Add Experience V1 schema migration and agent-run completion extractor.
Extend h5_experience with structured fields, wire mindspace-agent-runner and agent-run-gateway to persist task_outcome records with provenance, and add local migration and verification scripts. Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
john
+91
-47
@@ -1,5 +1,12 @@
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import crypto from 'node:crypto';
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import {
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experienceSearchHaystack,
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mapExperienceRow,
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normalizeExperienceRecordInput,
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serializeExperienceJson,
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} from './experience-schema.mjs';
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/**
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* PostgreSQL + pgvector backed experience store (etat C, polyglot mode).
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*
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@@ -51,10 +58,35 @@ export async function createPgExperienceService(options = {}) {
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source_user_id TEXT,
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use_count BIGINT NOT NULL DEFAULT 0,
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embedding vector(${embeddingDim}),
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problem TEXT,
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environment_json JSONB,
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hypothesis TEXT,
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action_json JSONB,
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result TEXT,
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confidence DOUBLE PRECISION,
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evidence_json JSONB,
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parent_experience_id UUID,
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supersedes_id UUID,
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status TEXT NOT NULL DEFAULT 'active',
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created_at BIGINT NOT NULL,
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updated_at BIGINT NOT NULL
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)
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`);
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const pgExperienceColumns = [
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['problem', 'TEXT'],
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['environment_json', 'JSONB'],
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['hypothesis', 'TEXT'],
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['action_json', 'JSONB'],
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['result', 'TEXT'],
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['confidence', 'DOUBLE PRECISION'],
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['evidence_json', 'JSONB'],
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['parent_experience_id', 'UUID'],
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['supersedes_id', 'UUID'],
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["status", "TEXT NOT NULL DEFAULT 'active'"],
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];
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for (const [column, definition] of pgExperienceColumns) {
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await pool.query(`ALTER TABLE h5_experience ADD COLUMN IF NOT EXISTS ${column} ${definition}`);
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}
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await pool.query(
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'CREATE INDEX IF NOT EXISTS idx_h5_experience_scope_updated ON h5_experience (scope, updated_at DESC)',
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);
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@@ -66,80 +98,88 @@ export async function createPgExperienceService(options = {}) {
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// ivfflat needs the extension + may warn on empty table; non-fatal.
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});
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function normalizeTags(tags) {
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if (!Array.isArray(tags)) return [];
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return [...new Set(tags.map((t) => String(t).trim()).filter(Boolean))];
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}
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function toVectorLiteral(vec) {
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// pgvector accepts a string like '[0.1,0.2,...]'
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return `[${vec.map((n) => Number(n)).join(',')}]`;
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}
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function rowToExperience(row) {
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return {
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id: row.id,
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scope: row.scope,
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kind: row.kind,
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title: row.title,
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body: row.body,
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tags: Array.isArray(row.tags) ? row.tags : [],
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sourceSessionId: row.source_session_id ?? null,
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sourceUserId: row.source_user_id ?? null,
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useCount: Number(row.use_count ?? 0),
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createdAt: Number(row.created_at),
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updatedAt: Number(row.updated_at),
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};
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return mapExperienceRow({
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...row,
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tags_json: row.tags,
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});
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}
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async function record(input) {
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const title = String(input?.title ?? '').trim();
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const body = String(input?.body ?? '').trim();
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if (!title) throw experienceError('经验标题不能为空', 'invalid_experience_input');
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if (!body) throw experienceError('经验内容不能为空', 'invalid_experience_input');
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const normalized = normalizeExperienceRecordInput(input);
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if (!normalized.title) throw experienceError('经验标题不能为空', 'invalid_experience_input');
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if (!normalized.body) throw experienceError('经验内容不能为空', 'invalid_experience_input');
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const id = crypto.randomUUID();
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const ts = now();
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const scope = String(input?.scope ?? 'global').trim() || 'global';
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const kind = String(input?.kind ?? 'lesson').trim() || 'lesson';
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const tags = normalizeTags(input?.tags);
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const environmentJson = normalized.environment;
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const actionJson = normalized.action;
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const evidenceJson = normalized.evidence;
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let embedding = null;
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if (embed) {
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try {
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const vec = await embed(`${title}\n${body}`);
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const vec = await embed(`${normalized.title}\n${normalized.body}`);
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if (Array.isArray(vec) && vec.length === embeddingDim) embedding = toVectorLiteral(vec);
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} catch {
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embedding = null; // embedding failure must not block recording
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embedding = null;
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}
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}
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await pool.query(
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`INSERT INTO h5_experience
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(id, scope, kind, title, body, tags, source_session_id, source_user_id,
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use_count, embedding, created_at, updated_at)
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VALUES ($1,$2,$3,$4,$5,$6::jsonb,$7,$8,0,$9::vector,$10,$11)`,
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use_count, embedding, problem, environment_json, hypothesis, action_json,
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result, confidence, evidence_json, parent_experience_id, supersedes_id,
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status, created_at, updated_at)
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VALUES ($1,$2,$3,$4,$5,$6::jsonb,$7,$8,0,$9::vector,$10,$11::jsonb,$12,$13::jsonb,
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$14,$15,$16::jsonb,$17::uuid,$18::uuid,$19,$20,$21)`,
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[
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id,
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scope,
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kind,
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title,
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body,
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JSON.stringify(tags),
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input?.sourceSessionId ?? null,
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input?.sourceUserId ?? null,
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normalized.scope,
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normalized.kind,
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normalized.title,
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normalized.body,
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JSON.stringify(normalized.tags),
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normalized.sourceSessionId,
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normalized.sourceUserId,
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embedding,
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normalized.problem,
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environmentJson == null ? null : JSON.stringify(environmentJson),
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normalized.hypothesis,
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actionJson == null ? null : JSON.stringify(actionJson),
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normalized.result,
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normalized.confidence,
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evidenceJson == null ? null : JSON.stringify(evidenceJson),
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normalized.parentExperienceId,
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normalized.supersedesId,
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normalized.status,
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ts,
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ts,
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],
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);
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return rowToExperience({
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id,
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scope,
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kind,
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title,
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body,
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tags,
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source_session_id: input?.sourceSessionId ?? null,
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source_user_id: input?.sourceUserId ?? null,
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scope: normalized.scope,
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kind: normalized.kind,
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title: normalized.title,
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body: normalized.body,
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tags: normalized.tags,
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source_session_id: normalized.sourceSessionId,
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source_user_id: normalized.sourceUserId,
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use_count: 0,
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problem: normalized.problem,
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environment_json: environmentJson,
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hypothesis: normalized.hypothesis,
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action_json: actionJson,
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result: normalized.result,
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confidence: normalized.confidence,
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evidence_json: evidenceJson,
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parent_experience_id: normalized.parentExperienceId,
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supersedes_id: normalized.supersedesId,
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status: normalized.status,
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created_at: ts,
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updated_at: ts,
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});
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@@ -157,9 +197,11 @@ export async function createPgExperienceService(options = {}) {
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if (Array.isArray(vec) && vec.length === embeddingDim) {
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const { rows } = await pool.query(
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`SELECT id, scope, kind, title, body, tags, source_session_id,
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source_user_id, use_count, created_at, updated_at
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source_user_id, use_count, problem, environment_json, hypothesis,
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action_json, result, confidence, evidence_json, parent_experience_id,
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supersedes_id, status, created_at, updated_at
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FROM h5_experience
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WHERE scope = $1 AND embedding IS NOT NULL
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WHERE scope = $1 AND status = 'active' AND embedding IS NOT NULL
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ORDER BY embedding <=> $2::vector, updated_at DESC
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LIMIT $3`,
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[scope, toVectorLiteral(vec), max],
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@@ -181,9 +223,11 @@ export async function createPgExperienceService(options = {}) {
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const params = [scope, ...terms.map((t) => `%${t}%`), max];
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const { rows } = await pool.query(
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`SELECT id, scope, kind, title, body, tags, source_session_id,
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source_user_id, use_count, created_at, updated_at
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source_user_id, use_count, problem, environment_json, hypothesis,
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action_json, result, confidence, evidence_json, parent_experience_id,
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supersedes_id, status, created_at, updated_at
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FROM h5_experience
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WHERE scope = $1 AND (${likeClauses.join(' OR ')})
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WHERE scope = $1 AND status = 'active' AND (${likeClauses.join(' OR ')})
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ORDER BY updated_at DESC
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LIMIT $${terms.length + 2}`,
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params,
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