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Author SHA1 Message Date
Garry TanandClaude Fable 5 5882d5261a fix(search): match both slash-split and literal slash forms in FTS queries (#2380 review)
Review finding on the normalize-only approach: Postgres' text-search
parser emits the joined file-alias lexeme on the INDEX side too
(to_tsvector('english','acme/widget') -> 'acme/widget'), so replacing
'/' with whitespace in the query made documents containing the literal
slash form (file paths, URLs, pasted titles) unreachable — the split-word
AND pass can't match the joined lexeme and the OR fallback can't either.
Pre-fix, those exact-form queries DID match.

Replace the TS-side normalizeKeywordQuery with buildWebsearchQueryExpr
in sql-ranking.ts (shared by both engines, keeping them in lockstep): a
slash-bearing query now binds the raw text once and matches
(websearch_to_tsquery(translate($1,'/',' ')) || websearch_to_tsquery($1))
— split-word prose AND literal slash forms alike. Slash-free queries keep
the byte-identical single-parse SQL and identical ts_rank.

New regression test pins the literal-slash arm (verified failing under
the normalize-only expression); the two AND-vs-OR slash tests still pass.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-22 11:35:32 -07:00
a5a80549e5 fix(search,embed): normalize / in FTS queries; CPU-safe defaults for local embedding endpoints
Two backlog fixes:

1. Takeover of #2380 (search): Postgres' default text-search parser
   classifies foo/bar as a single file-alias token mapped to the simple
   dictionary, so websearch_to_tsquery produces one un-stemmed lexeme
   that never matches indexed text — slash-containing queries bypassed
   FTS AND semantics (zero primary hits, OR-fallback results only).
   normalizeKeywordQuery() replaces / with whitespace before parse.
   Beyond the original PR: also routes searchTitles through the
   normalizer (the PR only covered the two chunk arms), applies it in
   BOTH engines, and drops the stray node_modules symlink from the diff.

2. Fixes #2552 (embed): cloud-tuned embedding defaults silently wedge
   CPU-only Ollama boxes. The ollama recipe now declares a conservative
   static batch cap (max_batch_tokens 4096 x chars_per_token 2, ~8K
   chars/request) instead of no_batch_cap — Ollama never returns a
   recognizable token-limit error, so the recursive-halving safety net
   can't fire. Bulk embed auto-caps worker fan-out at 2 for local
   endpoints (ollama / llama-server / localhost base URL) unless
   GBRAIN_EMBED_CONCURRENCY is set explicitly, and gbrain doctor grows
   an embed_concurrency check that warns when an explicit override fans
   out against a local endpoint.

Co-authored-by: rwbaker <rwbaker@users.noreply.github.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-21 15:12:33 -07:00
15 changed files with 384 additions and 131 deletions
+59
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@@ -820,6 +820,10 @@ export async function doctorReportRemote(engine: BrainEngine): Promise<DoctorRep
// v0.42.x (#1794, 4A): pool-budget nudge when GBRAIN_MAX_CONNECTIONS is set.
checks.push(await checkPoolBudget(engine));
// #2552: warn when an explicit embed-concurrency override fans out against
// a local single-slot embedding endpoint (silent backfill starvation).
checks.push(await checkEmbedConcurrency());
// v0.42.7 (#1696): link-extraction lag. Strictly SQL (single indexed COUNT),
// safe on the thin-client/remote path — remote operators on checkout-less
// Postgres brains are exactly who can't otherwise see the extraction backlog.
@@ -3815,6 +3819,61 @@ export function computePoolBudgetCheck(
};
}
/**
* #2552: warn when an explicit GBRAIN_EMBED_CONCURRENCY override fans out
* against a local single-slot embedding endpoint (Ollama / llama-server /
* localhost base URL). Requests serialize on the one loaded model, so N
* parallel pages multiply latency xN and can exceed the fetch timeout with
* no surfaced error the backfill silently starves. (When the env var is
* unset, embed auto-caps at LOCAL_EMBED_CONCURRENCY_CAP and this check
* reports ok.) Pure; exported for tests.
*/
export function computeEmbedConcurrencyCheck(
isLocalEndpoint: boolean,
envValue: string | undefined,
localCap: number,
): Check {
const name = 'embed_concurrency';
if (!isLocalEndpoint) {
return { name, status: 'ok', message: 'Embedding endpoint is not a local inference server — cloud concurrency defaults apply.' };
}
const parsed = envValue ? parseInt(envValue, 10) : NaN;
if (envValue && Number.isFinite(parsed) && parsed > localCap) {
return {
name,
status: 'warn',
message:
`GBRAIN_EMBED_CONCURRENCY=${parsed} against a local embedding endpoint. ` +
`Local inference servers serialize requests, so ${parsed} parallel pages multiply ` +
`latency x${parsed} and can exceed the fetch timeout — the embed backfill stalls ` +
`with no error. Unset GBRAIN_EMBED_CONCURRENCY (auto-caps at ${localCap}) or set it <= ${localCap}.`,
};
}
return {
name,
status: 'ok',
message: `Local embedding endpoint detected; embed concurrency capped at ${envValue ? parsed : localCap}.`,
};
}
/** Thin gateway/env wrapper over `computeEmbedConcurrencyCheck`. */
export async function checkEmbedConcurrency(): Promise<Check> {
try {
const { isLocalEmbeddingEndpoint, LOCAL_EMBED_CONCURRENCY_CAP } = await import('../core/ai/gateway.ts');
return computeEmbedConcurrencyCheck(
isLocalEmbeddingEndpoint(),
process.env.GBRAIN_EMBED_CONCURRENCY,
LOCAL_EMBED_CONCURRENCY_CAP,
);
} catch (err) {
return {
name: 'embed_concurrency',
status: 'ok',
message: `Skipped (${err instanceof Error ? err.message : String(err)})`,
};
}
}
/** Thin env/engine wrapper over `computePoolBudgetCheck`. */
export async function checkPoolBudget(_engine: BrainEngine): Promise<Check> {
try {
+30 -8
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@@ -1,5 +1,6 @@
import type { BrainEngine } from '../core/engine.ts';
import { embedBatch, currentEmbeddingSignature } from '../core/embedding.ts';
import { isLocalEmbeddingEndpoint, LOCAL_EMBED_CONCURRENCY_CAP } from '../core/ai/gateway.ts';
import type { ChunkInput } from '../core/types.ts';
import { chunkText } from '../core/chunkers/recursive.ts';
import { createProgress, type ProgressReporter } from '../core/progress.ts';
@@ -176,6 +177,31 @@ export class EmbeddingDimMismatchError extends Error {
}
}
/**
* #2552: resolve the bulk-embed worker count. Env override or the
* cloud-tuned default of 20 — but when the operator did NOT set
* GBRAIN_EMBED_CONCURRENCY and the embedding endpoint is a local inference
* server (Ollama / llama-server / localhost base URL), cap at
* LOCAL_EMBED_CONCURRENCY_CAP: 20 parallel pages against a single-slot
* server serialize on the one loaded model, multiply latency x20 past the
* fetch timeout, and starve the backfill with no surfaced error. An
* explicit env value always wins (`gbrain doctor` warns instead).
* Pacing only ever LOWERS concurrency (Codex P2).
*/
export function resolveEmbedConcurrency(paceMaxConcurrency?: number): number {
const envSet = !!process.env.GBRAIN_EMBED_CONCURRENCY;
const base = parseInt(process.env.GBRAIN_EMBED_CONCURRENCY || '20', 10);
let resolved = base;
if (!envSet && isLocalEmbeddingEndpoint() && base > LOCAL_EMBED_CONCURRENCY_CAP) {
resolved = LOCAL_EMBED_CONCURRENCY_CAP;
serr(
`[embed] local embedding endpoint detected — capping concurrency at ` +
`${LOCAL_EMBED_CONCURRENCY_CAP} (set GBRAIN_EMBED_CONCURRENCY to override)`,
);
}
return paceMaxConcurrency ? Math.min(resolved, paceMaxConcurrency) : resolved;
}
/**
* Pre-flight check: read the actual schema column dim and compare to the
* gateway's resolved dim. Throws `EmbeddingDimMismatchError` on mismatch
@@ -677,10 +703,8 @@ async function embedAll(
// Paced runs lower this to the resolved cap (the real lever vs pooler-slot
// starvation); unpaced keeps the env/default 20. Codex P2: only ever LOWER —
// never raise above an operator's existing env cap.
const BASE_CONCURRENCY = parseInt(process.env.GBRAIN_EMBED_CONCURRENCY || '20', 10);
const CONCURRENCY = staleOpts?.paceMaxConcurrency
? Math.min(BASE_CONCURRENCY, staleOpts.paceMaxConcurrency)
: BASE_CONCURRENCY;
// #2552: local endpoints auto-cap — see resolveEmbedConcurrency.
const CONCURRENCY = resolveEmbedConcurrency(staleOpts?.paceMaxConcurrency);
async function embedOnePage(page: typeof pages[number]) {
// #1737: bail before doing any work for this page if the run was aborted.
@@ -855,10 +879,8 @@ async function embedAllStale(
// Paced runs lower concurrency to the resolved cap (E-1: worker count IS the
// lever on this single pool, no separate permit). Codex P2: pacing only ever
// LOWERS concurrency — never raise above an operator's existing env cap.
const BASE_CONCURRENCY = parseInt(process.env.GBRAIN_EMBED_CONCURRENCY || '20', 10);
const CONCURRENCY = staleOpts?.paceMaxConcurrency
? Math.min(BASE_CONCURRENCY, staleOpts.paceMaxConcurrency)
: BASE_CONCURRENCY;
// #2552: local endpoints auto-cap — see resolveEmbedConcurrency.
const CONCURRENCY = resolveEmbedConcurrency(staleOpts?.paceMaxConcurrency);
const pacer = staleOpts?.pacer ?? createNoopPacer();
// D3 + D3a + D8: wall-clock budget. 30 min default; env override.
+5 -15
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@@ -43,7 +43,7 @@ import {
} from '../core/link-extraction.ts';
import { createProgress } from '../core/progress.ts';
import { getCliOptions, cliOptsToProgressOptions } from '../core/cli-options.ts';
import { pathToSlug, slugifyPath, pruneDir, isSyncable } from '../core/sync.ts';
import { pathToSlug, pruneDir, isSyncable } from '../core/sync.ts';
// v0.41.18.0: withRetry + isRetryableConnError + WithRetryOpts moved to
// src/core/retry.ts as the canonical primitive. Engine methods
// (addLinksBatch/addTimelineEntriesBatch/upsertChunks) now self-retry via
@@ -269,24 +269,14 @@ export function extractMarkdownLinks(content: string): { name: string; relTarget
export function resolveSlug(fileDir: string, relTarget: string, allSlugs: Set<string>): string | null {
const targetNoExt = relTarget.endsWith('.md') ? relTarget.slice(0, -3) : relTarget;
// Issue #1964: wikilinks carry raw Obsidian paths (`[[llm-wiki/entities/AI 3.0]]`)
// but allSlugs holds sync-slugified slugs (`llm-wiki/entities/ai-3.0`). Try the
// raw candidate first (back-compat), then the sync-consistent slugified form.
const hit = (candidate: string): string | null => {
if (allSlugs.has(candidate)) return candidate;
const slugified = slugifyPath(candidate);
if (slugified !== candidate && allSlugs.has(slugified)) return slugified;
return null;
};
const s1 = hit(join(fileDir, targetNoExt));
if (s1) return s1;
const s1 = join(fileDir, targetNoExt);
if (allSlugs.has(s1)) return s1;
const parts = fileDir.split('/').filter(Boolean);
for (let strip = 1; strip <= parts.length; strip++) {
const ancestor = parts.slice(0, parts.length - strip).join('/');
const candidate = hit(ancestor ? join(ancestor, targetNoExt) : targetNoExt);
if (candidate) return candidate;
const candidate = ancestor ? join(ancestor, targetNoExt) : targetNoExt;
if (allSlugs.has(candidate)) return candidate;
}
return null;
+27
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@@ -683,6 +683,33 @@ export function getEmbeddingDimensions(): number {
return requireConfig().embedding_dimensions ?? DEFAULT_EMBEDDING_DIMENSIONS;
}
/**
* #2552: cap for parallel bulk-embed workers against a local inference
* server. A single-slot Ollama/llama-server serializes requests, so the
* cloud-tuned 20-worker fan-out multiplies latency x20 and blows past the
* fetch timeout with no surfaced error (the backfill silently starves).
*/
export const LOCAL_EMBED_CONCURRENCY_CAP = 2;
/**
* #2552: true when the configured embedding model routes to a local
* inference server — the `ollama` / `llama-server` recipes, or any recipe
* whose base URL was explicitly pointed at localhost. Bulk callers use this
* to pick CPU-safe concurrency defaults; `gbrain doctor` uses it to warn
* about an explicit cloud-sized override. Fail-open: unconfigured or
* unresolvable gateway → false (cloud behavior, the historical default).
*/
export function isLocalEmbeddingEndpoint(): boolean {
try {
const { recipe } = resolveRecipe(getEmbeddingModel());
if (recipe.id === 'ollama' || recipe.id === 'llama-server') return true;
const base = requireConfig().base_urls?.[recipe.id] ?? '';
return /\/\/(localhost|127\.0\.0\.1|\[::1\])(:|\/|$)/i.test(base);
} catch {
return false;
}
}
/**
* v0.28.11: returns the configured multimodal embedding model when set,
* or undefined if the brain falls back to `embedding_model` for multimodal
+11 -3
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@@ -29,9 +29,17 @@ export const ollama: Recipe = {
trust_custom_dims: true, // #2271: local models carry varied native dims
cost_per_1m_tokens_usd: 0,
price_last_verified: '2026-04-20',
// Ollama's batch capacity depends on the locally loaded model + the
// OLLAMA_NUM_PARALLEL config; no static cap to declare. v0.32 (#779).
no_batch_cap: true,
// #2552: Ollama's true batch capacity depends on the locally loaded
// model + OLLAMA_NUM_PARALLEL, but the previous `no_batch_cap: true`
// meant a whole page went out in ONE request — on a CPU-only box that
// multiplies latency past the fetch timeout and the backfill starves
// with no surfaced error. Ollama doesn't return a recognizable
// token-limit error either, so the recursive-halving safety net never
// fires; a conservative static pre-split cap is the only guard.
// 4096 tokens x 2 chars/token ~= 8K chars per request (code-dense
// pages run ~2 chars/token, not the tiktoken-ish 4).
max_batch_tokens: 4096,
chars_per_token: 2,
},
},
setup_hint: 'Install Ollama from https://ollama.ai, then `ollama pull nomic-embed-text` and `ollama serve`.',
+1
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@@ -141,6 +141,7 @@ export const OPS_CHECK_NAMES: ReadonlySet<string> = new Set([
'pgbouncer_prepare',
'pgvector',
'pool_budget',
'embed_concurrency',
'progressive_batch_audit_health',
'queue_health',
'reranker_health',
+4 -20
View File
@@ -14,7 +14,6 @@
import type { BrainEngine } from './engine.ts';
import type { PageType } from './types.ts';
import { ensureWellFormed } from './text-safe.ts';
import { slugifyPath } from './sync.ts';
/**
* v0.42.7 — link-extraction version stamp. Bump this ISO timestamp whenever the
@@ -483,29 +482,14 @@ export async function extractPageLinks(
// pre-v0.40.8.2 behavior of dropping bare wikilinks outside
// DIR_PATTERN.
if (ref.needsResolution) {
if (typeof resolver.resolveBasenameMatches !== 'function') continue;
if (!opts.globalBasename || typeof resolver.resolveBasenameMatches !== 'function') {
continue;
}
// Issue #972 (codex): resolve by the wikilink TARGET (ref.slug — the
// text inside `[[...]]` before any `|`), NOT the display alias
// (ref.name = match[2]). `[[struktura|the project]]` must resolve
// `struktura`, not "the project". The display text is for context only.
//
// Issue #1964: a dir-qualified wikilink (`[[llm-wiki/entities/AI 3.0]]`)
// carries a raw Obsidian path while page slugs are sync-slugified
// (`llm-wiki/entities/ai-3.0`). Slugify the path the same way sync does,
// then match by exact slug or path-suffix (wiki-root-relative authoring).
// This runs regardless of global_basename — it's dir-qualified, so the
// cross-dir false-positive risk the flag guards against doesn't apply.
// Mirrors the FS path's resolveSlug ancestor walk. Bare `[[name]]`
// wikilinks still require the global_basename flag.
let matches: string[] = [];
const slugified = ref.slug.includes('/') ? slugifyPath(ref.slug) : '';
if (slugified.includes('/')) {
const tail = slugified.slice(slugified.lastIndexOf('/') + 1);
matches = (await resolver.resolveBasenameMatches(tail))
.filter(m => m === slugified || m.endsWith(`/${slugified}`));
} else if (opts.globalBasename) {
matches = await resolver.resolveBasenameMatches(ref.slug);
}
const matches = await resolver.resolveBasenameMatches(ref.slug);
if (matches.length === 0) continue;
const idx = content.indexOf(ref.slug);
const context = idx >= 0 ? excerpt(content, idx, 240) : ref.name;
+16 -7
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@@ -56,7 +56,7 @@ import { GBrainError, PAGE_SORT_SQL, ENRICH_ORDER_SQL } from './types.ts';
import { finalizeLastSeen } from './chronicle/last-seen.ts';
import { computeAnomaliesFromBuckets } from './cycle/anomaly.ts';
import { resolveBoostMap, resolveHardExcludes } from './search/source-boost.ts';
import { buildSourceFactorCase, buildHardExcludeClause, buildVisibilityClause, buildRecencyComponentSql, buildBestPerPagePoolCte, buildOrFallbackWebsearchQuery } from './search/sql-ranking.ts';
import { buildSourceFactorCase, buildHardExcludeClause, buildVisibilityClause, buildRecencyComponentSql, buildBestPerPagePoolCte, buildOrFallbackWebsearchQuery, buildWebsearchQueryExpr } from './search/sql-ranking.ts';
import {
normalizeEngineColumn,
buildVectorCastFragment,
@@ -1591,6 +1591,8 @@ export class PGLiteEngine implements BrainEngine {
}
// v0.20.0 Cathedral II Layer 10 C1/C2: language + symbol-kind filters.
// #2380: slash-bearing queries match both the split-word and literal
// slash forms — see buildWebsearchQueryExpr in ./search/sql-ranking.ts.
const params: unknown[] = [query, innerLimit, limit, offset];
let extraFilter = '';
if (opts?.language) {
@@ -1630,6 +1632,7 @@ export class PGLiteEngine implements BrainEngine {
// FTS config name (e.g. 'english', 'pt_br'). Validated by getFtsLanguage()
// — safe to interpolate into raw SQL.
const ftsLang = getFtsLanguage();
const ftsQueryExpr = buildWebsearchQueryExpr(ftsLang, '$1', query);
const keywordSql =
`WITH ranked AS (
@@ -1637,14 +1640,14 @@ export class PGLiteEngine implements BrainEngine {
p.slug, p.id as page_id, p.title, p.type, p.source_id,
p.effective_date, p.effective_date_source,
cc.id as chunk_id, cc.chunk_index, cc.chunk_text, cc.chunk_source,
ts_rank(cc.search_vector, websearch_to_tsquery('${ftsLang}', $1)) * ${sourceFactorCase} AS score,
ts_rank(cc.search_vector, ${ftsQueryExpr}) * ${sourceFactorCase} AS score,
CASE WHEN p.updated_at < (
SELECT MAX(te.created_at) FROM timeline_entries te WHERE te.page_id = p.id
) THEN true ELSE false END AS stale
FROM content_chunks cc
JOIN pages p ON p.id = cc.page_id
JOIN sources s ON s.id = p.source_id
WHERE cc.search_vector @@ websearch_to_tsquery('${ftsLang}', $1) ${detailFilter}${extraFilter} ${hardExcludeClause} ${visibilityClause}
WHERE cc.search_vector @@ ${ftsQueryExpr} ${detailFilter}${extraFilter} ${hardExcludeClause} ${visibilityClause}
-- v0.27.1: hide image rows from default text-keyword search so
-- OCR text doesn't drown text-page hits. Image-similarity queries
-- run a separate vector path on embedding_image.
@@ -1712,7 +1715,10 @@ export class PGLiteEngine implements BrainEngine {
// FTS config name (e.g. 'english', 'pt_br'). Validated by getFtsLanguage()
// — safe to interpolate into raw SQL.
const ftsLang = getFtsLanguage();
const ftsQueryExpr = buildWebsearchQueryExpr(ftsLang, '$1', query);
// #2380: slash-bearing queries match both the split-word and literal
// slash forms — see buildWebsearchQueryExpr in ./search/sql-ranking.ts.
const params: unknown[] = [query, limit, offset];
let extraFilter = '';
if (opts?.type) {
@@ -1760,7 +1766,7 @@ export class PGLiteEngine implements BrainEngine {
COALESCE(rep.chunk_index, 0) as chunk_index,
COALESCE(rep.chunk_text, '') as chunk_text,
COALESCE(rep.chunk_source, 'compiled_truth') as chunk_source,
ts_rank_cd(p.search_vector, websearch_to_tsquery('${ftsLang}', $1)) * ${sourceFactorCase} AS score,
ts_rank_cd(p.search_vector, ${ftsQueryExpr}) * ${sourceFactorCase} AS score,
CASE WHEN p.updated_at < (
SELECT MAX(te.created_at) FROM timeline_entries te WHERE te.page_id = p.id
) THEN true ELSE false END AS stale
@@ -1775,7 +1781,7 @@ export class PGLiteEngine implements BrainEngine {
ORDER BY (cc.chunk_source = 'compiled_truth') DESC, cc.chunk_index ASC
LIMIT 1
) rep ON true
WHERE p.search_vector @@ websearch_to_tsquery('${ftsLang}', $1)
WHERE p.search_vector @@ ${ftsQueryExpr}
${extraFilter} ${hardExcludeClause} ${visibilityClause}
ORDER BY score DESC, p.id ASC
LIMIT $2 OFFSET $3`;
@@ -1962,6 +1968,8 @@ export class PGLiteEngine implements BrainEngine {
});
}
// #2380: slash-bearing queries match both the split-word and literal
// slash forms — see buildWebsearchQueryExpr in ./search/sql-ranking.ts.
const params: unknown[] = [query, limit, offset];
let extraFilter = '';
if (opts?.language) {
@@ -1996,20 +2004,21 @@ export class PGLiteEngine implements BrainEngine {
// FTS config name (e.g. 'english', 'pt_br'). Validated by getFtsLanguage()
// — safe to interpolate into raw SQL.
const ftsLang = getFtsLanguage();
const ftsQueryExpr = buildWebsearchQueryExpr(ftsLang, '$1', query);
const { rows } = await this.db.query(
`SELECT
p.slug, p.id as page_id, p.title, p.type, p.source_id,
p.effective_date, p.effective_date_source,
cc.id as chunk_id, cc.chunk_index, cc.chunk_text, cc.chunk_source,
ts_rank(cc.search_vector, websearch_to_tsquery('${ftsLang}', $1)) * ${sourceFactorCase} AS score,
ts_rank(cc.search_vector, ${ftsQueryExpr}) * ${sourceFactorCase} AS score,
CASE WHEN p.updated_at < (
SELECT MAX(te.created_at) FROM timeline_entries te WHERE te.page_id = p.id
) THEN true ELSE false END AS stale
FROM content_chunks cc
JOIN pages p ON p.id = cc.page_id
JOIN sources s ON s.id = p.source_id
WHERE cc.search_vector @@ websearch_to_tsquery('${ftsLang}', $1) ${detailFilter}${extraFilter} ${hardExcludeClause} ${visibilityClause}
WHERE cc.search_vector @@ ${ftsQueryExpr} ${detailFilter}${extraFilter} ${hardExcludeClause} ${visibilityClause}
ORDER BY score DESC
LIMIT $2 OFFSET $3`,
params
+16 -7
View File
@@ -64,7 +64,7 @@ import { ConnectionManager } from './connection-manager.ts';
import { logConnectionEvent } from './connection-audit.ts';
import { validateSlug, contentHash, rowToPage, rowToStalePage, rowToChunk, rowToSearchResult, parseEmbedding, tryParseEmbedding, takeRowToTake, takeHitRowToHit, isUndefinedTableError, warnOncePerProcess } from './utils.ts';
import { resolveBoostMap, resolveHardExcludes } from './search/source-boost.ts';
import { buildSourceFactorCase, buildHardExcludeClause, buildVisibilityClause, buildRecencyComponentSql, buildBestPerPagePoolCte, buildOrFallbackWebsearchQuery } from './search/sql-ranking.ts';
import { buildSourceFactorCase, buildHardExcludeClause, buildVisibilityClause, buildRecencyComponentSql, buildBestPerPagePoolCte, buildOrFallbackWebsearchQuery, buildWebsearchQueryExpr } from './search/sql-ranking.ts';
import { DEFAULT_EMBEDDING_MODEL, DEFAULT_EMBEDDING_DIMENSIONS } from './ai/defaults.ts';
import { DELETE_BATCH_SIZE } from './engine-constants.ts';
@@ -1691,6 +1691,8 @@ export class PostgresEngine implements BrainEngine {
const hardExcludePrefixes = resolveHardExcludes(opts?.exclude_slug_prefixes, opts?.include_slug_prefixes);
const hardExcludeClause = buildHardExcludeClause('p.slug', hardExcludePrefixes);
// #2380: slash-bearing queries match both the split-word and literal
// slash forms — see buildWebsearchQueryExpr in ./search/sql-ranking.ts.
const params: unknown[] = [query];
let typeClause = '';
if (type) {
@@ -1761,6 +1763,7 @@ export class PostgresEngine implements BrainEngine {
// FTS config name (e.g. 'english', 'pt_br'). Validated by getFtsLanguage()
// — safe to interpolate into raw SQL.
const ftsLang = getFtsLanguage();
const ftsQueryExpr = buildWebsearchQueryExpr(ftsLang, '$1', query);
const rawQuery = `
WITH ranked_chunks AS (
@@ -1768,11 +1771,11 @@ export class PostgresEngine implements BrainEngine {
p.slug, p.id as page_id, p.title, p.type, p.source_id,
p.effective_date, p.effective_date_source,
cc.id as chunk_id, cc.chunk_index, cc.chunk_text, cc.chunk_source,
ts_rank(cc.search_vector, websearch_to_tsquery('${ftsLang}', $1)) * ${sourceFactorCase} AS score
ts_rank(cc.search_vector, ${ftsQueryExpr}) * ${sourceFactorCase} AS score
FROM content_chunks cc
JOIN pages p ON p.id = cc.page_id
JOIN sources s ON s.id = p.source_id
WHERE cc.search_vector @@ websearch_to_tsquery('${ftsLang}', $1)
WHERE cc.search_vector @@ ${ftsQueryExpr}
${typeClause}
${typesClause}
${excludeSlugsClause}
@@ -1863,7 +1866,10 @@ export class PostgresEngine implements BrainEngine {
// FTS config name (e.g. 'english', 'pt_br'). Validated by getFtsLanguage()
// — safe to interpolate into raw SQL.
const ftsLang = getFtsLanguage();
const ftsQueryExpr = buildWebsearchQueryExpr(ftsLang, '$1', query);
// #2380: slash-bearing queries match both the split-word and literal
// slash forms — see buildWebsearchQueryExpr in ./search/sql-ranking.ts.
const params: unknown[] = [query];
let typeClause = '';
if (opts?.type) {
@@ -1923,7 +1929,7 @@ export class PostgresEngine implements BrainEngine {
COALESCE(rep.chunk_index, 0) as chunk_index,
COALESCE(rep.chunk_text, '') as chunk_text,
COALESCE(rep.chunk_source, 'compiled_truth') as chunk_source,
ts_rank_cd(p.search_vector, websearch_to_tsquery('${ftsLang}', $1)) * ${sourceFactorCase} AS score,
ts_rank_cd(p.search_vector, ${ftsQueryExpr}) * ${sourceFactorCase} AS score,
false AS stale
FROM pages p
JOIN sources s ON s.id = p.source_id
@@ -1936,7 +1942,7 @@ export class PostgresEngine implements BrainEngine {
ORDER BY (cc.chunk_source = 'compiled_truth') DESC, cc.chunk_index ASC
LIMIT 1
) rep ON true
WHERE p.search_vector @@ websearch_to_tsquery('${ftsLang}', $1)
WHERE p.search_vector @@ ${ftsQueryExpr}
${typeClause}
${typesClause}
${excludeSlugsClause}
@@ -2000,6 +2006,8 @@ export class PostgresEngine implements BrainEngine {
const hardExcludePrefixes = resolveHardExcludes(opts?.exclude_slug_prefixes, opts?.include_slug_prefixes);
const hardExcludeClause = buildHardExcludeClause('p.slug', hardExcludePrefixes);
// #2380: slash-bearing queries match both the split-word and literal
// slash forms — see buildWebsearchQueryExpr in ./search/sql-ranking.ts.
const params: unknown[] = [query];
let typeClause = '';
if (type) {
@@ -2060,18 +2068,19 @@ export class PostgresEngine implements BrainEngine {
// FTS config name (e.g. 'english', 'pt_br'). Validated by getFtsLanguage()
// — safe to interpolate into raw SQL.
const ftsLang = getFtsLanguage();
const ftsQueryExpr = buildWebsearchQueryExpr(ftsLang, '$1', query);
const rawQuery = `
SELECT
p.slug, p.id as page_id, p.title, p.type, p.source_id,
p.effective_date, p.effective_date_source,
cc.id as chunk_id, cc.chunk_index, cc.chunk_text, cc.chunk_source,
ts_rank(cc.search_vector, websearch_to_tsquery('${ftsLang}', $1)) * ${sourceFactorCase} AS score,
ts_rank(cc.search_vector, ${ftsQueryExpr}) * ${sourceFactorCase} AS score,
false AS stale
FROM content_chunks cc
JOIN pages p ON p.id = cc.page_id
JOIN sources s ON s.id = p.source_id
WHERE cc.search_vector @@ websearch_to_tsquery('${ftsLang}', $1)
WHERE cc.search_vector @@ ${ftsQueryExpr}
${typeClause}
${typesClause}
${excludeSlugsClause}
+22
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@@ -251,6 +251,28 @@ export function buildOrFallbackWebsearchQuery(query: string): string | null {
return tokens.join(' OR ');
}
/**
* #2380: FTS query expression for slash-bearing queries. Postgres' default
* text-search parser classifies `foo/bar` as a single `file`-alias lexeme —
* on BOTH the query side and the index side. So a raw `foo/bar` query only
* matched documents carrying the identical joined lexeme (literal paths),
* and a slash-split query only matches documents whose text had the words
* separated. Neither form alone covers both document shapes; OR the two
* parses so a slash query matches prose ("foo and bar", stemmed, AND
* semantics) AND literal slash forms ("src/core/x.ts") alike.
*
* Slash-free queries return the plain single-parse expression — byte-
* identical SQL and identical ts_rank to the historical behavior.
*
* `ftsLang` is validated by getFtsLanguage() (safe to interpolate);
* `param` is a `$N` placeholder, never user text.
*/
export function buildWebsearchQueryExpr(ftsLang: string, param: string, query: string): string {
const plain = `websearch_to_tsquery('${ftsLang}', ${param})`;
if (!query.includes('/')) return plain;
return `(websearch_to_tsquery('${ftsLang}', translate(${param}, '/', ' ')) || ${plain})`;
}
// ============================================================
// v0.29.1 — Recency component SQL builder
// ============================================================
@@ -28,8 +28,8 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
resetGateway();
});
test('Ollama, LiteLLM, llama-server all declare no_batch_cap: true', () => {
for (const id of ['ollama', 'litellm', 'llama-server']) {
test('LiteLLM and llama-server declare no_batch_cap: true', () => {
for (const id of ['litellm', 'llama-server']) {
const r = getRecipe(id);
expect(r, `${id} not registered`).toBeDefined();
expect(
@@ -39,6 +39,18 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
}
});
test('#2552: Ollama declares a conservative static batch cap, not no_batch_cap', () => {
// A CPU-only Ollama box wedges when a whole page ships in one request;
// Ollama never returns a token-limit error so the recursive-halving
// safety net can't fire. The pre-split cap is the only guard.
const r = getRecipe('ollama');
expect(r).toBeDefined();
const e = r!.touchpoints.embedding!;
expect(e.no_batch_cap).toBeUndefined();
expect(e.max_batch_tokens).toBe(4096);
expect(e.chars_per_token).toBe(2);
});
test('configureGateway does NOT warn for ollama/litellm/llama-server', () => {
warnSpy.mockClear();
resetGateway();
+118
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@@ -0,0 +1,118 @@
/**
* #2552: cloud-tuned embedding defaults silently wedge CPU-only local
* endpoints (Ollama). Three-part fix under test:
*
* 1. `isLocalEmbeddingEndpoint()` — gateway helper detecting local
* inference servers (ollama / llama-server recipes, localhost base URL).
* 2. `resolveEmbedConcurrency()` — embed auto-caps the 20-worker fan-out
* at LOCAL_EMBED_CONCURRENCY_CAP for local endpoints unless the
* operator set GBRAIN_EMBED_CONCURRENCY explicitly.
* 3. `computeEmbedConcurrencyCheck()` — doctor warns when an explicit env
* override fans out against a local endpoint.
*
* Serial: mutates process.env and the module-global gateway config.
*/
import { afterAll, afterEach, describe, expect, test } from 'bun:test';
import {
configureGateway,
resetGateway,
isLocalEmbeddingEndpoint,
LOCAL_EMBED_CONCURRENCY_CAP,
} from '../src/core/ai/gateway.ts';
import { resolveEmbedConcurrency } from '../src/commands/embed.ts';
import { computeEmbedConcurrencyCheck } from '../src/commands/doctor.ts';
const SAVED_ENV = process.env.GBRAIN_EMBED_CONCURRENCY;
afterEach(() => {
resetGateway();
if (SAVED_ENV === undefined) delete process.env.GBRAIN_EMBED_CONCURRENCY;
else process.env.GBRAIN_EMBED_CONCURRENCY = SAVED_ENV;
});
afterAll(() => {
resetGateway();
});
describe('#2552 isLocalEmbeddingEndpoint', () => {
test('false when the gateway is not configured (fail-open to cloud behavior)', () => {
resetGateway();
expect(isLocalEmbeddingEndpoint()).toBe(false);
});
test('true for the ollama recipe', () => {
configureGateway({ embedding_model: 'ollama:nomic-embed-text', env: {} });
expect(isLocalEmbeddingEndpoint()).toBe(true);
});
test('true for the llama-server recipe', () => {
configureGateway({ embedding_model: 'llama-server:my-gguf', env: {} });
expect(isLocalEmbeddingEndpoint()).toBe(true);
});
test('false for a cloud recipe', () => {
configureGateway({
embedding_model: 'openai:text-embedding-3-small',
env: { OPENAI_API_KEY: 'fake' },
});
expect(isLocalEmbeddingEndpoint()).toBe(false);
});
test('true when a cloud recipe base URL is explicitly pointed at localhost', () => {
configureGateway({
embedding_model: 'openai:text-embedding-3-small',
env: { OPENAI_API_KEY: 'fake' },
base_urls: { openai: 'http://localhost:8080/v1' },
});
expect(isLocalEmbeddingEndpoint()).toBe(true);
});
});
describe('#2552 resolveEmbedConcurrency', () => {
test('caps at LOCAL_EMBED_CONCURRENCY_CAP for a local endpoint when env is unset', () => {
delete process.env.GBRAIN_EMBED_CONCURRENCY;
configureGateway({ embedding_model: 'ollama:nomic-embed-text', env: {} });
expect(resolveEmbedConcurrency()).toBe(LOCAL_EMBED_CONCURRENCY_CAP);
});
test('explicit env override always wins, even against a local endpoint', () => {
process.env.GBRAIN_EMBED_CONCURRENCY = '10';
configureGateway({ embedding_model: 'ollama:nomic-embed-text', env: {} });
expect(resolveEmbedConcurrency()).toBe(10);
});
test('cloud endpoints keep the historical default of 20', () => {
delete process.env.GBRAIN_EMBED_CONCURRENCY;
configureGateway({ env: { OPENAI_API_KEY: 'fake' } });
expect(resolveEmbedConcurrency()).toBe(20);
});
test('pacing only ever lowers concurrency', () => {
delete process.env.GBRAIN_EMBED_CONCURRENCY;
configureGateway({ embedding_model: 'ollama:nomic-embed-text', env: {} });
expect(resolveEmbedConcurrency(1)).toBe(1);
expect(resolveEmbedConcurrency(16)).toBe(LOCAL_EMBED_CONCURRENCY_CAP);
});
});
describe('#2552 computeEmbedConcurrencyCheck (doctor)', () => {
test('ok for non-local endpoints', () => {
expect(computeEmbedConcurrencyCheck(false, '20', 2).status).toBe('ok');
});
test('warn when an explicit override exceeds the local cap', () => {
const check = computeEmbedConcurrencyCheck(true, '20', 2);
expect(check.status).toBe('warn');
expect(check.message).toContain('GBRAIN_EMBED_CONCURRENCY=20');
});
test('ok when env is unset against a local endpoint (auto-cap applies)', () => {
expect(computeEmbedConcurrencyCheck(true, undefined, 2).status).toBe('ok');
});
test('ok when the override is at or under the cap', () => {
expect(computeEmbedConcurrencyCheck(true, '2', 2).status).toBe('ok');
expect(computeEmbedConcurrencyCheck(true, '1', 2).status).toBe('ok');
});
});
-27
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@@ -389,33 +389,6 @@ describe('resolveSlugAll', () => {
});
});
// ─── issue #1964: cross-directory wikilinks — slug/path mismatch ──────────
describe('issue #1964: raw Obsidian wikilink paths resolve to sync-slugified slugs', () => {
test('resolveSlug slugifies the candidate (sync-consistent), no flag needed', () => {
const all = new Set(['llm-wiki/entities/ai-3.0']);
// Wikilink literal `[[llm-wiki/entities/AI 3.0]]` — spaces + uppercase.
expect(resolveSlug('llm-wiki/notes', 'llm-wiki/entities/AI 3.0.md', all))
.toBe('llm-wiki/entities/ai-3.0');
});
test('resolveSlug slugifies raw (unslugified) fileDir too', () => {
const all = new Set(['llm-wiki/entities/ai-3.0']);
// fileDir comes from dirname(relPath) — the raw on-disk directory.
expect(resolveSlug('LLM Wiki/Notes', 'entities/AI 3.0.md', all))
.toBe('llm-wiki/entities/ai-3.0');
});
test('extractLinksFromFile resolves cross-directory wikilink with flag OFF as a typed edge', async () => {
const allSlugs = new Set(['llm-wiki/entities/ai-3.0', 'llm-wiki/notes/roadmap']);
const content = '---\ntitle: Roadmap\ntype: concept\n---\n\nSee [[llm-wiki/entities/AI 3.0]].\n';
const links = await extractLinksFromFile(content, 'llm-wiki/notes/roadmap.md', allSlugs);
expect(links.map(l => l.to_slug)).toEqual(['llm-wiki/entities/ai-3.0']);
// Dir-qualified path resolution is exact, NOT the basename fallback.
expect(links[0].link_type).not.toBe('wikilink_basename');
});
});
describe('issue #972 repro: bare wikilinks resolve when flag is on', () => {
// End-to-end: reproduces the issue's exact repro inside a tempdir +
// PGLite, then asserts edge count under both flag states.
-42
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@@ -9,8 +9,6 @@ import {
parseTimelineEntries,
isAutoLinkEnabled,
FRONTMATTER_LINK_MAP,
buildBasenameIndex,
queryBasenameIndex,
type SlugResolver,
} from '../src/core/link-extraction.ts';
import type { BrainEngine } from '../src/core/engine.ts';
@@ -426,46 +424,6 @@ describe('extractPageLinks', () => {
expect(strk!.linkType).toBe('wikilink_basename');
});
// ─── issue #1964: dir-qualified wikilinks with raw Obsidian paths ────────
test('#1964: dir-qualified wikilink resolves via sync-consistent slugification (flag OFF)', async () => {
// `[[llm-wiki/entities/AI 3.0]]` is a raw Obsidian path; the page slug
// is the sync-slugified `llm-wiki/entities/ai-3.0`. Must resolve WITHOUT
// global_basename (it's dir-qualified) and must NOT leak to a same-tail
// page in a different directory.
const resolver: SlugResolver = {
resolve: async () => null,
resolveBasenameMatches: async (name) =>
name === 'ai-3.0' ? ['other/ai-3.0', 'llm-wiki/entities/ai-3.0'] : [],
};
const { candidates } = await extractPageLinks(
'llm-wiki/notes/roadmap',
'See [[llm-wiki/entities/AI 3.0]] for the model.',
{}, 'concept', resolver,
// opts.globalBasename omitted (= false) — path is dir-qualified
);
expect(candidates.map(c => c.targetSlug)).toEqual(['llm-wiki/entities/ai-3.0']);
expect(candidates[0].linkType).toBe('wikilink_basename');
expect(candidates[0].linkSource).toBe('wikilink-resolved');
});
test('#1964: path-suffix match resolves wiki-root-relative paths against a real index', async () => {
// Author writes `[[llm-wiki/entities/AI 3.0]]` but the brain nests the
// wiki under a vault dir. Suffix match rescues it; queried through the
// REAL basename index so the tail-key lookup is exercised end to end.
const idx = buildBasenameIndex(['vault/llm-wiki/entities/ai-3.0', 'people/ai-3.0']);
const resolver: SlugResolver = {
resolve: async () => null,
resolveBasenameMatches: async (name) => queryBasenameIndex(idx, name),
};
const { candidates } = await extractPageLinks(
'vault/llm-wiki/notes/roadmap',
'See [[llm-wiki/entities/AI 3.0]].',
{}, 'concept', resolver,
);
expect(candidates.map(c => c.targetSlug)).toEqual(['vault/llm-wiki/entities/ai-3.0']);
});
test('opts.skipFrontmatter suppresses the frontmatter pass', async () => {
// Real resolver shape that WOULD resolve frontmatter source: too,
// but skipFrontmatter blocks the path entirely.
+61
View File
@@ -216,6 +216,67 @@ describe('PGLiteEngine: Search', () => {
expect(results.length).toBe(0);
});
// Regression (#2380): queries containing `/` used to bypass FTS AND
// semantics. Postgres' default text-search parser classifies `foo/bar` as
// a `file`-alias token mapped to the `simple` dictionary, so it became a
// single un-stemmed lexeme `'foo/bar'` that never matches indexed text —
// the primary FTS pass returned 0 and the OR fallback took over, matching
// pages that contain EITHER term. searchKeyword/searchTitles now normalize
// `/` to whitespace before websearch_to_tsquery parses, so the primary
// AND pass matches directly.
test('searchKeyword: slash query matches with AND semantics, not OR fallback', async () => {
// Decoy shares only ONE of the two query terms ('enterprise').
await engine.putPage('concepts/enterprise-pricing', {
type: 'concept', title: 'Widget Pricing',
compiled_truth: 'Enterprise pricing for widgets.',
});
await engine.upsertChunks('concepts/enterprise-pricing', [
{ chunk_index: 0, chunk_text: 'Enterprise pricing for widgets', chunk_source: 'compiled_truth' },
]);
// Both terms co-occur only in the novamind chunk. Pre-fix this returned
// BOTH pages (primary pass zero-hit → OR fallback); post-fix the primary
// AND pass returns exactly the co-occurrence page.
const results = await engine.searchKeyword('NovaMind/enterprise');
expect(results.length).toBe(1);
expect(results[0].slug).toBe('companies/novamind');
});
test('searchTitles: slash query matches with AND semantics, not OR fallback', async () => {
await engine.putPage('companies/novamind-enterprise', {
type: 'company', title: 'NovaMind Enterprise Platform',
compiled_truth: 'Placeholder body.',
});
await engine.putPage('guides/enterprise-sales', {
type: 'concept', title: 'Enterprise Sales Guide',
compiled_truth: 'Placeholder body.',
});
// Pre-fix: `NovaMind/Enterprise` parsed as one file-alias lexeme → the
// primary title pass returned 0 and the OR fallback matched BOTH titles.
const results = await engine.searchTitles('NovaMind/Enterprise');
expect(results.length).toBe(1);
expect(results[0].slug).toBe('companies/novamind-enterprise');
});
test('searchKeyword: slash query still matches the literal slash form (file paths)', async () => {
// The INDEX side also emits the joined file-alias lexeme for literal
// `foo/bar` text, so a query normalized to split words alone would go
// blind to documents containing the literal slash form (paths, URLs).
// buildWebsearchQueryExpr ORs both parses; this pins the raw arm.
await engine.putPage('runbooks/widget-deploy', {
type: 'concept', title: 'Widget Deploy Runbook',
compiled_truth: 'Runbook for the acme/widget deployment pipeline.',
});
await engine.upsertChunks('runbooks/widget-deploy', [
{ chunk_index: 0, chunk_text: 'Runbook for the acme/widget deployment pipeline', chunk_source: 'compiled_truth' },
]);
const results = await engine.searchKeyword('acme/widget');
expect(results.length).toBe(1);
expect(results[0].slug).toBe('runbooks/widget-deploy');
});
test('tsvector trigger populates search_vector on insert', async () => {
// Verify the PL/pgSQL trigger fires and content_chunks.search_vector is
// populated from chunk_text. v0.20.0 Cathedral II Layer 3 moved FTS from