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Author SHA1 Message Date
fd7a85a56d fix(backlinks): honor positional check-backlinks directory argument
The help text (gbrain check-backlinks <check|fix> [dir]) promised a
positional directory argument, but runBacklinks only parsed --dir and
defaulted to cwd, so the walker ran from the wrong root and could hit
EPERM on unreadable sibling dirs.

Extract parseBacklinksArgs: positional [dir] is now honored, --dir still
overrides it, --dry-run preserved, and a --dir flag missing its value
falls back to the positional dir instead of picking up undefined.

Takeover of #852 (rebased onto master past the findBacklinkGaps dedupe
test block). Fixes #485.

Co-authored-by: Kage18 <Kage18@users.noreply.github.com>
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-21 14:19:35 -07:00
9 changed files with 66 additions and 151 deletions
+40 -8
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@@ -5,8 +5,8 @@
* checks if back-links exist, and optionally creates them.
*
* Usage:
* gbrain check-backlinks check [--dir <brain-dir>] # report missing back-links
* gbrain check-backlinks fix [--dir <brain-dir>] # create missing back-links
* gbrain check-backlinks check [dir] [--dir <brain-dir>] # report missing back-links
* gbrain check-backlinks fix [dir] [--dir <brain-dir>] # create missing back-links
* gbrain check-backlinks fix --dry-run # preview fixes
*/
@@ -201,6 +201,40 @@ export interface BacklinksResult {
dryRun: boolean;
}
export interface ParsedBacklinksArgs {
subcommand: string | undefined;
brainDir: string;
dryRun: boolean;
}
export function parseBacklinksArgs(args: string[]): ParsedBacklinksArgs {
const subcommand = args[0];
const dryRun = args.includes('--dry-run');
const dirIdx = args.indexOf('--dir');
const flagDir = dirIdx >= 0 && args[dirIdx + 1] && !args[dirIdx + 1].startsWith('--')
? args[dirIdx + 1]
: undefined;
let positionalDir: string | undefined;
for (let i = 1; i < args.length; i++) {
const arg = args[i];
if (arg === '--dir') {
i++;
continue;
}
if (arg === '--dry-run') continue;
if (arg.startsWith('--')) continue;
positionalDir = arg;
break;
}
return {
subcommand,
brainDir: flagDir ?? positionalDir ?? '.',
dryRun,
};
}
/**
* Library-level backlinks check/fix. Throws on validation errors; returns a
* structured result so Minions handlers + autopilot-cycle can surface counts.
@@ -236,16 +270,14 @@ export async function runBacklinksCore(opts: BacklinksOpts): Promise<BacklinksRe
}
export async function runBacklinks(args: string[]) {
const subcommand = args[0];
const dirIdx = args.indexOf('--dir');
const brainDir = dirIdx >= 0 ? args[dirIdx + 1] : '.';
const dryRun = args.includes('--dry-run');
const { subcommand, brainDir, dryRun } = parseBacklinksArgs(args);
if (!subcommand || !['check', 'fix'].includes(subcommand)) {
console.error('Usage: gbrain check-backlinks <check|fix> [--dir <brain-dir>] [--dry-run]');
console.error('Usage: gbrain check-backlinks <check|fix> [dir] [--dir <brain-dir>] [--dry-run]');
console.error(' check Report missing back-links');
console.error(' fix Create missing back-links (appends to Timeline)');
console.error(' --dir Brain directory (default: current directory)');
console.error(' dir Brain directory (default: current directory)');
console.error(' --dir Brain directory override');
console.error(' --dry-run Preview fixes without writing');
process.exit(1);
}
+1 -14
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@@ -1,5 +1,5 @@
import type { BrainEngine } from '../core/engine.ts';
import { embedBatch, currentEmbeddingSignature, resolveEmbeddingModelLabel } from '../core/embedding.ts';
import { embedBatch, currentEmbeddingSignature } from '../core/embedding.ts';
import type { ChunkInput } from '../core/types.ts';
import { chunkText } from '../core/chunkers/recursive.ts';
import { createProgress, type ProgressReporter } from '../core/progress.ts';
@@ -581,16 +581,11 @@ async function embedPage(
for (let j = 0; j < toEmbed.length; j++) {
embeddingMap.set(toEmbed[j].chunk_index, embeddings[j]);
}
// #1717: label each (re)embedded chunk with the model that actually
// produced its vector. Preserved chunks (not re-embedded this pass) keep
// their existing model so a mixed-model page isn't relabeled wholesale.
const embedModelLabel = resolveEmbeddingModelLabel();
const updated: ChunkInput[] = chunks.map(c => ({
chunk_index: c.chunk_index,
chunk_text: c.chunk_text,
chunk_source: c.chunk_source,
embedding: embeddingMap.get(c.chunk_index),
model: embeddingMap.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
}));
@@ -722,16 +717,12 @@ async function embedAll(
for (let j = 0; j < toEmbed.length; j++) {
embeddingMap.set(toEmbed[j].chunk_index, embeddings[j]);
}
// #1717: stamp the resolved embedding model on (re)embedded chunks;
// preserve the existing model on chunks left untouched.
const embedModelLabel = resolveEmbeddingModelLabel();
// Preserve ALL chunks, only update embeddings for stale ones
const updated: ChunkInput[] = chunks.map(c => ({
chunk_index: c.chunk_index,
chunk_text: c.chunk_text,
chunk_source: c.chunk_source,
embedding: embeddingMap.get(c.chunk_index) ?? undefined,
model: embeddingMap.has(c.chunk_index) && embedModelLabel ? embedModelLabel : c.model,
token_count: c.token_count || Math.ceil(c.chunk_text.length / 4),
}));
await observed(pacer, () => engine.upsertChunks(page.slug, updated, pageOpts));
@@ -1021,15 +1012,11 @@ async function embedAllStale(
for (let j = 0; j < stale.length; j++) {
staleIdxToEmbedding.set(stale[j].chunk_index, embeddings[j]);
}
// #1717: label the re-embedded (stale) chunks with the resolved
// model; preserve the existing model on the non-stale chunks.
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),
}));
await observed(pacer, () => engine.upsertChunks(slug, merged, { sourceId: keySourceId }));
-7
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@@ -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
-15
View File
@@ -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';
+1 -11
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@@ -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) {
+24
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@@ -4,6 +4,7 @@ import {
extractPageTitle,
hasBacklink,
buildBacklinkEntry,
parseBacklinksArgs,
} from '../src/commands/backlinks.ts';
describe('extractEntityRefs', () => {
@@ -104,3 +105,26 @@ describe('findBacklinkGaps dedupe (v0.36.x #967 regression)', () => {
}
});
});
describe('parseBacklinksArgs', () => {
test('uses positional dir for check and fix subcommands', () => {
expect(parseBacklinksArgs(['check', '/tmp/brain']).brainDir).toBe('/tmp/brain');
expect(parseBacklinksArgs(['fix', '/tmp/brain']).brainDir).toBe('/tmp/brain');
});
test('defaults to cwd when no dir given', () => {
expect(parseBacklinksArgs(['check']).brainDir).toBe('.');
});
test('--dir overrides positional dir and preserves dry-run', () => {
const parsed = parseBacklinksArgs(['fix', '/tmp/ignored', '--dir', '/tmp/brain', '--dry-run']);
expect(parsed.subcommand).toBe('fix');
expect(parsed.brainDir).toBe('/tmp/brain');
expect(parsed.dryRun).toBe(true);
});
test('--dir missing its value falls back to positional dir', () => {
expect(parseBacklinksArgs(['check', '/tmp/brain', '--dir']).brainDir).toBe('/tmp/brain');
expect(parseBacklinksArgs(['check', '--dir', '--dry-run']).brainDir).toBe('.');
});
});
-46
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@@ -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();
}
});
});
-33
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@@ -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');
});
});
@@ -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');
});
});