mirror of
https://github.com/garrytan/gbrain.git
synced 2026-08-16 01:42:23 +00:00
Compare commits
2
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
89579780e0 | ||
|
|
cf2deedfc6 |
+14
-1
@@ -1,5 +1,5 @@
|
||||
import type { BrainEngine } from '../core/engine.ts';
|
||||
import { embedBatch, currentEmbeddingSignature } from '../core/embedding.ts';
|
||||
import { embedBatch, currentEmbeddingSignature, resolveEmbeddingModelLabel } 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';
|
||||
@@ -581,11 +581,16 @@ 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),
|
||||
}));
|
||||
|
||||
@@ -717,12 +722,16 @@ 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));
|
||||
@@ -1012,11 +1021,15 @@ 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 }));
|
||||
|
||||
@@ -1743,15 +1743,7 @@ async function extractStaleFromDB(
|
||||
// `page.updated_at.toISOString()` — the JS Date is ms-truncated, so the
|
||||
// µs-precision DB updated_at stayed strictly greater and the page never
|
||||
// cleared on Postgres. Stamping the exact value makes them equal.
|
||||
//
|
||||
// Version-arm floor: a page last edited BEFORE LINK_EXTRACTOR_VERSION_TS
|
||||
// would otherwise be stamped below the version watermark and stay
|
||||
// permanently stale (`links_extracted_at < versionTs` re-fires every run).
|
||||
// Stamp max(updated_at, versionTs) — versionTs is always a past release
|
||||
// date, so a concurrent edit's now() still exceeds the stamp and D4 holds.
|
||||
// Tie at ms precision picks updated_at_iso (its µs ≥ versionTs's .000000).
|
||||
const stampTs = new Date(page.updated_at_iso) >= new Date(versionTs) ? page.updated_at_iso : versionTs;
|
||||
processedRefs.push({ slug: page.slug, source_id: page.source_id, extractedAt: stampTs });
|
||||
processedRefs.push({ slug: page.slug, source_id: page.source_id, extractedAt: page.updated_at_iso });
|
||||
}
|
||||
|
||||
// Flush NON-swallowing (CDX-4): a throw here propagates out of the sweep so
|
||||
|
||||
@@ -20,6 +20,7 @@
|
||||
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';
|
||||
|
||||
@@ -200,11 +201,17 @@ 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
|
||||
|
||||
@@ -113,6 +113,21 @@ 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';
|
||||
|
||||
+11
-1
@@ -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 } from './embedding.ts';
|
||||
import { embedBatch, embedMultimodal, currentEmbeddingSignature, resolveEmbeddingModelLabel } from './embedding.ts';
|
||||
import { slugifyPath, slugifyCodePath, isCodeFilePath } from './sync.ts';
|
||||
import type { ChunkInput, PageInput, PageType } from './types.ts';
|
||||
import { computeEffectiveDate } from './effective-date.ts';
|
||||
@@ -716,8 +716,12 @@ 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);
|
||||
@@ -1141,7 +1145,10 @@ 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);
|
||||
@@ -1153,9 +1160,12 @@ 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) {
|
||||
|
||||
@@ -28,7 +28,7 @@ import { ensureWellFormed } from './text-safe.ts';
|
||||
* OR updated_at > links_extracted_at`. It is an ISO-8601 string (NOT a number) —
|
||||
* the column is TIMESTAMPTZ and the predicate binds it as `::timestamptz`.
|
||||
*/
|
||||
export const LINK_EXTRACTOR_VERSION_TS = '2026-07-21T00:00:00Z';
|
||||
export const LINK_EXTRACTOR_VERSION_TS = '2026-05-31T00:00:00Z';
|
||||
|
||||
// ─── Entity references ──────────────────────────────────────────
|
||||
|
||||
@@ -80,10 +80,10 @@ export type LinkResolutionType = 'qualified' | 'unqualified';
|
||||
* Directory prefix whitelist. These are the top-level slug dirs the extractor
|
||||
* recognizes as entity references. Upstream canonical + our extensions:
|
||||
* - Gbrain canonical: people, companies, meetings, concepts, deal, civic, project, source, media, yc, projects
|
||||
* - Our domain extensions: tech, finance, personal, openclaw, ops (domain-organized wikis)
|
||||
* - Our domain extensions: tech, finance, personal, openclaw (domain-organized wikis)
|
||||
* - Our entity prefix: entities (we kept some legacy entities/projects/ pages)
|
||||
*/
|
||||
const DIR_PATTERN = '(?:people|companies|meetings|concepts|deal|civic|project|projects|source|media|yc|tech|finance|personal|openclaw|entities|ops)';
|
||||
const DIR_PATTERN = '(?:people|companies|meetings|concepts|deal|civic|project|projects|source|media|yc|tech|finance|personal|openclaw|entities)';
|
||||
|
||||
/**
|
||||
* Match `[Name](path)` markdown links pointing to entity directories.
|
||||
@@ -865,16 +865,7 @@ export function queryBasenameIndex(idx: Map<string, string[]>, name: string): st
|
||||
if (!name || typeof name !== 'string') return [];
|
||||
const trimmed = name.trim();
|
||||
if (!trimmed) return [];
|
||||
let hit = idx.get(trimmed) ?? idx.get(trimmed.toLowerCase()) ?? idx.get(normalizeBasename(trimmed));
|
||||
// Issue #2576 bug 2: path-style refs (`runbooks/2026-05-01-x`) from dirs
|
||||
// outside DIR_PATTERN reach here, but normalizeBasename strips slashes
|
||||
// into a garbage key (`runbooks2026-05-01-x`) that can never hit the
|
||||
// tail-keyed index. Fall back to the path tail so qualified refs resolve
|
||||
// by basename like everything else.
|
||||
if (!hit && trimmed.includes('/')) {
|
||||
const tail = trimmed.slice(trimmed.lastIndexOf('/') + 1).trim();
|
||||
if (tail) hit = idx.get(tail) ?? idx.get(tail.toLowerCase()) ?? idx.get(normalizeBasename(tail));
|
||||
}
|
||||
const hit = idx.get(trimmed) ?? idx.get(trimmed.toLowerCase()) ?? idx.get(normalizeBasename(trimmed));
|
||||
return hit ? [...hit].sort(basenameSort) : [];
|
||||
}
|
||||
|
||||
|
||||
@@ -15,6 +15,7 @@ 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;
|
||||
@@ -276,4 +277,49 @@ 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();
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
@@ -37,6 +37,8 @@ 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.
|
||||
@@ -803,3 +805,34 @@ 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');
|
||||
});
|
||||
});
|
||||
|
||||
@@ -209,24 +209,6 @@ describe('gbrain extract --stale', () => {
|
||||
expect(usRows[0]?.eq).toBe(true);
|
||||
});
|
||||
|
||||
test('version-arm floor: page edited BEFORE LINK_EXTRACTOR_VERSION_TS clears after --stale (issue #2576 bug 3)', async () => {
|
||||
// A page whose updated_at predates the version watermark used to be
|
||||
// stamped at its updated_at (< versionTs), so the version arm re-fired
|
||||
// every run — permanently stale. The sweep now floors the stamp at
|
||||
// versionTs. (The #1768 test above also covers this since the v0.42.x
|
||||
// VERSION_TS bump moved its date below the watermark, but this pins the
|
||||
// behavior explicitly so a date "repair" there can't drop coverage.)
|
||||
await engine.putPage('people/alice', personPage('Alice'));
|
||||
await engine.executeRaw(`UPDATE pages SET updated_at = '2000-01-01T00:00:00Z' WHERE slug = 'people/alice'`);
|
||||
expect(await engine.countStalePagesForExtraction({ versionTs: LINK_EXTRACTOR_VERSION_TS })).toBe(1);
|
||||
|
||||
await runExtract(engine, ['--stale']);
|
||||
// Pre-floor this stayed 1 forever (stamp < versionTs → version arm re-fires).
|
||||
expect(await engine.countStalePagesForExtraction({ versionTs: LINK_EXTRACTOR_VERSION_TS })).toBe(0);
|
||||
await runExtract(engine, ['--stale']);
|
||||
expect(await engine.countStalePagesForExtraction({ versionTs: LINK_EXTRACTOR_VERSION_TS })).toBe(0);
|
||||
});
|
||||
|
||||
test('CDX-4 (D2): a link-flush throw aborts the sweep and leaves pages UNSTAMPED', async () => {
|
||||
await engine.putPage('people/alice', personPage('Alice'));
|
||||
await engine.putPage('companies/acme', companyPage('Acme', '[Alice](people/alice) founded [Acme](companies/acme).'));
|
||||
|
||||
@@ -73,4 +73,21 @@ 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');
|
||||
});
|
||||
});
|
||||
|
||||
@@ -140,15 +140,6 @@ describe('extractEntityRefs', () => {
|
||||
expect(wikiRefs[0].needsResolution).toBe(true);
|
||||
});
|
||||
|
||||
test('recognizes ops/ qualified wikilinks (issue #2576 bug 2)', () => {
|
||||
// `ops` was missing from DIR_PATTERN, so [[ops/...]] fell through to
|
||||
// the generic 2c pass (needsResolution) instead of being a real ref.
|
||||
const refs = extractEntityRefs('Deployed via [[ops/services/pointer-agent]].');
|
||||
expect(refs.length).toBe(1);
|
||||
expect(refs[0].slug).toBe('ops/services/pointer-agent');
|
||||
expect(refs[0].needsResolution).toBeUndefined();
|
||||
});
|
||||
|
||||
test('skips qualified-syntax tokens (those belong to 2a)', () => {
|
||||
// [[wiki:topics/ai]] looks like 2a's qualified shape — even though
|
||||
// it wouldn't satisfy DIR_PATTERN, 2c must not claim it either
|
||||
@@ -1078,15 +1069,6 @@ describe('makeResolver — fallback chain', () => {
|
||||
]);
|
||||
});
|
||||
|
||||
test('resolveBasenameMatches: path-style ref falls back to the tail (issue #2576 bug 2)', async () => {
|
||||
// normalizeBasename strips slashes, so `runbooks/2026-05-01-pointer-agent`
|
||||
// used to normalize to a garbage key that never hit the tail-keyed index.
|
||||
const engine = makeFakeEngineWithSlugs(['ops/changes/2026-05-01-pointer-agent']);
|
||||
const r = makeResolver(engine);
|
||||
expect(await r.resolveBasenameMatches!('runbooks/2026-05-01-pointer-agent'))
|
||||
.toEqual(['ops/changes/2026-05-01-pointer-agent']);
|
||||
});
|
||||
|
||||
test('resolveBasenameMatches: case-insensitive fallback', async () => {
|
||||
const engine = makeFakeEngineWithSlugs(['companies/fast-weigh']);
|
||||
const r = makeResolver(engine);
|
||||
|
||||
Reference in New Issue
Block a user