recall: normalize entity weights + relation target

modules/story-summary/vector/recall.js

@@ -1,6 +1,7 @@
 // Story Summary - Recall Engine
 // L1 chunk + L2 event 召回
 // - 全量向量打分
+// - 实体权重归一化分配
 // - 指数衰减加权 Query Embedding
 // - L0 floor 加权
 // - RRF 混合检索（向量 + 文本）
@@ -193,6 +194,19 @@ function cleanForRecall(text) {
     return filterText(text).replace(/\[tts:[^\]]*\]/gi, '').trim();
 }
 
+// ═══════════════════════════════════════════════════════════════════════════
+// 从谓词提取关系对象
+// ═══════════════════════════════════════════════════════════════════════════
+
+function extractRelationTarget(p) {
+    if (!p) return '';
+    let m = String(p).match(/^对(.+)的看法$/);
+    if (m) return m[1].trim();
+    m = String(p).match(/^与(.+)的关系$/);
+    if (m) return m[1].trim();
+    return '';
+}
+
 function buildExpDecayWeights(n, beta) {
     const last = n - 1;
     const w = Array.from({ length: n }, (_, i) => Math.exp(beta * (i - last)));
@@ -296,19 +310,22 @@ function buildEntityLexicon(store, allEvents) {
 
 function buildFactGraph(facts) {
     const graph = new Map();
+    const { name1 } = getContext();
+    const userName = normalize(name1);
 
     for (const f of facts || []) {
         if (f?.retracted) continue;
         if (!isRelationFact(f)) continue;
 
         const s = normalize(f?.s);
-        const o = normalize(f?.o);
+        const target = normalize(extractRelationTarget(f?.p));
-        if (!s || !o) continue;
+        if (!s || !target) continue;
+        if (s === userName || target === userName) continue;
 
         if (!graph.has(s)) graph.set(s, new Set());
-        if (!graph.has(o)) graph.set(o, new Set());
+        if (!graph.has(target)) graph.set(target, new Set());
-        graph.get(s).add(o);
+        graph.get(s).add(target);
-        graph.get(o).add(s);
+        graph.get(target).add(s);
     }
 
     return graph;
@@ -347,6 +364,23 @@ function expandByFacts(presentEntities, facts, maxDepth = 2) {
         .map(([term]) => term);
 }
 
+// ═══════════════════════════════════════════════════════════════════════════
+// 实体权重归一化（用于加分分配）
+// ═══════════════════════════════════════════════════════════════════════════
+
+function normalizeEntityWeights(queryEntityWeights) {
+    if (!queryEntityWeights?.size) return new Map();
+
+    const total = Array.from(queryEntityWeights.values()).reduce((a, b) => a + b, 0);
+    if (total <= 0) return new Map();
+
+    const normalized = new Map();
+    for (const [entity, weight] of queryEntityWeights) {
+        normalized.set(entity, weight / total);
+    }
+    return normalized;
+}
+
 function stripFloorTag(s) {
     return String(s || '').replace(/\s*\(#\d+(?:-\d+)?\)\s*$/, '').trim();
 }
@@ -543,7 +577,7 @@ async function searchChunks(queryVector, vectorConfig, l0FloorBonus = new Map(),
 // L2 Events 检索（RRF 混合 + MMR 后置）
 // ═══════════════════════════════════════════════════════════════════════════
 
-async function searchEvents(queryVector, queryTextForSearch, allEvents, vectorConfig, store, queryEntityWeights, l0FloorBonus = new Map()) {
+async function searchEvents(queryVector, queryTextForSearch, allEvents, vectorConfig, store, normalizedEntityWeights, l0FloorBonus = new Map()) {
     const { chatId } = getContext();
     if (!chatId || !queryVector?.length) return [];
 
@@ -567,7 +601,7 @@ async function searchEvents(queryVector, queryTextForSearch, allEvents, vectorCo
     // 向量路检索（只保留 L0 加权）
     // ═══════════════════════════════════════════════════════════════════════
 
-    const ENTITY_BONUS_FACTOR = 0.10;
+    const ENTITY_BONUS_POOL = 0.10;
 
     const scored = (allEvents || []).map((event, idx) => {
         const v = vectorMap.get(event.id);
@@ -589,12 +623,12 @@ async function searchEvents(queryVector, queryTextForSearch, allEvents, vectorCo
         const participants = (event.participants || []).map(p => normalize(p));
         let maxEntityWeight = 0;
         for (const p of participants) {
-            const w = queryEntityWeights.get(p) || 0;
+            const w = normalizedEntityWeights.get(p) || 0;
             if (w > maxEntityWeight) {
                 maxEntityWeight = w;
             }
         }
-        const entityBonus = ENTITY_BONUS_FACTOR * maxEntityWeight;
+        const entityBonus = ENTITY_BONUS_POOL * maxEntityWeight;
         bonus += entityBonus;
 
         return {
@@ -605,10 +639,12 @@ async function searchEvents(queryVector, queryTextForSearch, allEvents, vectorCo
             finalScore: sim + bonus,
             vector: v,
             _entityBonus: entityBonus,
+            _hasPresent: maxEntityWeight > 0,
         };
     });
 
     const entityBonusById = new Map(scored.map(s => [s._id, s._entityBonus]));
+    const hasPresentById = new Map(scored.map(s => [s._id, s._hasPresent]));
 
     const preFilterDistribution = {
         total: scored.length,
@@ -654,7 +690,7 @@ async function searchEvents(queryVector, queryTextForSearch, allEvents, vectorCo
     const results = mmrOutput.map(x => ({
         event: x.event,
         similarity: x.rrf,
-        _recallType: x.type === 'HYBRID' ? 'DIRECT' : 'SIMILAR',
+        _recallType: hasPresentById.get(x.event?.id) ? 'DIRECT' : 'SIMILAR',
         _recallReason: x.type,
         _rrfDetail: { vRank: x.vRank, tRank: x.tRank, rrf: x.rrf },
         _entityBonus: entityBonusById.get(x.event?.id) || 0,
@@ -687,7 +723,7 @@ function formatRecallLog({
     chunkResults,
     eventResults,
     allEvents,
-    queryEntityWeights = new Map(),
+    normalizedEntityWeights = new Map(),
     causalEvents = [],
     chunkPreFilterStats = null,
     l0Results = [],
@@ -724,8 +760,8 @@ function formatRecallLog({
     lines.push('\u2502 【提取实体】                                                 \u2502');
     lines.push('\u2514' + '\u2500'.repeat(61) + '\u2518');
 
-    if (queryEntityWeights?.size) {
+    if (normalizedEntityWeights?.size) {
-        const sorted = Array.from(queryEntityWeights.entries())
+        const sorted = Array.from(normalizedEntityWeights.entries())
             .sort((a, b) => b[1] - a[1])
             .slice(0, 8);
         const formatted = sorted
@@ -739,6 +775,20 @@ function formatRecallLog({
         lines.push(`  扩散: ${expandedTerms.join('、')}`);
     }
 
+    lines.push('');
+    lines.push('  实体归一化（用于加分）:');
+    if (normalizedEntityWeights?.size) {
+        const sorted = Array.from(normalizedEntityWeights.entries())
+            .sort((a, b) => b[1] - a[1])
+            .slice(0, 8);
+        const formatted = sorted
+            .map(([e, w]) => `${e}(${(w * 100).toFixed(0)}%)`)
+            .join(' | ');
+        lines.push(`    ${formatted}`);
+    } else {
+        lines.push('    (无)');
+    }
+
     lines.push('');
     lines.push('\u250c' + '\u2500'.repeat(61) + '\u2510');
     lines.push('\u2502 【召回统计】                                                 \u2502');
@@ -834,6 +884,7 @@ export async function recallMemory(queryText, allEvents, vectorConfig, options =
     const queryEntities = Array.from(queryEntityWeights.keys());
     const facts = getFacts(store);
     const expandedTerms = expandByFacts(queryEntities, facts, 2);
+    const normalizedEntityWeights = normalizeEntityWeights(queryEntityWeights);
 
     // 构建文本查询串：最后一条消息 + 实体 + 关键词
     const lastSeg = segments[segments.length - 1] || '';
@@ -859,7 +910,7 @@ export async function recallMemory(queryText, allEvents, vectorConfig, options =
 
     const [chunkResults, eventResults] = await Promise.all([
         searchChunks(queryVector, vectorConfig, l0FloorBonus, lastSummarizedFloor),
-        searchEvents(queryVector, queryTextForSearch, allEvents, vectorConfig, store, queryEntityWeights, l0FloorBonus),
+        searchEvents(queryVector, queryTextForSearch, allEvents, vectorConfig, store, normalizedEntityWeights, l0FloorBonus),
     ]);
 
     const chunkPreFilterStats = chunkResults._preFilterStats || null;
@@ -897,7 +948,7 @@ export async function recallMemory(queryText, allEvents, vectorConfig, options =
         chunkResults: mergedChunks,
         eventResults,
         allEvents,
-        queryEntityWeights,
+        normalizedEntityWeights,
         causalEvents: causalEventsTruncated,
         chunkPreFilterStats,
         l0Results,