563 lines
20 KiB
JavaScript
563 lines
20 KiB
JavaScript
// ============================================================================
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// state-integration.js - L0 状态层集成
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// Phase 1: 批量 LLM 提取（只存文本）
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// Phase 2: 统一向量化（提取完成后）
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// ============================================================================
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import { getContext } from '../../../../../../../extensions.js';
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import { saveMetadataDebounced } from '../../../../../../../extensions.js';
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import { xbLog } from '../../../../core/debug-core.js';
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import {
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saveStateAtoms,
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saveStateVectors,
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deleteStateAtomsFromFloor,
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deleteStateVectorsFromFloor,
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getStateAtoms,
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clearStateAtoms,
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clearStateVectors,
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getL0FloorStatus,
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setL0FloorStatus,
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clearL0Index,
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deleteL0IndexFromFloor,
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} from '../storage/state-store.js';
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import { embed } from '../llm/siliconflow.js';
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import { extractAtomsForRound, cancelBatchExtraction } from '../llm/atom-extraction.js';
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import { getVectorConfig } from '../../data/config.js';
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import { getEngineFingerprint } from '../utils/embedder.js';
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import { filterText } from '../utils/text-filter.js';
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const MODULE_ID = 'state-integration';
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// ★ 并发配置
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const CONCURRENCY = 10;
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const STAGGER_DELAY = 15;
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const DEBUG_CONCURRENCY = true;
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const R_AGG_MAX_CHARS = 256;
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let initialized = false;
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let extractionCancelled = false;
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export function cancelL0Extraction() {
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extractionCancelled = true;
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cancelBatchExtraction();
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}
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// ============================================================================
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// 初始化
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// ============================================================================
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export function initStateIntegration() {
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if (initialized) return;
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initialized = true;
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globalThis.LWB_StateRollbackHook = handleStateRollback;
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xbLog.info(MODULE_ID, 'L0 状态层集成已初始化');
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}
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// ============================================================================
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// 统计
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// ============================================================================
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export async function getAnchorStats() {
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const { chat } = getContext();
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if (!chat?.length) {
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return { extracted: 0, total: 0, pending: 0, empty: 0, fail: 0 };
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}
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// 统计 AI 楼层
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const aiFloors = [];
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for (let i = 0; i < chat.length; i++) {
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if (!chat[i]?.is_user) aiFloors.push(i);
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}
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let ok = 0;
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let empty = 0;
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let fail = 0;
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for (const f of aiFloors) {
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const s = getL0FloorStatus(f);
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if (!s) continue;
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if (s.status === 'ok') ok++;
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else if (s.status === 'empty') empty++;
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else if (s.status === 'fail') fail++;
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}
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const total = aiFloors.length;
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const processed = ok + empty + fail;
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const pending = Math.max(0, total - processed);
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return {
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extracted: ok + empty,
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total,
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pending,
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empty,
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fail
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};
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}
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// ============================================================================
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// 增量提取 - Phase 1 提取文本，Phase 2 统一向量化
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// ============================================================================
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function buildL0InputText(userMessage, aiMessage) {
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const parts = [];
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const userName = userMessage?.name || '用户';
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const aiName = aiMessage?.name || '角色';
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if (userMessage?.mes?.trim()) {
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parts.push(`【用户：${userName}】\n${filterText(userMessage.mes).trim()}`);
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}
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if (aiMessage?.mes?.trim()) {
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parts.push(`【角色：${aiName}】\n${filterText(aiMessage.mes).trim()}`);
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}
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return parts.join('\n\n---\n\n').trim();
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}
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function buildRAggregateText(atom) {
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const uniq = new Set();
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for (const edge of (atom?.edges || [])) {
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const r = String(edge?.r || '').trim();
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if (!r) continue;
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uniq.add(r);
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}
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const joined = [...uniq].join(' ; ');
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if (!joined) return String(atom?.semantic || '').trim();
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return joined.length > R_AGG_MAX_CHARS ? joined.slice(0, R_AGG_MAX_CHARS) : joined;
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}
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export async function incrementalExtractAtoms(chatId, chat, onProgress, options = {}) {
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const { maxFloors = Infinity } = options;
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if (!chatId || !chat?.length) return { built: 0 };
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const vectorCfg = getVectorConfig();
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if (!vectorCfg?.enabled) return { built: 0 };
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// ★ 重置取消标志
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extractionCancelled = false;
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const pendingPairs = [];
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for (let i = 0; i < chat.length; i++) {
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const msg = chat[i];
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if (!msg || msg.is_user) continue;
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const st = getL0FloorStatus(i);
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// ★ 只跳过 ok 和 empty，fail 的可以重试
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if (st?.status === 'ok' || st?.status === 'empty') {
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continue;
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}
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const userMsg = (i > 0 && chat[i - 1]?.is_user) ? chat[i - 1] : null;
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const inputText = buildL0InputText(userMsg, msg);
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if (!inputText) {
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setL0FloorStatus(i, { status: 'empty', reason: 'filtered_empty', atoms: 0 });
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continue;
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}
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pendingPairs.push({ userMsg, aiMsg: msg, aiFloor: i });
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}
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// 限制单次提取楼层数（自动触发时使用）
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if (pendingPairs.length > maxFloors) {
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pendingPairs.length = maxFloors;
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}
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if (!pendingPairs.length) {
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onProgress?.('已全部提取', 0, 0);
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return { built: 0 };
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}
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xbLog.info(MODULE_ID, `增量 L0 提取：pending=${pendingPairs.length}, concurrency=${CONCURRENCY}`);
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let completed = 0;
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let failed = 0;
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const total = pendingPairs.length;
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let builtAtoms = 0;
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let active = 0;
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let peakActive = 0;
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const tStart = performance.now();
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// ★ Phase 1: 收集所有新提取的 atoms（不向量化）
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const allNewAtoms = [];
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// ★ 限流检测：连续失败 N 次后暂停并降速
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let consecutiveFailures = 0;
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let rateLimited = false;
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const RATE_LIMIT_THRESHOLD = 6; // 连续失败多少次触发限流保护
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const RATE_LIMIT_WAIT_MS = 60000; // 限流后等待时间（60 秒）
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const RETRY_INTERVAL_MS = 1000; // 降速模式下每次请求间隔（1 秒）
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const RETRY_CONCURRENCY = 1; // ★ 降速模式下的并发数（默认1，建议不要超过5）
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// ★ 通用处理单个 pair 的逻辑（复用于正常模式和降速模式）
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const processPair = async (pair, idx, workerId) => {
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const floor = pair.aiFloor;
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const prev = getL0FloorStatus(floor);
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active++;
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if (active > peakActive) peakActive = active;
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if (DEBUG_CONCURRENCY && (idx % 10 === 0)) {
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xbLog.info(MODULE_ID, `L0 pool start idx=${idx} active=${active} peak=${peakActive} worker=${workerId}`);
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}
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try {
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const atoms = await extractAtomsForRound(pair.userMsg, pair.aiMsg, floor, { timeout: 40000 });
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if (extractionCancelled) return;
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if (atoms == null) {
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throw new Error('llm_failed');
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}
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// ★ 成功：重置连续失败计数
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consecutiveFailures = 0;
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if (!atoms.length) {
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setL0FloorStatus(floor, { status: 'empty', reason: 'llm_empty', atoms: 0 });
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} else {
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atoms.forEach(a => a.chatId = chatId);
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saveStateAtoms(atoms);
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allNewAtoms.push(...atoms);
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setL0FloorStatus(floor, { status: 'ok', atoms: atoms.length });
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builtAtoms += atoms.length;
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}
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} catch (e) {
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if (extractionCancelled) return;
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setL0FloorStatus(floor, {
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status: 'fail',
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attempts: (prev?.attempts || 0) + 1,
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reason: String(e?.message || e).replace(/\s+/g, ' ').slice(0, 120),
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});
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failed++;
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// ★ 限流检测：连续失败累加
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consecutiveFailures++;
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if (consecutiveFailures >= RATE_LIMIT_THRESHOLD && !rateLimited) {
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rateLimited = true;
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xbLog.warn(MODULE_ID, `连续失败 ${consecutiveFailures} 次，疑似触发 API 限流，将暂停所有并发`);
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}
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} finally {
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active--;
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if (!extractionCancelled) {
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completed++;
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onProgress?.(`提取: ${completed}/${total}`, completed, total);
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}
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if (DEBUG_CONCURRENCY && (completed % 25 === 0 || completed === total)) {
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const elapsed = Math.max(1, Math.round(performance.now() - tStart));
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xbLog.info(MODULE_ID, `L0 pool progress=${completed}/${total} active=${active} peak=${peakActive} elapsedMs=${elapsed}`);
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}
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}
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};
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// ★ 并发池处理（保持固定并发度）
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const poolSize = Math.min(CONCURRENCY, pendingPairs.length);
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let nextIndex = 0;
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let started = 0;
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const runWorker = async (workerId) => {
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while (true) {
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if (extractionCancelled || rateLimited) return;
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const idx = nextIndex++;
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if (idx >= pendingPairs.length) return;
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const pair = pendingPairs[idx];
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const stagger = started++;
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if (STAGGER_DELAY > 0) {
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await new Promise(r => setTimeout(r, stagger * STAGGER_DELAY));
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}
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if (extractionCancelled || rateLimited) return;
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await processPair(pair, idx, workerId);
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}
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};
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await Promise.all(Array.from({ length: poolSize }, (_, i) => runWorker(i)));
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if (DEBUG_CONCURRENCY) {
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const elapsed = Math.max(1, Math.round(performance.now() - tStart));
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xbLog.info(MODULE_ID, `L0 pool done completed=${completed}/${total} failed=${failed} peakActive=${peakActive} elapsedMs=${elapsed}`);
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}
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// ═════════════════════════════════════════════════════════════════════
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// ★ 限流恢复：重置进度，从头开始以限速模式慢慢跑
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// ═════════════════════════════════════════════════════════════════════
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if (rateLimited && !extractionCancelled) {
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const waitSec = RATE_LIMIT_WAIT_MS / 1000;
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xbLog.info(MODULE_ID, `限流保护：将重置进度并从头开始降速重来（并发=${RETRY_CONCURRENCY}, 间隔=${RETRY_INTERVAL_MS}ms）`);
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onProgress?.(`疑似限流，${waitSec}s 后降速重头开始...`, completed, total);
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await new Promise(r => setTimeout(r, RATE_LIMIT_WAIT_MS));
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if (!extractionCancelled) {
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// ★ 核心逻辑：重置计数器，让 UI 从 0 开始跑，给用户“重头开始”的反馈
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rateLimited = false;
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consecutiveFailures = 0;
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completed = 0;
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failed = 0;
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let retryNextIdx = 0;
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xbLog.info(MODULE_ID, `限流恢复：开始降速模式扫描 ${pendingPairs.length} 个楼层`);
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const retryWorkers = Math.min(RETRY_CONCURRENCY, pendingPairs.length);
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const runRetryWorker = async (wid) => {
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while (true) {
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if (extractionCancelled) return;
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const idx = retryNextIdx++;
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if (idx >= pendingPairs.length) return;
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const pair = pendingPairs[idx];
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const floor = pair.aiFloor;
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// ★ 检查该楼层状态
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const st = getL0FloorStatus(floor);
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if (st?.status === 'ok' || st?.status === 'empty') {
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// 刚才已经成功了，直接跳过（仅增加进度计数）
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completed++;
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onProgress?.(`提取: ${completed}/${total} (跳过已完成)`, completed, total);
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continue;
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}
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// ★ 没做过的，用 slow 模式处理
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await processPair(pair, idx, `retry-${wid}`);
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// 每个请求后休息，避免再次触发限流
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if (idx < pendingPairs.length - 1 && RETRY_INTERVAL_MS > 0) {
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await new Promise(r => setTimeout(r, RETRY_INTERVAL_MS));
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}
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}
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};
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await Promise.all(Array.from({ length: retryWorkers }, (_, i) => runRetryWorker(i)));
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xbLog.info(MODULE_ID, `降速重头开始阶段结束`);
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}
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}
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try {
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saveMetadataDebounced?.();
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} catch { }
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// ★ Phase 2: 统一向量化所有新提取的 atoms
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if (allNewAtoms.length > 0 && !extractionCancelled) {
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onProgress?.(`向量化 L0: 0/${allNewAtoms.length}`, 0, allNewAtoms.length);
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await vectorizeAtoms(chatId, allNewAtoms, (current, total) => {
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onProgress?.(`向量化 L0: ${current}/${total}`, current, total);
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});
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}
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xbLog.info(MODULE_ID, `L0 ${extractionCancelled ? '已取消' : '完成'}：atoms=${builtAtoms}, completed=${completed}/${total}, failed=${failed}`);
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return { built: builtAtoms };
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}
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// ============================================================================
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// 向量化（支持进度回调）
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// ============================================================================
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async function vectorizeAtoms(chatId, atoms, onProgress) {
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if (!atoms?.length) return;
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const vectorCfg = getVectorConfig();
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if (!vectorCfg?.enabled) return;
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const semanticTexts = atoms.map(a => a.semantic);
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const rTexts = atoms.map(a => buildRAggregateText(a));
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const fingerprint = getEngineFingerprint(vectorCfg);
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const batchSize = 20;
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try {
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const allVectors = [];
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for (let i = 0; i < semanticTexts.length; i += batchSize) {
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if (extractionCancelled) break;
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const semBatch = semanticTexts.slice(i, i + batchSize);
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const rBatch = rTexts.slice(i, i + batchSize);
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const payload = semBatch.concat(rBatch);
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const vectors = await embed(payload, { timeout: 30000 });
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const split = semBatch.length;
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if (!Array.isArray(vectors) || vectors.length < split * 2) {
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throw new Error(`embed length mismatch: expect>=${split * 2}, got=${vectors?.length || 0}`);
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}
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const semVectors = vectors.slice(0, split);
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const rVectors = vectors.slice(split, split + split);
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for (let j = 0; j < split; j++) {
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allVectors.push({
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vector: semVectors[j],
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rVector: rVectors[j] || semVectors[j],
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});
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}
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onProgress?.(allVectors.length, semanticTexts.length);
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}
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if (extractionCancelled) return;
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const items = atoms.slice(0, allVectors.length).map((a, i) => ({
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atomId: a.atomId,
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floor: a.floor,
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vector: allVectors[i].vector,
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rVector: allVectors[i].rVector,
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}));
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await saveStateVectors(chatId, items, fingerprint);
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xbLog.info(MODULE_ID, `L0 向量化完成: ${items.length} 条`);
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} catch (e) {
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xbLog.error(MODULE_ID, 'L0 向量化失败', e);
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}
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}
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// ============================================================================
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// 清空
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// ============================================================================
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export async function clearAllAtomsAndVectors(chatId) {
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clearStateAtoms();
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clearL0Index();
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if (chatId) {
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await clearStateVectors(chatId);
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}
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// ★ 立即保存
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try {
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saveMetadataDebounced?.();
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} catch { }
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xbLog.info(MODULE_ID, '已清空所有记忆锚点');
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}
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// ============================================================================
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// 实时增量（AI 消息后触发）- 保持不变
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// ============================================================================
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let extractionQueue = [];
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let isProcessing = false;
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export async function extractAndStoreAtomsForRound(aiFloor, aiMessage, userMessage, onComplete) {
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const { chatId } = getContext();
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if (!chatId) return;
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const vectorCfg = getVectorConfig();
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if (!vectorCfg?.enabled) return;
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extractionQueue.push({ aiFloor, aiMessage, userMessage, chatId, onComplete });
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processQueue();
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}
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async function processQueue() {
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if (isProcessing || extractionQueue.length === 0) return;
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isProcessing = true;
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while (extractionQueue.length > 0) {
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const { aiFloor, aiMessage, userMessage, chatId, onComplete } = extractionQueue.shift();
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try {
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const atoms = await extractAtomsForRound(userMessage, aiMessage, aiFloor, { timeout: 12000 });
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if (!atoms?.length) {
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xbLog.info(MODULE_ID, `floor ${aiFloor}: 无有效 atoms`);
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onComplete?.({ floor: aiFloor, atomCount: 0 });
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continue;
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}
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atoms.forEach(a => a.chatId = chatId);
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saveStateAtoms(atoms);
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// 单楼实时处理：立即向量化
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await vectorizeAtomsSimple(chatId, atoms);
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xbLog.info(MODULE_ID, `floor ${aiFloor}: ${atoms.length} atoms 已存储`);
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onComplete?.({ floor: aiFloor, atomCount: atoms.length });
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} catch (e) {
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xbLog.error(MODULE_ID, `floor ${aiFloor} 处理失败`, e);
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onComplete?.({ floor: aiFloor, atomCount: 0, error: e });
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}
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}
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isProcessing = false;
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||
}
|
||
|
||
// 简单向量化（无进度回调，用于单楼实时处理）
|
||
async function vectorizeAtomsSimple(chatId, atoms) {
|
||
if (!atoms?.length) return;
|
||
|
||
const vectorCfg = getVectorConfig();
|
||
if (!vectorCfg?.enabled) return;
|
||
|
||
const semanticTexts = atoms.map(a => a.semantic);
|
||
const rTexts = atoms.map(a => buildRAggregateText(a));
|
||
const fingerprint = getEngineFingerprint(vectorCfg);
|
||
|
||
try {
|
||
const vectors = await embed(semanticTexts.concat(rTexts), { timeout: 30000 });
|
||
const split = semanticTexts.length;
|
||
if (!Array.isArray(vectors) || vectors.length < split * 2) {
|
||
throw new Error(`embed length mismatch: expect>=${split * 2}, got=${vectors?.length || 0}`);
|
||
}
|
||
const semVectors = vectors.slice(0, split);
|
||
const rVectors = vectors.slice(split, split + split);
|
||
|
||
const items = atoms.map((a, i) => ({
|
||
atomId: a.atomId,
|
||
floor: a.floor,
|
||
vector: semVectors[i],
|
||
rVector: rVectors[i] || semVectors[i],
|
||
}));
|
||
|
||
await saveStateVectors(chatId, items, fingerprint);
|
||
} catch (e) {
|
||
xbLog.error(MODULE_ID, 'L0 向量化失败', e);
|
||
}
|
||
}
|
||
|
||
// ============================================================================
|
||
// 回滚钩子
|
||
// ============================================================================
|
||
|
||
async function handleStateRollback(floor) {
|
||
xbLog.info(MODULE_ID, `收到回滚请求: floor >= ${floor}`);
|
||
|
||
const { chatId } = getContext();
|
||
|
||
deleteStateAtomsFromFloor(floor);
|
||
deleteL0IndexFromFloor(floor);
|
||
|
||
if (chatId) {
|
||
await deleteStateVectorsFromFloor(chatId, floor);
|
||
}
|
||
}
|
||
|
||
// ============================================================================
|
||
// 兼容旧接口
|
||
// ============================================================================
|
||
|
||
export async function batchExtractAndStoreAtoms(chatId, chat, onProgress) {
|
||
if (!chatId || !chat?.length) return { built: 0 };
|
||
|
||
const vectorCfg = getVectorConfig();
|
||
if (!vectorCfg?.enabled) return { built: 0 };
|
||
|
||
xbLog.info(MODULE_ID, `开始批量 L0 提取: ${chat.length} 条消息`);
|
||
|
||
clearStateAtoms();
|
||
clearL0Index();
|
||
await clearStateVectors(chatId);
|
||
|
||
return await incrementalExtractAtoms(chatId, chat, onProgress);
|
||
}
|
||
|
||
export async function rebuildStateVectors(chatId, vectorCfg) {
|
||
if (!chatId || !vectorCfg?.enabled) return { built: 0 };
|
||
|
||
const atoms = getStateAtoms();
|
||
if (!atoms.length) return { built: 0 };
|
||
|
||
xbLog.info(MODULE_ID, `重建 L0 向量: ${atoms.length} 条 atom`);
|
||
|
||
await clearStateVectors(chatId);
|
||
await vectorizeAtomsSimple(chatId, atoms);
|
||
|
||
return { built: atoms.length };
|
||
}
|