v0.42.66.1 fix: honor pgvector HNSW dimension limits (#3440)

* fix(doctor): honor pgvector HNSW dimension limits

* fix(ci): stabilize local Docker verification

* chore: bump version and changelog (v0.42.66.1)

Co-Authored-By: OpenAI Codex <noreply@openai.com>

---------

Co-authored-by: OpenAI Codex <noreply@openai.com>

CHANGELOG.md

@@ -2,6 +2,13 @@
 
 All notable changes to GBrain will be documented in this file.
 
+## [0.42.66.1] - 2026-07-27
+
+### Fixed
+
+- `gbrain doctor` now treats embedding columns wider than pgvector's HNSW limit as healthy exact-scan configurations instead of prescribing an index PostgreSQL cannot build.
+- Local CI now passes an empty Docker mount list correctly and compiles the embedded-WASM smoke binary from container-local storage on Docker Desktop.
+
 ## [0.42.66.0] - 2026-07-24
 
 **54 verified fixes from the community backlog: background enrichment stops wasting money on dead pages, autopilot stops killing its own healthy runs, and search respects your settings.**

VERSION

@@ -1 +1 @@
-0.42.66.0
+0.42.66.1

docs/architecture/KEY_FILES.md

@@ -502,3 +502,5 @@ T1.5 wiring is partial in v0.40.7.0. Three follow-ups filed in TODOS.md under
 union widening (`'person' | 'company'` → `string`), facts/eligibility.ts
 pack-aware `ELIGIBLE_TYPES` wiring, and 3 doctor checks (schema_pack_coverage,
 schema_pack_writability, schema_pack_mutation_audit).
+
+- `src/core/vector-index.ts` + `src/commands/doctor.ts:embedding_column_registry` — shared pgvector HNSW eligibility policy. `hnswIndexExpected(columnType, dims)` derives the answer from the canonical `vector`/`halfvec` dimension caps already used by migration index generation. Doctor reports an HNSW-less active embedding column as a healthy exact-scan configuration when its declared width exceeds the applicable pgvector cap, and only emits the index repair recipe when an index is actually supported. Pinned at both cap boundaries by `test/vector-index-lifecycle.test.ts`.

package.json

@@ -144,7 +144,7 @@
     "bun": ">=1.3.10"
   },
   "license": "MIT",
-  "version": "0.42.66.0",
+  "version": "0.42.66.1",
   "overrides": {
     "@hono/node-server": "^2.0.5",
     "fast-uri": "^3.1.4",

scripts/check-wasm-embedded.sh

@@ -19,13 +19,25 @@ set -euo pipefail
 REPO_ROOT="$(cd "$(dirname "$0")/.." && pwd)"
 cd "$REPO_ROOT"
 
-OUT_BIN="$(mktemp /tmp/gbrain-wasm-check.XXXXXX)"
-trap 'rm -f "$OUT_BIN"' EXIT
+# Build from a container-local copy. On Docker Desktop, Bun canonicalizes a
+# bind-mounted input to /run/host_virtiofs but keeps /app as the output path;
+# its final atomic rename then fails with ENOENT even though both names refer
+# to the same mount. Keeping inputs and output under /tmp avoids that alias.
+BUILD_DIR="$(mktemp -d /tmp/gbrain-wasm-check.XXXXXX)"
+OUT_BIN="$BUILD_DIR/chunker-smoketest"
+trap 'rm -rf "$BUILD_DIR"' EXIT
+mkdir -p "$BUILD_DIR/scripts"
+cp -R "$REPO_ROOT/src" "$BUILD_DIR/src"
+cp "$REPO_ROOT/scripts/chunker-smoketest.ts" "$BUILD_DIR/scripts/chunker-smoketest.ts"
+ln -s "$REPO_ROOT/node_modules" "$BUILD_DIR/node_modules"
 
 # Build a minimal smoketest binary that imports the chunker. We compile this
 # instead of the full gbrain CLI so the failure mode is laser-focused on
 # chunker + WASM path resolution, not unrelated CLI wiring.
-bun build --compile --outfile "$OUT_BIN" scripts/chunker-smoketest.ts >/dev/null 2>&1
+if ! (cd "$BUILD_DIR" && bun build --compile --outfile "$OUT_BIN" scripts/chunker-smoketest.ts >/dev/null); then
+  echo "[check-wasm-embedded] FAIL: bun could not compile the smoketest binary." >&2
+  exit 1
+fi
 
 # Run it and capture JSON output.
 OUTPUT="$("$OUT_BIN" 2>&1)"

scripts/ci-local.sh

@@ -350,7 +350,7 @@ if [ -f .git ]; then
 fi
 
 echo "[ci-local] Running checks inside runner container..."
-docker compose -f "$COMPOSE_FILE" run --rm "${EXTRA_MOUNTS[@]:-}" runner bash -c "$INNER_CMD"
+docker compose -f "$COMPOSE_FILE" run --rm "${EXTRA_MOUNTS[@]}" runner bash -c "$INNER_CMD"
 
 echo ""
 echo "[ci-local] All checks passed."

src/commands/doctor.ts

@@ -52,6 +52,7 @@ import { isUndefinedColumnError } from '../core/utils.ts';
 // drift from what search actually filters.
 import { resolveHardExcludes, DEFAULT_HARD_EXCLUDES } from '../core/search/source-boost.ts';
 import { escapeLikePattern, buildVisibilityClause } from '../core/search/sql-ranking.ts';
+import { hnswIndexExpected, hnswMaxDimsForType } from '../core/vector-index.ts';
 
 export interface Check {
   name: string;
@@ -6147,6 +6148,12 @@ export async function buildChecks(
           continue;
         }
         if (engine.kind === 'postgres' && haveIndex.get(colName) === false) {
+          if (!hnswIndexExpected(entry.type, entry.dimensions)) {
+            okColumns.push(
+              `${colName} (exact scan: ${entry.type}(${entry.dimensions}) exceeds HNSW cap ${hnswMaxDimsForType(entry.type)})`,
+            );
+            continue;
+          }
           issues.push(
             `${colName}: no HNSW index. Search works but uses sequential scan. ` +
               `Fix: CREATE INDEX IF NOT EXISTS idx_chunks_${colName} ON content_chunks USING hnsw (${quoteIdentifier(colName)} ${entry.type}_cosine_ops);`,

src/core/vector-index.ts

@@ -34,6 +34,11 @@ export function hnswMaxDimsForType(columnType: 'vector' | 'halfvec'): number {
   return columnType === 'halfvec' ? PGVECTOR_HNSW_HALFVEC_MAX_DIMS : PGVECTOR_HNSW_VECTOR_MAX_DIMS;
 }
 
+/** Whether pgvector can build an HNSW index for this exact column shape. */
+export function hnswIndexExpected(columnType: 'vector' | 'halfvec', dims: number): boolean {
+  return dims <= hnswMaxDimsForType(columnType);
+}
+
 export function applyChunkEmbeddingIndexPolicy(sql: string, dims: number): string {
   return sql.replaceAll(CHUNK_EMBEDDING_HNSW_INDEX, chunkEmbeddingIndexSql(dims));
 }

test/vector-index-lifecycle.test.ts

@@ -3,6 +3,8 @@ import {
   chunkEmbeddingIndexSql,
   applyChunkEmbeddingIndexPolicy,
   PGVECTOR_HNSW_VECTOR_MAX_DIMS,
+  PGVECTOR_HNSW_HALFVEC_MAX_DIMS,
+  hnswIndexExpected,
   checkActiveBuild,
   dropZombieIndexes,
   dropAndRebuild,
@@ -32,6 +34,15 @@ describe('chunkEmbeddingIndexSql — pre-v0.30.1 contract', () => {
   });
 });
 
+describe('hnswIndexExpected', () => {
+  test('matches pgvector caps for vector and halfvec columns', () => {
+    expect(hnswIndexExpected('vector', PGVECTOR_HNSW_VECTOR_MAX_DIMS)).toBe(true);
+    expect(hnswIndexExpected('vector', PGVECTOR_HNSW_VECTOR_MAX_DIMS + 1)).toBe(false);
+    expect(hnswIndexExpected('halfvec', PGVECTOR_HNSW_HALFVEC_MAX_DIMS)).toBe(true);
+    expect(hnswIndexExpected('halfvec', PGVECTOR_HNSW_HALFVEC_MAX_DIMS + 1)).toBe(false);
+  });
+});
+
 describe('applyChunkEmbeddingIndexPolicy', () => {
   test('replaces the canonical index SQL', () => {
     const input = `BEFORE\nCREATE INDEX IF NOT EXISTS idx_chunks_embedding ON content_chunks USING hnsw (embedding vector_cosine_ops);\nAFTER`;