217 lines
6.9 KiB
JavaScript
217 lines
6.9 KiB
JavaScript
const DEFAULT_LIMIT = 100;
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const DEFAULT_TABLE = 'memory_embeddings';
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const MAX_LIMIT = 1000;
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function isSafeIdentifier(value) {
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return /^[a-zA-Z_][a-zA-Z0-9_]*$/.test(String(value ?? ''));
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}
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function quoteIdent(value) {
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const normalized = String(value ?? '').trim();
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if (!isSafeIdentifier(normalized)) {
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throw new Error(`Invalid PostgreSQL identifier: ${normalized}`);
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}
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return `"${normalized}"`;
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}
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function normalizeLimit(value) {
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return Math.max(1, Math.min(MAX_LIMIT, Number(value ?? DEFAULT_LIMIT) || DEFAULT_LIMIT));
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}
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function normalizeCursor(cursor = {}) {
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return {
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updatedAt: Number(cursor.updatedAt ?? 0) || 0,
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id: String(cursor.id ?? ''),
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};
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}
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function toPgTimestamp(value) {
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const numeric = Number(value ?? 0);
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if (!Number.isFinite(numeric) || numeric <= 0) return new Date(0);
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return new Date(numeric);
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}
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function vectorLiteral(embedding) {
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return `[${embedding.map((item) => Number(item)).join(',')}]`;
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}
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function normalizeEmbedding(value) {
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if (!Array.isArray(value)) return null;
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const numbers = value.map((item) => Number(item));
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if (!numbers.length || numbers.some((item) => !Number.isFinite(item))) return null;
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return numbers;
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}
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function normalizeLegacyMemory(row) {
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const id = String(row?.id ?? '').trim();
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const userId = String(row?.user_id ?? '').trim();
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const text = String(row?.memory_text ?? '').trim();
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if (!id || !userId || !text) return null;
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return {
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id,
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userId,
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label: String(row?.label ?? 'fact').trim() || 'fact',
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text,
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evidenceMessageId: row?.evidence_message_id == null ? null : String(row.evidence_message_id),
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sourceSessionId: row?.source_session_id == null ? null : String(row.source_session_id),
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confidence: row?.confidence == null ? null : Number(row.confidence),
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createdAt: Number(row?.created_at ?? 0) || 0,
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updatedAt: Number(row?.updated_at ?? 0) || 0,
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};
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}
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async function upsertLegacyMemories({ memories, pgPool, embedMemory, tableName }) {
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if (!pgPool?.query) {
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throw new Error('pgvector sync requires a PostgreSQL pool with query(sql, params)');
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}
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if (typeof embedMemory !== 'function') {
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throw new Error('pgvector sync requires embedMemory(memory) => number[]');
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}
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const table = quoteIdent(tableName);
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let inserted = 0;
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for (const memory of memories) {
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const embedding = normalizeEmbedding(await embedMemory(memory));
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if (!embedding) continue;
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await pgPool.query(
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`INSERT INTO ${table}
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(user_id, content, embedding, type, source_memory_id, source_session_id,
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source_message_id, metadata, created_at, updated_at)
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VALUES ($1, $2, $3::vector, $4, $5, $6, $7, $8::jsonb, $9, $10)
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ON CONFLICT (source_memory_id) WHERE source_memory_id IS NOT NULL
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DO UPDATE SET
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content = EXCLUDED.content,
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embedding = EXCLUDED.embedding,
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type = EXCLUDED.type,
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source_session_id = EXCLUDED.source_session_id,
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source_message_id = EXCLUDED.source_message_id,
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metadata = EXCLUDED.metadata,
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updated_at = EXCLUDED.updated_at`,
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[
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memory.userId,
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memory.text,
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vectorLiteral(embedding),
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memory.label,
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memory.id,
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memory.sourceSessionId,
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memory.evidenceMessageId,
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JSON.stringify({ confidence: memory.confidence }),
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toPgTimestamp(memory.createdAt),
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toPgTimestamp(memory.updatedAt),
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],
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);
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inserted += 1;
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}
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return inserted;
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}
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export async function loadLegacyMemoryBackfillBatch(mysqlPool, { cursor = {}, limit = DEFAULT_LIMIT } = {}) {
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if (!mysqlPool?.query) {
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throw new Error('loadLegacyMemoryBackfillBatch requires a MySQL pool with query(sql, params)');
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}
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const resolvedCursor = normalizeCursor(cursor);
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const resolvedLimit = normalizeLimit(limit);
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const [rows] = await mysqlPool.query(
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`SELECT id, user_id, label, memory_text, evidence_message_id, source_session_id,
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confidence, created_at, updated_at
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FROM h5_user_memory_items
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WHERE status = 'active'
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AND (updated_at > ? OR (updated_at = ? AND id > ?))
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ORDER BY updated_at ASC, id ASC
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LIMIT ?`,
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[resolvedCursor.updatedAt, resolvedCursor.updatedAt, resolvedCursor.id, resolvedLimit],
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);
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const memories = (rows ?? []).map((row) => normalizeLegacyMemory(row)).filter(Boolean);
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const last = memories.at(-1);
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return {
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memories,
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nextCursor: last ? { updatedAt: last.updatedAt, id: last.id } : resolvedCursor,
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hasMore: memories.length === resolvedLimit,
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};
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}
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export async function loadLegacyUserMemorySyncBatch(
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mysqlPool,
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{ userId, sessionId = null, limit = DEFAULT_LIMIT } = {},
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) {
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if (!mysqlPool?.query) {
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throw new Error('loadLegacyUserMemorySyncBatch requires a MySQL pool with query(sql, params)');
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}
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const resolvedUserId = String(userId ?? '').trim();
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if (!resolvedUserId) throw new Error('loadLegacyUserMemorySyncBatch requires userId');
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const resolvedSessionId = String(sessionId ?? '').trim();
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const resolvedLimit = normalizeLimit(limit);
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const sessionScope = resolvedSessionId ? ' AND source_session_id = ?' : '';
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const params = resolvedSessionId
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? [resolvedUserId, resolvedSessionId, resolvedLimit]
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: [resolvedUserId, resolvedLimit];
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const [rows] = await mysqlPool.query(
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`SELECT id, user_id, label, memory_text, evidence_message_id, source_session_id,
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confidence, created_at, updated_at
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FROM h5_user_memory_items
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WHERE status = 'active'
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AND user_id = ?${sessionScope}
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ORDER BY updated_at DESC, id DESC
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LIMIT ?`,
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params,
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);
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return (rows ?? []).map((row) => normalizeLegacyMemory(row)).filter(Boolean);
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}
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export async function syncLegacyUserMemoriesToPgvector({
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mysqlPool,
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pgPool,
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embedMemory,
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tableName = DEFAULT_TABLE,
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userId,
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sessionId = null,
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limit = DEFAULT_LIMIT,
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} = {}) {
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const memories = await loadLegacyUserMemorySyncBatch(mysqlPool, { userId, sessionId, limit });
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const inserted = await upsertLegacyMemories({ memories, pgPool, embedMemory, tableName });
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return {
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ok: true,
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mode: 'user-sync',
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scanned: memories.length,
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inserted,
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userId: String(userId),
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sessionId: sessionId == null ? null : String(sessionId),
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};
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}
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export async function backfillLegacyMemoriesToPgvector({
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mysqlPool,
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pgPool = null,
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embedMemory = null,
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tableName = DEFAULT_TABLE,
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cursor = {},
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limit = DEFAULT_LIMIT,
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dryRun = true,
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} = {}) {
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const batch = await loadLegacyMemoryBackfillBatch(mysqlPool, { cursor, limit });
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if (dryRun) {
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return {
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ok: true,
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mode: 'dry-run',
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scanned: batch.memories.length,
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inserted: 0,
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nextCursor: batch.nextCursor,
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hasMore: batch.hasMore,
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};
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}
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const inserted = await upsertLegacyMemories({
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memories: batch.memories,
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pgPool,
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embedMemory,
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tableName,
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});
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return {
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ok: true,
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mode: 'apply',
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scanned: batch.memories.length,
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inserted,
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nextCursor: batch.nextCursor,
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hasMore: batch.hasMore,
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};
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}
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