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https://github.com/garrytan/gbrain.git
synced 2026-08-17 02:12:40 +00:00
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3
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
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52fffc7ecc | ||
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039b97df36 | ||
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2bb3424863 |
+12
-1
@@ -54,7 +54,7 @@ export function bigintToStringReplacer(_key: string, value: unknown): unknown {
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}
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// CLI-only commands that bypass the operation layer
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export const CLI_ONLY = new Set(['init', 'reinit-pglite', 'upgrade', 'post-upgrade', 'check-update', 'integrations', 'publish', 'check-backlinks', 'lint', 'report', 'import', 'export', 'files', 'embed', 'serve', 'call', 'config', 'doctor', 'migrate', 'eval', 'sync', 'extract', 'extract-conversation-facts', 'enrich', 'features', 'autopilot', 'graph-query', 'jobs', 'agent', 'apply-migrations', 'skillpack-check', 'skillpack', 'resolvers', 'integrity', 'repair-jsonb', 'orphans', 'sources', 'mounts', 'dream', 'check-resolvable', 'routing-eval', 'skillify', 'smoke-test', 'providers', 'storage', 'repos', 'code-def', 'code-refs', 'reindex', 'reindex-code', 'reindex-frontmatter', 'code-callers', 'code-callees', 'reconcile-links', 'frontmatter', 'auth', 'friction', 'claw-test', 'book-mirror', 'takes', 'think', 'salience', 'anomalies', 'calibration', 'transcripts', 'models', 'remote', 'recall', 'forget', 'edges-backfill', 'cache', 'ze-switch', 'founder', 'brainstorm', 'lsd', 'schema', 'capture', 'onboard', 'conversation-parser', 'status', 'connect', 'skillopt', 'quarantine', 'self-upgrade', 'advisor', 'watch', 'reindex-search-vector']);
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export const CLI_ONLY = new Set(['init', 'reinit-pglite', 'upgrade', 'post-upgrade', 'check-update', 'integrations', 'publish', 'check-backlinks', 'lint', 'report', 'import', 'export', 'files', 'embed', 'serve', 'call', 'config', 'doctor', 'migrate', 'eval', 'sync', 'extract', 'extract-conversation-facts', 'enrich', 'features', 'autopilot', 'graph-query', 'jobs', 'agent', 'apply-migrations', 'skillpack-check', 'skillpack', 'resolvers', 'integrity', 'repair-jsonb', 'orphans', 'sources', 'mounts', 'dream', 'check-resolvable', 'routing-eval', 'skillify', 'smoke-test', 'providers', 'storage', 'repos', 'code-def', 'code-refs', 'reindex', 'reindex-code', 'reindex-frontmatter', 'code-callers', 'code-callees', 'reconcile-links', 'frontmatter', 'auth', 'friction', 'claw-test', 'book-mirror', 'takes', 'think', 'salience', 'anomalies', 'calibration', 'transcripts', 'models', 'remote', 'recall', 'forget', 'edges-backfill', 'facts', 'cache', 'ze-switch', 'founder', 'brainstorm', 'lsd', 'schema', 'capture', 'onboard', 'conversation-parser', 'status', 'connect', 'skillopt', 'quarantine', 'self-upgrade', 'advisor', 'watch', 'reindex-search-vector']);
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// CLI-only commands whose handlers print their own --help text. These are
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// excluded from the generic short-circuit so detailed per-command and
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// per-subcommand usage stays reachable.
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@@ -991,6 +991,8 @@ const THIN_CLIENT_REFUSED_COMMANDS = new Set([
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// hint pointing at the routable MCP tools; per-subcommand splits are
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// a v0.31.x follow-up TODO.
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'takes', 'sources',
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// #1867: fence-backfill edits local .md fences + stamps the local DB.
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'facts',
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// v0.32 thin-client routing audit (Codex round 2 findings #2, #4):
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// - `pages` purge-deleted is admin+localOnly (operations.ts:856-864)
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// - `files` list / file_url MCP ops are localOnly (operations.ts:1769-1879)
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@@ -1026,6 +1028,7 @@ const THIN_CLIENT_REFUSE_HINTS: Record<string, string> = {
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migrate: "migrate runs on the host's local engine. Run on the host machine.",
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'apply-migrations': 'schema migrations run on the host. SSH and run there.',
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'repair-jsonb': 'repair-jsonb operates on the local DB only.',
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facts: 'facts fence-backfill edits local entity-page fences. Run on the host machine.',
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integrity: 'integrity scans local files. Run on the host machine.',
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serve: 'serve starts a server. Run on the host, not the thin client.',
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dream: 'dream runs the autopilot cycle on the host. `gbrain remote ping` queues one. (Native `gbrain dream` thin-client routing planned for v0.31.2.)',
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@@ -1855,6 +1858,13 @@ async function handleCliOnly(command: string, args: string[]) {
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await runEdgesBackfill(engine, args);
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break;
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}
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case 'facts': {
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// #1867 — re-runnable fence-backfill for row_num-NULL legacy fact
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// rows (idempotent v0_32_2 phase B, exposed as an operator command).
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const { runFactsCommand } = await import('./commands/facts.ts');
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await runFactsCommand(engine, args);
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break;
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}
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case 'whoknows': {
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// v0.33 (Issue #?): expertise + relationship-proximity routing.
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// MCP op `find_experts` (read-scoped) backs the same code path; CLI
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@@ -2335,6 +2345,7 @@ TOOLS
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check-backlinks <check|fix> [dir] Find/fix missing back-links across brain
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lint <dir|file> [--fix] Catch LLM artifacts, placeholder dates, bad frontmatter
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orphans [--json] [--count] Find pages with no inbound wikilinks
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facts fence-backfill [--dry-run] Fence legacy fact rows (row_num NULL) onto entity pages
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salience [--days N] [--kind P] v0.29: pages ranked by emotional + activity salience
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anomalies [--since D] [--sigma N] v0.29: cohort-based statistical anomalies (tag, type)
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transcripts recent [--days N] v0.29: recent raw .txt transcripts (local-only)
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+1
-14
@@ -1,5 +1,5 @@
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import type { BrainEngine } from '../core/engine.ts';
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import { embedBatch, currentEmbeddingSignature, resolveEmbeddingModelLabel } from '../core/embedding.ts';
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import { embedBatch, currentEmbeddingSignature } from '../core/embedding.ts';
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import type { ChunkInput } from '../core/types.ts';
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import { chunkText } from '../core/chunkers/recursive.ts';
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import { createProgress, type ProgressReporter } from '../core/progress.ts';
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@@ -581,16 +581,11 @@ async function embedPage(
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for (let j = 0; j < toEmbed.length; j++) {
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embeddingMap.set(toEmbed[j].chunk_index, embeddings[j]);
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}
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// #1717: label each (re)embedded chunk with the model that actually
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// produced its vector. Preserved chunks (not re-embedded this pass) keep
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// their existing model so a mixed-model page isn't relabeled wholesale.
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const embedModelLabel = resolveEmbeddingModelLabel();
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const updated: ChunkInput[] = chunks.map(c => ({
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chunk_index: c.chunk_index,
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chunk_text: c.chunk_text,
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chunk_source: c.chunk_source,
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embedding: embeddingMap.get(c.chunk_index),
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model: embeddingMap.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
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token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
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}));
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@@ -722,16 +717,12 @@ async function embedAll(
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for (let j = 0; j < toEmbed.length; j++) {
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embeddingMap.set(toEmbed[j].chunk_index, embeddings[j]);
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}
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// #1717: stamp the resolved embedding model on (re)embedded chunks;
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// preserve the existing model on chunks left untouched.
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const embedModelLabel = resolveEmbeddingModelLabel();
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// Preserve ALL chunks, only update embeddings for stale ones
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const updated: ChunkInput[] = chunks.map(c => ({
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chunk_index: c.chunk_index,
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chunk_text: c.chunk_text,
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chunk_source: c.chunk_source,
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embedding: embeddingMap.get(c.chunk_index) ?? undefined,
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model: embeddingMap.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
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token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
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}));
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await observed(pacer, () => engine.upsertChunks(page.slug, updated, pageOpts));
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@@ -1021,15 +1012,11 @@ async function embedAllStale(
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for (let j = 0; j < stale.length; j++) {
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staleIdxToEmbedding.set(stale[j].chunk_index, embeddings[j]);
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}
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// #1717: label the re-embedded (stale) chunks with the resolved
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// model; preserve the existing model on the non-stale chunks.
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const embedModelLabel = resolveEmbeddingModelLabel();
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const merged: ChunkInput[] = existing.map(c => ({
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chunk_index: c.chunk_index,
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chunk_text: c.chunk_text,
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chunk_source: c.chunk_source,
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embedding: staleIdxToEmbedding.get(c.chunk_index) ?? undefined,
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model: staleIdxToEmbedding.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
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token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
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}));
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await observed(pacer, () => engine.upsertChunks(slug, merged, { sourceId: keySourceId }));
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@@ -0,0 +1,48 @@
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/**
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* gbrain facts — fact-store maintenance surface (#1867).
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*
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* `fence-backfill` re-runs the v0_32_2 fence-backfill phase on demand.
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* Remote `extract_facts` deposits that predate the fence-write backstop
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* (and any legacy DB-only insert) leave `row_num IS NULL` rows that the
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* cycle extract_facts guard refuses to reconcile past — previously the
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* only remedy was the one-shot v0_32_2 migration, which the ledger marks
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* complete and never re-runs. The phase is idempotent (only touches
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* `row_num IS NULL` rows), so exposing it as a command is safe to re-run
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* any time the backlog reappears.
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*/
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import type { BrainEngine } from '../core/engine.ts';
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import { setCliExitVerdict } from '../core/cli-force-exit.ts';
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import { phaseBFenceFacts } from './migrations/v0_32_2.ts';
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function printHelp(): void {
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process.stderr.write(
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`Usage: gbrain facts fence-backfill [--dry-run]\n\n` +
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`Fence-backfill: appends every legacy fact row (row_num IS NULL) to its\n` +
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`entity page's \`## Facts\` fence and stamps row_num + source_markdown_slug\n` +
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`back onto the DB row. Idempotent — re-runs only pick up rows still\n` +
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`missing a fence assignment. Clears the backlog that makes the cycle's\n` +
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`extract_facts phase skip fence→DB reconciliation.\n\n` +
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` --dry-run report what would be fenced; no FS or DB writes\n`,
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);
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}
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export async function runFactsCommand(engine: BrainEngine, args: string[]): Promise<void> {
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const sub = args[0];
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if (!sub || sub === '--help' || sub === '-h') {
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printHelp();
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return;
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}
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if (sub !== 'fence-backfill') {
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process.stderr.write(`Unknown facts subcommand: ${sub}\n`);
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printHelp();
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setCliExitVerdict(1);
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return;
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}
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const dryRun = args.includes('--dry-run');
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const result = await phaseBFenceFacts(engine, { dryRun });
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process.stderr.write(
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`fence-backfill: ${result.status}${result.detail ? ` — ${result.detail}` : ''}\n`,
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);
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if (result.status === 'failed') setCliExitVerdict(1);
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}
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@@ -39,6 +39,7 @@ import type { BrainEngine } from '../../core/engine.ts';
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import { loadConfig, toEngineConfig } from '../../core/config.ts';
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import { createEngine } from '../../core/engine-factory.ts';
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import { upsertFactRow, parseFactsFence } from '../../core/facts-fence.ts';
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import { resolvePageFilePath } from '../../core/markdown.ts';
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let testEngineOverride: BrainEngine | null = null;
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export function __setTestEngineOverride(engine: BrainEngine | null): void {
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@@ -148,9 +149,16 @@ function isLocalPathDirty(localPath: string): boolean {
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}
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}
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async function phaseBFenceFacts(
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/**
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* Exported (not just via `__testing`) because `gbrain facts fence-backfill`
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* (#1867) re-runs this phase on demand: remote `extract_facts` deposits that
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* predate the fence-write backstop leave row_num-NULL rows the cycle guard
|
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* refuses to reconcile past. The phase is idempotent (only touches
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* `row_num IS NULL` rows), so re-running is always safe.
|
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*/
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export async function phaseBFenceFacts(
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engine: BrainEngine | null,
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opts: OrchestratorOpts,
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opts: Pick<OrchestratorOpts, 'dryRun'>,
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): Promise<OrchestratorPhaseResult> {
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if (opts.dryRun) {
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// Dry-run: report what WOULD happen without touching FS or DB.
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@@ -238,7 +246,11 @@ async function phaseBFenceFacts(
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for (const [key, group] of groups) {
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const [sourceId, entitySlug] = key.split('\0');
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const localPath = localPathById.get(sourceId)!;
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const filePath = join(localPath, `${entitySlug}.md`);
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// resolvePageFilePath, NOT a bare join — non-default sources fence
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// into `<local_path>/.sources/<id>/<slug>.md`, the same path the
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// fence-write backstop and put_page write-through compute. A bare
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// join here diverges fence and DB for non-default sources (#2044).
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const filePath = resolvePageFilePath(localPath, entitySlug, sourceId);
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const tmpPath = `${filePath}.tmp`;
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|
||||
try {
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@@ -269,6 +281,21 @@ async function phaseBFenceFacts(
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const existingFence = parseFactsFence(body);
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const existingKeySet = new Set(existingFence.facts.map(f => `${f.claim}\0${f.source ?? ''}`));
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|
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// Seed appended row_nums from MAX(fence max, DB max) — same #2044
|
||||
// divergence guard as writeFactsToFence. When the fence at the
|
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// resolved path is missing/behind but the DB already holds stamped
|
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// rows for this slug (legacy wrong-path fence writes), fence-max+1
|
||||
// collides with idx_facts_fence_key on the post-rename UPDATE,
|
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// failing the page and leaving fence and DB disagreeing.
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const dbMaxRows = await engine.executeRaw<{ max: number | string | null }>(
|
||||
`SELECT MAX(row_num) AS max FROM facts
|
||||
WHERE source_id = $1 AND source_markdown_slug = $2`,
|
||||
[sourceId, entitySlug],
|
||||
);
|
||||
const dbMaxRowNum = Number(dbMaxRows[0]?.max ?? 0) || 0;
|
||||
const fenceMaxRowNum = existingFence.facts.reduce((m, f) => Math.max(m, f.rowNum), 0);
|
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let nextRowNum = Math.max(fenceMaxRowNum, dbMaxRowNum) + 1;
|
||||
|
||||
const assignments: Array<{ id: string; row_num: number }> = [];
|
||||
for (const row of group) {
|
||||
const key = `${row.fact}\0${row.source ?? ''}`;
|
||||
@@ -291,6 +318,7 @@ async function phaseBFenceFacts(
|
||||
.toISOString().slice(0, 10)
|
||||
: undefined;
|
||||
const { body: updated, rowNum } = upsertFactRow(body, {
|
||||
rowNum: nextRowNum++,
|
||||
claim: row.fact,
|
||||
kind: row.kind,
|
||||
confidence: row.confidence,
|
||||
@@ -381,7 +409,7 @@ async function phaseCVerify(
|
||||
for (const g of groups) {
|
||||
const localPath = localPathById.get(g.source_id);
|
||||
if (!localPath) continue;
|
||||
const filePath = join(localPath, `${g.source_markdown_slug}.md`);
|
||||
const filePath = resolvePageFilePath(localPath, g.source_markdown_slug, g.source_id);
|
||||
if (!existsSync(filePath)) {
|
||||
mismatches.push(`${g.source_markdown_slug} (file missing)`);
|
||||
continue;
|
||||
|
||||
@@ -176,9 +176,11 @@ export async function runExtractFacts(
|
||||
if (legacyCount > 0) {
|
||||
result.guardTriggered = true;
|
||||
result.warnings.push(
|
||||
`extract_facts: ${legacyCount} legacy v0.31 fact rows pending fence backfill. ` +
|
||||
`Run \`gbrain apply-migrations --yes\` to complete v0_32_2 before this phase ` +
|
||||
`can safely reconcile fence → DB.`,
|
||||
`extract_facts: ${legacyCount} legacy fact rows pending fence backfill ` +
|
||||
`(row_num IS NULL — v0.31 rows or remote extract_facts deposits that ` +
|
||||
`predate the fence backstop). Run \`gbrain facts fence-backfill\` ` +
|
||||
`(idempotent, re-runnable) before this phase can safely reconcile ` +
|
||||
`fence → DB.`,
|
||||
);
|
||||
return result;
|
||||
}
|
||||
|
||||
@@ -20,7 +20,6 @@
|
||||
import type { BrainEngine } from './engine.ts';
|
||||
import type { ChunkInput } from './types.ts';
|
||||
import { embedBatchWithBackoff } from '../commands/embed.ts';
|
||||
import { resolveEmbeddingModelLabel } from './embedding.ts';
|
||||
import { type DbPacer, createNoopPacer, observed } from './db-pacer.ts';
|
||||
import { AbortError } from './abort-check.ts';
|
||||
|
||||
@@ -201,17 +200,11 @@ export async function embedStaleForSource(
|
||||
for (let j = 0; j < stale.length; j++) {
|
||||
staleIdxToEmbedding.set(stale[j].chunk_index, embeddings[j]);
|
||||
}
|
||||
// #1717: label re-embedded chunks with the model that produced the
|
||||
// vector; preserved chunks keep their existing model. Without this,
|
||||
// upsertChunks falls back to DEFAULT_EMBEDDING_MODEL for every chunk
|
||||
// (the same mislabel the embed.ts paths fixed).
|
||||
const embedModelLabel = resolveEmbeddingModelLabel();
|
||||
const merged: ChunkInput[] = existing.map((c) => ({
|
||||
chunk_index: c.chunk_index,
|
||||
chunk_text: c.chunk_text,
|
||||
chunk_source: c.chunk_source,
|
||||
embedding: staleIdxToEmbedding.get(c.chunk_index) ?? undefined,
|
||||
model: staleIdxToEmbedding.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
|
||||
token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
|
||||
// Carry through per-chunk metadata. upsertChunks writes these as
|
||||
// EXCLUDED.<col> (not COALESCE), so omitting them here resets image
|
||||
|
||||
@@ -113,21 +113,6 @@ export async function embedBatch(
|
||||
return results;
|
||||
}
|
||||
|
||||
/**
|
||||
* Resolve the embedding model label (`provider:model`) to stamp onto
|
||||
* `content_chunks.model`, so each chunk records the model that actually
|
||||
* produced its vector instead of the engine's hardcoded default (#1717).
|
||||
* Returns undefined if the gateway is unconfigured; callers then fall back
|
||||
* to the chunk's existing model rather than mislabeling it.
|
||||
*/
|
||||
export function resolveEmbeddingModelLabel(): string | undefined {
|
||||
try {
|
||||
return gatewayGetModel();
|
||||
} catch {
|
||||
return undefined;
|
||||
}
|
||||
}
|
||||
|
||||
/** Currently-configured embedding model (short form without provider prefix). */
|
||||
export function getEmbeddingModelName(): string {
|
||||
return gatewayGetModel().split(':').slice(1).join(':') || 'text-embedding-3-large';
|
||||
|
||||
+7
-6
@@ -1739,13 +1739,14 @@ export interface BrainEngine {
|
||||
* single-row supersede flow because fence reconciliation is the canonical
|
||||
* source-of-truth direction, not the consolidator path.
|
||||
*
|
||||
* Insertion is atomic per call: all rows commit in a single transaction
|
||||
* or none commit (the transaction rolls back on any constraint
|
||||
* violation, e.g. the v51 partial UNIQUE index on
|
||||
* `(source_id, source_markdown_slug, row_num)`).
|
||||
* Insertion runs in a single transaction. A collision on the v51
|
||||
* partial UNIQUE index `(source_id, source_markdown_slug, row_num)`
|
||||
* skips ONLY that row (ON CONFLICT DO NOTHING, #2044) — the rest of
|
||||
* the batch still commits, so a redundant deposit against an
|
||||
* already-indexed fence row is idempotent instead of a hard failure.
|
||||
*
|
||||
* Returns the inserted ids in input-order so callers can correlate
|
||||
* fence-row → DB-id without a separate lookup.
|
||||
* Returns the inserted ids in input-order (colliding rows omitted) so
|
||||
* callers can correlate fence-row → DB-id without a separate lookup.
|
||||
*/
|
||||
insertFacts(
|
||||
rows: Array<NewFact & { row_num: number; source_markdown_slug: string }>,
|
||||
|
||||
@@ -218,11 +218,27 @@ export async function writeFactsToFence(
|
||||
}
|
||||
|
||||
// 2. Upsert each fact onto the fence in input order. row_num
|
||||
// monotonically increases (max-existing + 1 per call, append-only).
|
||||
// monotonically increases, append-only, seeded from the MAX of
|
||||
// the fence and the DB index (#2044): when fence and DB have
|
||||
// diverged (e.g. legacy writes that stamped DB rows against a
|
||||
// fence at a path this code no longer reads), fence-max+1 can
|
||||
// collide with an existing DB row_num, tripping
|
||||
// idx_facts_fence_key and rolling back the whole batch.
|
||||
const dbMaxRows = await engine.executeRaw<{ max: number | string | null }>(
|
||||
`SELECT MAX(row_num) AS max FROM facts
|
||||
WHERE source_id = $1 AND source_markdown_slug = $2`,
|
||||
[target.sourceId, target.slug],
|
||||
);
|
||||
const dbMaxRowNum = Number(dbMaxRows[0]?.max ?? 0) || 0;
|
||||
const fenceMaxRowNum = parseFactsFence(body).facts
|
||||
.reduce((m, f) => Math.max(m, f.rowNum), 0);
|
||||
let nextRowNum = Math.max(fenceMaxRowNum, dbMaxRowNum) + 1;
|
||||
|
||||
const assignedRowNums: number[] = [];
|
||||
for (const f of facts) {
|
||||
const validFromStr = (f.validFrom ?? new Date()).toISOString().slice(0, 10);
|
||||
const { body: updated, rowNum } = upsertFactRow(body, {
|
||||
rowNum: nextRowNum++,
|
||||
claim: f.fact,
|
||||
kind: (f.kind ?? 'fact') as 'fact' | 'event' | 'preference' | 'commitment' | 'belief',
|
||||
confidence: f.confidence ?? 1.0,
|
||||
|
||||
+1
-11
@@ -8,7 +8,7 @@ import { chunkText } from './chunkers/recursive.ts';
|
||||
import { chunkCodeText, chunkCodeTextFull, detectCodeLanguage, CHUNKER_VERSION } from './chunkers/code.ts';
|
||||
import { findChunkForOffset } from './chunkers/edge-extractor.ts';
|
||||
import { extractCodeRefs, imageOfCandidates } from './link-extraction.ts';
|
||||
import { embedBatch, embedMultimodal, currentEmbeddingSignature, resolveEmbeddingModelLabel } from './embedding.ts';
|
||||
import { embedBatch, embedMultimodal, currentEmbeddingSignature } from './embedding.ts';
|
||||
import { slugifyPath, slugifyCodePath, isCodeFilePath } from './sync.ts';
|
||||
import type { ChunkInput, PageInput, PageType } from './types.ts';
|
||||
import { computeEffectiveDate } from './effective-date.ts';
|
||||
@@ -716,12 +716,8 @@ export async function importFromContent(
|
||||
? chunks.map((c) => wrapChunkForEmbedding(c.chunk_text, prefix, c.chunk_source))
|
||||
: chunks.map((c) => c.chunk_text);
|
||||
const embeddings = await embedBatch(wrappedTexts);
|
||||
// #1717: label each chunk with the model that actually produced its
|
||||
// vector, not the engine's hardcoded default.
|
||||
const embedModelLabel = resolveEmbeddingModelLabel();
|
||||
for (let i = 0; i < chunks.length; i++) {
|
||||
chunks[i].embedding = embeddings[i];
|
||||
if (embedModelLabel) chunks[i].model = embedModelLabel;
|
||||
// token_count tracks the wrapped string length so cost reporting
|
||||
// reflects what we actually sent to the embedder.
|
||||
chunks[i].token_count = Math.ceil(wrappedTexts[i].length / 4);
|
||||
@@ -1145,10 +1141,7 @@ export async function importCodeFile(
|
||||
const matched = existingByKey.get(key);
|
||||
if (matched && matched.embedding) {
|
||||
// Reuse the existing embedding verbatim. No API call, no cost.
|
||||
// #1717: carry the existing model label along with the reused vector
|
||||
// so the upsert doesn't relabel it with the engine default.
|
||||
chunks[i]!.embedding = matched.embedding as Float32Array;
|
||||
chunks[i]!.model = matched.model ?? undefined;
|
||||
chunks[i]!.token_count = matched.token_count ?? undefined;
|
||||
} else {
|
||||
needsEmbedIndexes.push(i);
|
||||
@@ -1160,12 +1153,9 @@ export async function importCodeFile(
|
||||
try {
|
||||
const textsToEmbed = needsEmbedIndexes.map((i) => chunks[i]!.chunk_text);
|
||||
const embeddings = await embedBatch(textsToEmbed);
|
||||
// #1717: stamp the model that produced these vectors.
|
||||
const embedModelLabel = resolveEmbeddingModelLabel();
|
||||
for (let j = 0; j < needsEmbedIndexes.length; j++) {
|
||||
const i = needsEmbedIndexes[j]!;
|
||||
chunks[i]!.embedding = embeddings[j]!;
|
||||
if (embedModelLabel) chunks[i]!.model = embedModelLabel;
|
||||
chunks[i]!.token_count = Math.ceil(chunks[i]!.chunk_text.length / 4);
|
||||
}
|
||||
} catch (e: unknown) {
|
||||
|
||||
@@ -4102,11 +4102,13 @@ export class PGLiteEngine implements BrainEngine {
|
||||
): Promise<{ inserted: number; ids: number[] }> {
|
||||
if (rows.length === 0) return { inserted: 0, ids: [] };
|
||||
|
||||
// Single transaction so the v51 partial UNIQUE index can roll back the
|
||||
// whole batch on constraint violation. Per-row INSERTs (not multi-row
|
||||
// VALUES) keep the embedding-vs-no-embedding branching readable; batch
|
||||
// sizes are small (5-30 rows per page in practice) so the loop overhead
|
||||
// is negligible vs the embedding compute cost.
|
||||
// Single transaction; per-row INSERTs (not multi-row VALUES) keep the
|
||||
// embedding-vs-no-embedding branching readable; batch sizes are small
|
||||
// (5-30 rows per page in practice) so the loop overhead is negligible
|
||||
// vs the embedding compute cost. #2044: ON CONFLICT DO NOTHING on the
|
||||
// v51 partial UNIQUE index makes a residual fence/DB row_num collision
|
||||
// skip that row instead of rolling back the whole batch (parity with
|
||||
// postgres-engine.ts).
|
||||
const ids = await this.db.transaction(async (tx) => {
|
||||
const out: number[] = [];
|
||||
for (const input of rows) {
|
||||
@@ -4149,7 +4151,11 @@ export class PGLiteEngine implements BrainEngine {
|
||||
$14, $15,
|
||||
$16, $17, $18, $19,
|
||||
$20
|
||||
) RETURNING id`
|
||||
)
|
||||
ON CONFLICT (source_id, source_markdown_slug, row_num)
|
||||
WHERE row_num IS NOT NULL
|
||||
DO NOTHING
|
||||
RETURNING id`
|
||||
: `INSERT INTO facts (
|
||||
source_id, entity_slug, fact, kind, visibility, notability, context,
|
||||
valid_from, valid_until, source, source_session, confidence,
|
||||
@@ -4163,12 +4169,16 @@ export class PGLiteEngine implements BrainEngine {
|
||||
$15, $16,
|
||||
$17, $18, $19, $20,
|
||||
$21
|
||||
) RETURNING id`,
|
||||
)
|
||||
ON CONFLICT (source_id, source_markdown_slug, row_num)
|
||||
WHERE row_num IS NOT NULL
|
||||
DO NOTHING
|
||||
RETURNING id`,
|
||||
embedStr === null
|
||||
? [ctx.source_id, entitySlug, input.fact, kind, visibility, notability, context, validFrom, validUntil, input.source, sourceSession, confidence, embeddedAt, input.row_num, input.source_markdown_slug, claimMetric, claimValue, claimUnit, claimPeriod, eventType]
|
||||
: [ctx.source_id, entitySlug, input.fact, kind, visibility, notability, context, validFrom, validUntil, input.source, sourceSession, confidence, embedStr, embeddedAt, input.row_num, input.source_markdown_slug, claimMetric, claimValue, claimUnit, claimPeriod, eventType],
|
||||
);
|
||||
out.push(ins.rows[0].id);
|
||||
if (ins.rows[0]) out.push(ins.rows[0].id);
|
||||
}
|
||||
return out;
|
||||
});
|
||||
|
||||
@@ -4302,10 +4302,12 @@ export class PostgresEngine implements BrainEngine {
|
||||
// ONCE per process so the cast matches the actual column type
|
||||
// (halfvec vs vector). The probe is cached after first call.
|
||||
const castSuffix = await this.resolveFactsEmbeddingCast();
|
||||
// Single transaction so the v51 partial UNIQUE index can roll back
|
||||
// the whole batch on constraint violation. Per-row INSERTs (not
|
||||
// multi-row VALUES) keep the embedding-vs-no-embedding branching
|
||||
// readable; batch sizes are small (5-30 rows per page in practice).
|
||||
// Single transaction; per-row INSERTs (not multi-row VALUES) keep the
|
||||
// embedding-vs-no-embedding branching readable; batch sizes are small
|
||||
// (5-30 rows per page in practice). #2044: ON CONFLICT DO NOTHING on
|
||||
// the v51 partial UNIQUE index makes a residual fence/DB row_num
|
||||
// collision skip that row instead of rolling back the whole batch —
|
||||
// the fence stays system-of-record and reconciliation catches up.
|
||||
// No supersede flow in this path — fence reconciliation is the
|
||||
// canonical source-of-truth direction, not the consolidator path.
|
||||
const ids = await sql.begin(async (tx) => {
|
||||
@@ -4346,9 +4348,13 @@ export class PostgresEngine implements BrainEngine {
|
||||
${input.row_num}, ${input.source_markdown_slug},
|
||||
${claimMetric}, ${claimValue}, ${claimUnit}, ${claimPeriod},
|
||||
${eventType}
|
||||
) RETURNING id
|
||||
)
|
||||
ON CONFLICT (source_id, source_markdown_slug, row_num)
|
||||
WHERE row_num IS NOT NULL
|
||||
DO NOTHING
|
||||
RETURNING id
|
||||
`;
|
||||
out.push(Number(ins[0].id));
|
||||
if (ins[0]) out.push(Number(ins[0].id));
|
||||
}
|
||||
return out;
|
||||
});
|
||||
|
||||
@@ -15,7 +15,6 @@ import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:tes
|
||||
import { PGLiteEngine } from '../src/core/pglite-engine.ts';
|
||||
import { resetPgliteState } from './helpers/reset-pglite.ts';
|
||||
import { embedStaleForSource } from '../src/core/embed-stale.ts';
|
||||
import { configureGateway, resetGateway } from '../src/core/ai/gateway.ts';
|
||||
import type { ChunkInput } from '../src/core/types.ts';
|
||||
|
||||
let engine: PGLiteEngine;
|
||||
@@ -277,49 +276,4 @@ describe('embedStaleForSource', () => {
|
||||
// The stale text row actually got its embedding.
|
||||
expect(txtRow.embedded_at).not.toBeNull();
|
||||
});
|
||||
|
||||
// #1717: the backfill path must label re-embedded chunks with the model
|
||||
// that produced the vector, and preserve the existing label on chunks it
|
||||
// did not touch (before the fix, both were reset to the engine default).
|
||||
test('labels re-embedded chunks with the gateway model, preserves untouched labels (#1717)', async () => {
|
||||
configureGateway({
|
||||
embedding_model: 'openai:text-embedding-3-large',
|
||||
env: { OPENAI_API_KEY: 'sk-test-embed-stale-1717' },
|
||||
});
|
||||
try {
|
||||
await engine.putPage('notes/model-label', {
|
||||
type: 'note',
|
||||
title: 'model-label',
|
||||
compiled_truth: '# model-label\n\nseeded',
|
||||
});
|
||||
await engine.upsertChunks('notes/model-label', [
|
||||
{
|
||||
chunk_index: 0,
|
||||
chunk_text: 'already embedded elsewhere',
|
||||
chunk_source: 'compiled_truth',
|
||||
embedding: new Float32Array(1536).fill(0.01),
|
||||
model: 'voyage:voyage-3',
|
||||
token_count: 4,
|
||||
},
|
||||
{
|
||||
chunk_index: 1,
|
||||
chunk_text: 'stale chunk needing embed',
|
||||
chunk_source: 'compiled_truth',
|
||||
token_count: 5,
|
||||
embedding: undefined, // stale
|
||||
},
|
||||
]);
|
||||
|
||||
const result = await embedStaleForSource(engine, 'default', { embedFn: fakeEmbedFn });
|
||||
expect(result.embedded).toBe(1);
|
||||
|
||||
const after = await engine.getChunks('notes/model-label');
|
||||
const preserved = after.find((c) => c.chunk_index === 0)!;
|
||||
const reembedded = after.find((c) => c.chunk_index === 1)!;
|
||||
expect(reembedded.model).toBe('openai:text-embedding-3-large');
|
||||
expect(preserved.model).toBe('voyage:voyage-3');
|
||||
} finally {
|
||||
resetGateway();
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
@@ -37,8 +37,6 @@ mock.module('../src/core/embedding.ts', () => ({
|
||||
// setPageEmbeddingSignature / invalidateStaleSignatureEmbeddings resolve to
|
||||
// null via the Proxy default, so the signature value is inert here.
|
||||
currentEmbeddingSignature: () => 'test:model:1536',
|
||||
// #1717: embed paths stamp this label on (re)embedded chunks.
|
||||
resolveEmbeddingModelLabel: () => 'openai:text-embedding-3-large',
|
||||
}));
|
||||
|
||||
// Import AFTER mocking.
|
||||
@@ -805,34 +803,3 @@ describe('embedAllStale --source threading (D7)', () => {
|
||||
expect((firstCallOpts as { sourceId?: string }).sourceId).toBe('media-corpus');
|
||||
});
|
||||
});
|
||||
|
||||
// #1717: content_chunks.model must record the model that actually produced
|
||||
// each vector, not the gateway/engine default.
|
||||
describe('content_chunks.model labeling (#1717)', () => {
|
||||
test('stamps the resolved embedding model on re-embedded chunks, preserves it on untouched chunks', async () => {
|
||||
let upserted: any[] | undefined;
|
||||
// Chunk 0 is stale (no embedded_at) → gets re-embedded this pass.
|
||||
// Chunk 1 is already embedded with a DIFFERENT model → must be preserved,
|
||||
// not relabeled to the current model.
|
||||
const chunks = [
|
||||
{ chunk_index: 0, chunk_text: 'a', chunk_source: 'compiled_truth', embedded_at: null, model: 'zeroentropyai:zembed-1', token_count: 1 },
|
||||
{ chunk_index: 1, chunk_text: 'b', chunk_source: 'compiled_truth', embedded_at: '2026-01-01', embedding: new Float32Array(1536), model: 'voyage:voyage-3', token_count: 1 },
|
||||
];
|
||||
const engine = mockEngine({
|
||||
getPage: async () => ({ slug: 'notes/x', compiled_truth: 'a', timeline: '', source_id: 'default' }),
|
||||
getChunks: async () => chunks,
|
||||
upsertChunks: async (_slug: string, c: any[]) => { upserted = c; },
|
||||
setPageEmbeddingSignature: async () => null,
|
||||
});
|
||||
|
||||
await runEmbedCore(engine, { slugs: ['notes/x'] });
|
||||
|
||||
expect(upserted).toBeDefined();
|
||||
const byIdx = Object.fromEntries(upserted!.map(c => [c.chunk_index, c]));
|
||||
// Re-embedded chunk carries the model that produced its vector (was
|
||||
// mislabeled with the default before the fix).
|
||||
expect(byIdx[0].model).toBe('openai:text-embedding-3-large');
|
||||
// Untouched chunk keeps its original model — no wholesale relabel.
|
||||
expect(byIdx[1].model).toBe('voyage:voyage-3');
|
||||
});
|
||||
});
|
||||
|
||||
@@ -304,7 +304,9 @@ describe('runExtractFacts — empty-fence guard (Codex R2-#7)', () => {
|
||||
expect(r.legacyRowsPending).toBe(1);
|
||||
expect(r.factsInserted).toBe(0);
|
||||
expect(r.factsDeleted).toBe(0);
|
||||
expect(r.warnings.some(w => w.includes('apply-migrations'))).toBe(true);
|
||||
// #1867: the remedy hint points at the re-runnable backfill command,
|
||||
// not the one-shot v0_32_2 migration (which the ledger never re-runs).
|
||||
expect(r.warnings.some(w => w.includes('gbrain facts fence-backfill'))).toBe(true);
|
||||
|
||||
// Legacy row was NOT touched.
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
|
||||
@@ -0,0 +1,133 @@
|
||||
/**
|
||||
* #1867 — `gbrain facts fence-backfill` command tests.
|
||||
*
|
||||
* The command re-runs the (idempotent) v0_32_2 phase B on demand so
|
||||
* row_num-NULL backlogs — remote extract_facts deposits that predate
|
||||
* the fence-write backstop — can be cleared without re-running the
|
||||
* one-shot migration. Real PGLite + real tempdir filesystem.
|
||||
*/
|
||||
|
||||
import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:test';
|
||||
import { mkdtempSync, rmSync, existsSync, readFileSync } from 'node:fs';
|
||||
import { tmpdir } from 'node:os';
|
||||
import { join } from 'node:path';
|
||||
|
||||
import { PGLiteEngine } from '../src/core/pglite-engine.ts';
|
||||
import { runFactsCommand } from '../src/commands/facts.ts';
|
||||
import { phaseBFenceFacts } from '../src/commands/migrations/v0_32_2.ts';
|
||||
|
||||
let engine: PGLiteEngine;
|
||||
let brainDir: string;
|
||||
|
||||
beforeAll(async () => {
|
||||
engine = new PGLiteEngine();
|
||||
await engine.connect({});
|
||||
await engine.initSchema();
|
||||
});
|
||||
|
||||
afterAll(async () => {
|
||||
await engine.disconnect();
|
||||
try {
|
||||
if (brainDir) rmSync(brainDir, { recursive: true, force: true });
|
||||
} catch { /* best-effort */ }
|
||||
});
|
||||
|
||||
beforeEach(async () => {
|
||||
brainDir = mkdtempSync(join(tmpdir(), 'facts-backfill-cmd-test-'));
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
await (engine as any).db.query('DELETE FROM facts');
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
await (engine as any).db.query(
|
||||
`UPDATE sources SET local_path = $1 WHERE id = 'default'`,
|
||||
[brainDir],
|
||||
);
|
||||
});
|
||||
|
||||
async function seedLegacyFact(fact: string): Promise<void> {
|
||||
// The row_num-NULL shape a remote extract_facts deposit leaves behind
|
||||
// when it lands via the legacy DB-only path.
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
await (engine as any).db.query(
|
||||
`INSERT INTO facts (source_id, entity_slug, fact, kind, visibility, notability,
|
||||
valid_from, source, confidence)
|
||||
VALUES ('default', 'people/alice', $1, 'fact', 'private', 'medium',
|
||||
now(), 'mcp:extract_facts', 1.0)`,
|
||||
[fact],
|
||||
);
|
||||
}
|
||||
|
||||
describe('gbrain facts fence-backfill', () => {
|
||||
test('fences row_num-NULL rows and stamps the DB', async () => {
|
||||
await seedLegacyFact('Deposited remotely');
|
||||
|
||||
await runFactsCommand(engine, ['fence-backfill']);
|
||||
|
||||
// The fence exists on disk with the claim.
|
||||
const filePath = join(brainDir, 'people/alice.md');
|
||||
expect(existsSync(filePath)).toBe(true);
|
||||
expect(readFileSync(filePath, 'utf-8')).toContain('Deposited remotely');
|
||||
|
||||
// The backlog is cleared: no row_num-NULL rows remain.
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const rows = await (engine as any).db.query(
|
||||
'SELECT row_num, source_markdown_slug FROM facts',
|
||||
);
|
||||
expect(rows.rows).toHaveLength(1);
|
||||
expect(rows.rows[0].row_num).toBe(1);
|
||||
expect(rows.rows[0].source_markdown_slug).toBe('people/alice');
|
||||
});
|
||||
|
||||
test('re-run is a no-op (idempotent)', async () => {
|
||||
await seedLegacyFact('Deposited remotely');
|
||||
await runFactsCommand(engine, ['fence-backfill']);
|
||||
await runFactsCommand(engine, ['fence-backfill']);
|
||||
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const rows = await (engine as any).db.query('SELECT id FROM facts');
|
||||
expect(rows.rows).toHaveLength(1);
|
||||
const body = readFileSync(join(brainDir, 'people/alice.md'), 'utf-8');
|
||||
expect(body.match(/Deposited remotely/g)).toHaveLength(1);
|
||||
});
|
||||
|
||||
test('--dry-run reports without writing', async () => {
|
||||
await seedLegacyFact('Deposited remotely');
|
||||
await runFactsCommand(engine, ['fence-backfill', '--dry-run']);
|
||||
|
||||
expect(existsSync(join(brainDir, 'people/alice.md'))).toBe(false);
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const rows = await (engine as any).db.query(
|
||||
'SELECT row_num FROM facts',
|
||||
);
|
||||
expect(rows.rows[0].row_num).toBeNull();
|
||||
});
|
||||
|
||||
test('diverged page: appends past the DB row_num max instead of colliding (#2044 class)', async () => {
|
||||
// The #2044 divergence shape the backfill must survive: the DB already
|
||||
// holds stamped rows 1..3 for the slug (legacy wrong-path fence write),
|
||||
// but the fence at the resolved path is missing. Fence-max+1 (= 1) would
|
||||
// collide with the stamped rows on the post-rename UPDATE, failing the
|
||||
// page and leaving the renamed fence disagreeing with the DB.
|
||||
for (let n = 1; n <= 3; n++) {
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
await (engine as any).db.query(
|
||||
`INSERT INTO facts (source_id, entity_slug, fact, kind, visibility, notability,
|
||||
valid_from, source, confidence, row_num, source_markdown_slug)
|
||||
VALUES ('default', 'people/alice', $1, 'fact', 'private', 'medium',
|
||||
now(), 'mcp:extract_facts', 1.0, $2, 'people/alice')`,
|
||||
[`stamped ${n}`, n],
|
||||
);
|
||||
}
|
||||
await seedLegacyFact('Deposited remotely');
|
||||
|
||||
const result = await phaseBFenceFacts(engine, { dryRun: false });
|
||||
expect(result.status).toBe('complete');
|
||||
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const rows = await (engine as any).db.query(
|
||||
`SELECT row_num FROM facts WHERE fact = 'Deposited remotely'`,
|
||||
);
|
||||
expect(rows.rows[0].row_num).toBe(4);
|
||||
const body = readFileSync(join(brainDir, 'people/alice.md'), 'utf-8');
|
||||
expect(body).toContain('| 4 | Deposited remotely |');
|
||||
});
|
||||
});
|
||||
@@ -292,6 +292,49 @@ describe('lookupSourceLocalPath', () => {
|
||||
});
|
||||
});
|
||||
|
||||
describe('writeFactsToFence — fence/DB divergence (#2044)', () => {
|
||||
test('seeds row_num past the DB max when the fence lags the DB', async () => {
|
||||
// Simulate the divergence class from #2044: DB rows were stamped with
|
||||
// row_nums against a fence written at a path this code no longer reads
|
||||
// (e.g. the pre-"Local patch 2026-06-11" wrong-path writes). The page
|
||||
// on disk has NO fence, but the DB already holds row_num 1..3 for the
|
||||
// slug. Pre-fix, the next deposit re-assigned row_num=1 from fence
|
||||
// text alone and the whole insertFacts batch failed on
|
||||
// idx_facts_fence_key.
|
||||
for (let n = 1; n <= 3; n++) {
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
await (engine as any).db.query(
|
||||
`INSERT INTO facts (source_id, entity_slug, fact, kind, visibility, notability,
|
||||
valid_from, source, confidence, row_num, source_markdown_slug)
|
||||
VALUES ('default', 'people/dana', $1, 'fact', 'private', 'medium',
|
||||
now(), 'mcp:extract_facts', 1.0, $2, 'people/dana')`,
|
||||
[`old claim ${n}`, n],
|
||||
);
|
||||
}
|
||||
|
||||
const result = await writeFactsToFence(
|
||||
engine,
|
||||
{ sourceId: 'default', localPath: brainDir, slug: 'people/dana' },
|
||||
[baseInput({ fact: 'second deposit' })],
|
||||
);
|
||||
|
||||
expect(result.fenceWriteFailed).toBeUndefined();
|
||||
expect(result.inserted).toBe(1);
|
||||
|
||||
// The new row landed PAST the DB max, not at fence-max+1 (= 1).
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const rows = await (engine as any).db.query(
|
||||
'SELECT row_num FROM facts WHERE id = $1',
|
||||
[result.ids[0]],
|
||||
);
|
||||
expect(rows.rows[0].row_num).toBe(4);
|
||||
|
||||
// And the on-disk fence carries the same row_num — fence and DB agree.
|
||||
const body = readFileSync(join(brainDir, 'people/dana.md'), 'utf-8');
|
||||
expect(body).toContain('| 4 | second deposit |');
|
||||
});
|
||||
});
|
||||
|
||||
// Cleanup any leftover tempdirs after the whole suite.
|
||||
afterAll(() => {
|
||||
// No-op: each test cleaned up via the beforeEach; this is a safety net.
|
||||
|
||||
@@ -73,21 +73,4 @@ describe('importFromContent embedding_signature stamping (F1)', () => {
|
||||
await importFromContent(engine, 'concepts/unstamped', '# Unstamped\n\nbody content.', { noEmbed: true });
|
||||
expect(await signatureOf('concepts/unstamped')).toBeNull();
|
||||
});
|
||||
|
||||
// #1717: content_chunks.model must record the model that produced the
|
||||
// vector (the configured gateway model), not the engine's hardcoded
|
||||
// default. The gateway here is configured to openai:text-embedding-3-large,
|
||||
// which differs from DEFAULT_EMBEDDING_MODEL — so this fails without the
|
||||
// import-path model stamping.
|
||||
test('inline embed labels content_chunks.model with the configured model (#1717)', async () => {
|
||||
await importFromContent(engine, 'concepts/labeled', '# Labeled\n\nsome body content to chunk and embed.', {});
|
||||
const rows = await engine.executeRaw<{ model: string }>(
|
||||
`SELECT cc.model FROM content_chunks cc
|
||||
JOIN pages p ON p.id = cc.page_id
|
||||
WHERE p.slug = $1 AND p.source_id = 'default'`,
|
||||
['concepts/labeled'],
|
||||
);
|
||||
expect(rows.length).toBeGreaterThan(0);
|
||||
for (const r of rows) expect(r.model).toBe('openai:text-embedding-3-large');
|
||||
});
|
||||
});
|
||||
|
||||
@@ -5,7 +5,7 @@
|
||||
* - Batch insert N rows persists row_num + source_markdown_slug
|
||||
* - Empty batch is a no-op
|
||||
* - Returns ids in input-order
|
||||
* - v51 partial UNIQUE index rolls back the whole batch on a collision
|
||||
* - v51 partial UNIQUE collision skips only the colliding row (#2044)
|
||||
* - deleteFactsForPage scopes by (source_id, source_markdown_slug);
|
||||
* never touches other pages or pre-v51 NULL-source_markdown_slug rows
|
||||
* - deleteFactsForPage on an empty page returns deleted:0 (idempotent)
|
||||
@@ -135,30 +135,29 @@ describe('engine.insertFacts — batch insert', () => {
|
||||
});
|
||||
});
|
||||
|
||||
test('v51 partial UNIQUE index rolls back the whole batch on collision', async () => {
|
||||
test('v51 partial UNIQUE collision skips ONLY the colliding row (#2044)', async () => {
|
||||
// Seed row #1 first.
|
||||
await engine.insertFacts([fixtureFact(1, { fact: 'seeded' })], { source_id: 'default' });
|
||||
|
||||
// Now try to batch-insert rows that include a colliding row_num=1.
|
||||
let threw = false;
|
||||
try {
|
||||
await engine.insertFacts(
|
||||
[
|
||||
fixtureFact(2, { fact: 'second' }),
|
||||
fixtureFact(1, { fact: 'collides' }), // row_num=1 on same (source_id, source_markdown_slug)
|
||||
fixtureFact(3, { fact: 'third' }),
|
||||
],
|
||||
{ source_id: 'default' },
|
||||
);
|
||||
} catch {
|
||||
threw = true;
|
||||
}
|
||||
expect(threw).toBe(true);
|
||||
// Batch-insert rows that include a colliding row_num=1. Pre-#2044 this
|
||||
// threw and rolled back the whole batch, making a second remote
|
||||
// extract_facts deposit to an already-fenced page a hard failure. Now
|
||||
// ON CONFLICT DO NOTHING skips the colliding row and keeps the rest.
|
||||
const result = await engine.insertFacts(
|
||||
[
|
||||
fixtureFact(2, { fact: 'second' }),
|
||||
fixtureFact(1, { fact: 'collides' }), // row_num=1 on same (source_id, source_markdown_slug)
|
||||
fixtureFact(3, { fact: 'third' }),
|
||||
],
|
||||
{ source_id: 'default' },
|
||||
);
|
||||
expect(result.inserted).toBe(2);
|
||||
expect(result.ids).toHaveLength(2);
|
||||
|
||||
// Verify the transaction rolled back — only the seeded row should remain.
|
||||
// The seeded row survives untouched; the colliding claim is skipped.
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
const rows = await (engine as any).db.query('SELECT fact FROM facts ORDER BY id');
|
||||
expect(rows.rows.map((r: { fact: string }) => r.fact)).toEqual(['seeded']);
|
||||
expect(rows.rows.map((r: { fact: string }) => r.fact)).toEqual(['seeded', 'second', 'third']);
|
||||
});
|
||||
|
||||
test('different source_markdown_slug values DO NOT collide on the same row_num', async () => {
|
||||
|
||||
Reference in New Issue
Block a user