
        distantEvidence: { injected: 0, tokens: 0, anchorCount: 0, contextPairs: 0 },
    };

    const recentEvidenceStats = {
        injected: 0,
        tokens: 0,
        floorRange: "N/A",
        contextPairs: 0,
    };

    const eventDetails = {
        list: [],
        directCount: 0,
        relatedCount: 0,
    };

    // ═══════════════════════════════════════════════════════════════════════
    // [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
    // ═══════════════════════════════════════════════════════════════════════

    const eventHits = (recallResult?.events || []).filter(e => e?.event?.summary);
    const evidenceChunks = recallResult?.evidenceChunks || [];
    const usedChunkIds = new Set();

    /**
     * 为事件选择最佳证据 chunk
     * @param {object} eventObj - 事件对象
     * @returns {object|null} 最佳 chunk
     */
    function pickBestEvidenceForEvent(eventObj) {
        const range = parseFloorRange(eventObj?.summary);
        if (!range) return null;

        let best = null;
        for (const c of evidenceChunks) {
            if (usedChunkIds.has(c.chunkId)) continue;
            if (c.floor < range.start || c.floor > range.end) continue;

            if (!best) {
                best = c;
            } else if (c.isAnchorVirtual && !best.isAnchorVirtual) {
                best = c;
            } else if (c.isAnchorVirtual === best.isAnchorVirtual && (c.chunkIdx ?? 0) < (best.chunkIdx ?? 0)) {
                best = c;
            }
        }
        return best;
    }

    /**
     * 格式化事件带证据
     * @param {object} eventItem - 事件项
     * @param {number} idx - 编号
     * @param {object} chunk - 证据 chunk
     * @returns {string} 格式化后的文本
     */
    function formatEventWithEvidence(eventItem, idx, chunk) {
        const ev = eventItem.event || {};
        const time = ev.timeLabel || "";
        const title = String(ev.title || "").trim();
        const people = (ev.participants || []).join(" / ").trim();
        const summary = cleanSummary(ev.summary);

        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}`);

        for (const cid of ev.causedBy || []) {
            const c = causalById?.get(cid);
            if (c) lines.push(formatCausalEventLine(c, causalById));
        }

        if (chunk) {
            lines.push(`  ${formatEvidenceFullLine(chunk)}`);
        }

        return lines.join("\n");
    }

    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";

        const bestChunk = pickBestEvidenceForEvent(e.event);

        let text = formatEventWithEvidence(e, 0, bestChunk);
        let cost = estimateTokens(text);
        let hasEvidence = !!bestChunk;
        let chosenChunk = bestChunk || null;

        if (total.used + cost > total.max) {
            text = formatEventWithEvidence(e, 0, null);
            cost = estimateTokens(text);
            hasEvidence = false;
            chosenChunk = null;

            if (total.used + cost > total.max) {
                continue;
            }
        }

        if (isDirect) {
            selectedDirect.push({ event: e.event, text, tokens: cost, chunk: chosenChunk, hasEvidence, candidateRank });
        } else {
            selectedRelated.push({ event: e.event, text, tokens: cost, chunk: chosenChunk, hasEvidence, candidateRank });
        }

        injectionStats.event.selected++;
        total.used += cost;

        if (hasEvidence && bestChunk) {
            const chunkLine = formatEvidenceFullLine(bestChunk);
            const ct = estimateTokens(chunkLine);
            injectionStats.evidence.attached++;
            injectionStats.evidence.tokens += ct;
            usedChunkIds.add(bestChunk.chunkId);

            injectionStats.event.tokens += Math.max(0, cost - ct);
        } else {
            injectionStats.event.tokens += cost;
        }

        eventDetails.list.push({
            title: e.event?.title || e.event?.id,
            isDirect,
            hasEvidence,
            tokens: cost,
            similarity: e.similarity || 0,
            hasAnchorEvidence: bestChunk?.isAnchorVirtual || false,
        });
    }

    // 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] L1 Chunks → 远期证据（已总结范围）
    // ═══════════════════════════════════════════════════════════════════════

    const lastSummarized = store.lastSummarizedMesId ?? -1;
    const lastChunkFloor = meta?.lastChunkFloor ?? -1;
    const keepVisible = store.keepVisibleCount ?? 3;

    const distantContextFloors = new Set();
    const distantCandidates = evidenceChunks
        .filter(c => !usedChunkIds.has(c.chunkId))
        .filter(c => c.floor <= lastSummarized);

    for (const c of distantCandidates) {
        if (c.isAnchorVirtual) continue;
        const pairFloor = getContextFloor(c);
        if (pairFloor >= 0) distantContextFloors.add(pairFloor);
    }

    let contextChunksByFloor = new Map();
    if (chatId && distantContextFloors.size > 0) {
        try {
            const contextChunks = await getChunksByFloors(chatId, Array.from(distantContextFloors));
            for (const pc of contextChunks) {
                if (!contextChunksByFloor.has(pc.floor)) {
                    contextChunksByFloor.set(pc.floor, []);
                }
                contextChunksByFloor.get(pc.floor).push(pc);
            }
        } catch (e) {
            xbLog.warn(MODULE_ID, "获取配对chunks失败", e);
        }
    }

    if (distantCandidates.length && total.used < total.max) {
        const distantBudget = { used: 0, max: Math.min(DISTANT_EVIDENCE_MAX, total.max - total.used) };

        const result = assembleEvidenceByFloor(
            distantCandidates.sort((a, b) => (a.floor - b.floor) || ((a.chunkIdx ?? 0) - (b.chunkIdx ?? 0))),
            contextChunksByFloor,
            distantBudget
        );

        assembled.distantEvidence.lines = result.lines;
        assembled.distantEvidence.tokens = distantBudget.used;
        total.used += distantBudget.used;

        injectionStats.distantEvidence.injected = result.lines.length;
        injectionStats.distantEvidence.tokens = distantBudget.used;
        injectionStats.distantEvidence.anchorCount = result.anchorCount;
        injectionStats.distantEvidence.contextPairs = result.contextPairsCount;
    }

    // ═══════════════════════════════════════════════════════════════════════
    // [Evidence - Recent] L1 Chunks → 近期证据（未总结范围，独立预算）
    // ═══════════════════════════════════════════════════════════════════════

    const recentStart = lastSummarized + 1;
    const recentEnd = lastChunkFloor - keepVisible;

    if (evidenceChunks.length && recentEnd >= recentStart) {
        const recentCandidates = evidenceChunks
            .filter(c => !usedChunkIds.has(c.chunkId))
            .filter(c => c.floor >= recentStart && c.floor <= recentEnd);

        const recentContextFloors = new Set();
        for (const c of recentCandidates) {
            if (c.isAnchorVirtual) continue;
            const pairFloor = getContextFloor(c);
            if (pairFloor >= 0) recentContextFloors.add(pairFloor);
        }

        if (chatId && recentContextFloors.size > 0) {
            const newFloors = Array.from(recentContextFloors).filter(f => !contextChunksByFloor.has(f));
            if (newFloors.length > 0) {
                try {
                    const newContextChunks = await getChunksByFloors(chatId, newFloors);
                    for (const pc of newContextChunks) {
                        if (!contextChunksByFloor.has(pc.floor)) {
                            contextChunksByFloor.set(pc.floor, []);
                        }
                        contextChunksByFloor.get(pc.floor).push(pc);
                    }
                } catch (e) {
                    xbLog.warn(MODULE_ID, "获取近期配对chunks失败", e);
                }
            }
        }

        if (recentCandidates.length) {
            const recentBudget = { used: 0, max: RECENT_EVIDENCE_MAX };

            const result = assembleEvidenceByFloor(
                recentCandidates.sort((a, b) => (a.floor - b.floor) || ((a.chunkIdx ?? 0) - (b.chunkIdx ?? 0))),
                contextChunksByFloor,
                recentBudget
            );

            assembled.recentEvidence.lines = result.lines;
            assembled.recentEvidence.tokens = recentBudget.used;

            recentEvidenceStats.injected = result.lines.length;
            recentEvidenceStats.tokens = recentBudget.used;
            recentEvidenceStats.floorRange = `${recentStart + 1}~${recentEnd + 1}楼`;
            recentEvidenceStats.contextPairs = result.contextPairsCount;
        }
    }

    // ═══════════════════════════════════════════════════════════════════════
    // 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: "", injectionLogText: "", 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 + injectionStats.evidence.tokens,
            distantEvidence: injectionStats.distantEvidence.tokens,
            recentEvidence: recentEvidenceStats.tokens || 0,
            arcs: assembled.arcs.tokens,
        };

        metrics.evidence.tokens = injectionStats.distantEvidence.tokens + (recentEvidenceStats.tokens || 0);
        metrics.evidence.contextPairsAdded = injectionStats.distantEvidence.contextPairs + recentEvidenceStats.contextPairs;
        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 totalSelected = metrics.evidence.selected || 0;
        const attached = injectionStats.evidence.attached;
        metrics.quality.evidenceDensity = totalSelected > 0
            ? Math.round(attached / totalSelected * 100)
            : 0;
            
        const selectedReal = metrics.evidence.selectedByType?.chunkReal || 0;
        const selectedTotal = metrics.evidence.selected || 0;
        metrics.quality.chunkRealRatio = selectedTotal > 0
            ? Math.round(selectedReal / selectedTotal * 100)
            : 0;
            
        metrics.quality.potentialIssues = detectIssues(metrics);
    }

    return { promptText, injectionLogText: "", injectionStats, metrics };
}

// ─────────────────────────────────────────────────────────────────────────────
// 因果证据补充
// ─────────────────────────────────────────────────────────────────────────────

/**
 * 为因果事件附加证据
 * @param {object[]} causalChain - 因果链
 * @param {Map} eventVectorMap - 事件向量索引
 * @param {Map} chunkVectorMap - chunk 向量索引
 * @param {Map} chunksMap - chunks 索引
 */
async function attachEvidenceToCausalEvents(causalChain, eventVectorMap, chunkVectorMap, chunksMap) {
    for (const c of causalChain) {
        c._evidenceChunk = null;

        const ev = c.event;
        if (!ev?.id) continue;

        const evVec = eventVectorMap.get(ev.id);
        if (!evVec?.length) continue;

        const range = parseFloorRange(ev.summary);
        if (!range) continue;

        const candidateChunks = [];
        for (const [chunkId, chunk] of chunksMap) {
            if (chunk.floor >= range.start && chunk.floor <= range.end) {
                const vec = chunkVectorMap.get(chunkId);
                if (vec?.length) candidateChunks.push({ chunk, vec });
            }
        }
        if (!candidateChunks.length) continue;

        let best = null;
        let bestSim = -1;
        for (const { chunk, vec } of candidateChunks) {
            const sim = cosineSimilarity(evVec, vec);
            if (sim > bestSim) {
                bestSim = sim;
                best = chunk;
            }
        }

        if (best && bestSim > 0.3) {
            c._evidenceChunk = {
                floor: best.floor,
                speaker: best.speaker,
                text: best.text,
                similarity: bestSim,
            };
        }
    }
}

// ─────────────────────────────────────────────────────────────────────────────
// 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 || [],
            evidenceChunks: recallResult?.evidenceChunks || [],
            causalChain: recallResult?.causalChain || [],
            focusEntities: recallResult?.focusEntities || [],
            logText: recallResult?.logText || "",
            metrics: recallResult?.metrics || null,
        };

        const causalChain = recallResult.causalChain || [];
        if (causalChain.length > 0) {
            if (chatId) {
                try {
                    const floors = new Set();
                    for (const c of causalChain) {
                        const r = parseFloorRange(c.event?.summary);
                        if (!r) continue;
                        for (let f = r.start; f <= r.end; f++) floors.add(f);
                    }

                    const [chunksList, chunkVecs, eventVecs] = await Promise.all([
                        getChunksByFloors(chatId, Array.from(floors)),
                        getAllChunkVectors(chatId),
                        getAllEventVectors(chatId),
                    ]);

                    const chunksMap = new Map(chunksList.map(c => [c.chunkId, c]));
                    const chunkVectorMap = new Map(chunkVecs.map(v => [v.chunkId, v.vector]));
                    const eventVectorMap = new Map(eventVecs.map(v => [v.eventId, v.vector]));

                    await attachEvidenceToCausalEvents(causalChain, eventVectorMap, chunkVectorMap, chunksMap);
                } catch (e) {
                    xbLog.warn(MODULE_ID, "Causal evidence attachment failed", e);
                }
            }
        }

        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?.evidenceChunks?.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 };
}