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https://github.com/garrytan/gbrain.git
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Compare commits
2
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
89579780e0 | ||
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cf2deedfc6 |
@@ -438,13 +438,6 @@ export async function runApplyMigrations(args: string[]): Promise<void> {
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const result = await m.orchestrator(orchestratorOptsFrom(cli));
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if (result.status === 'failed') {
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console.error(`Migration v${m.version} reported status=failed.`);
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// Surface each failed phase's detail — the ledger records it, but
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// the operator needs it on stderr to act (#921).
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for (const p of result.phases) {
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if (p.status === 'failed') {
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console.error(` phase ${p.name}: ${p.detail ?? '(no detail)'}`);
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}
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}
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// Record the attempt as 'partial' (not 'complete') so the cap counts
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// it. Don't let a failed orchestrator look like it never ran.
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try {
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+14
-1
@@ -1,5 +1,5 @@
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import type { BrainEngine } from '../core/engine.ts';
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import { embedBatch, currentEmbeddingSignature } from '../core/embedding.ts';
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import { embedBatch, currentEmbeddingSignature, resolveEmbeddingModelLabel } 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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@@ -581,11 +581,16 @@ 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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@@ -717,12 +722,16 @@ 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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@@ -1012,11 +1021,15 @@ 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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@@ -186,6 +186,17 @@ async function phaseBFenceFacts(
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const localPathById = new Map<string, string | null>();
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for (const s of sources) localPathById.set(s.id, s.local_path);
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// Dirty-tree refusal: check every source's local_path before writing.
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for (const [id, localPath] of localPathById) {
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if (localPath && isLocalPathDirty(localPath)) {
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return {
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name: 'fence_facts',
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status: 'failed',
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detail: `source "${id}" has uncommitted changes in ${localPath}. Commit or stash, then re-run.`,
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};
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}
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}
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// Walk legacy rows in (source_id, entity_slug) groups for per-page
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// atomic writes.
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const legacy = await engine.executeRaw<LegacyFactRow>(
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@@ -224,21 +235,6 @@ async function phaseBFenceFacts(
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groups.set(key, list);
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}
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// Dirty-tree refusal: check ONLY the sources we are about to write
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// into. A dirty tree in an unrelated source (or zero fenceable rows
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// at all) must not block a no-op or a targeted backfill (#927).
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const targetSourceIds = new Set([...groups.keys()].map(k => k.split('\0')[0]));
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for (const id of targetSourceIds) {
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const localPath = localPathById.get(id);
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if (localPath && isLocalPathDirty(localPath)) {
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return {
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name: 'fence_facts',
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status: 'failed',
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detail: `source "${id}" has uncommitted changes in ${localPath}. Commit or stash, then re-run.`,
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};
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}
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}
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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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@@ -20,6 +20,7 @@
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import type { BrainEngine } from './engine.ts';
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import type { ChunkInput } from './types.ts';
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import { embedBatchWithBackoff } from '../commands/embed.ts';
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import { resolveEmbeddingModelLabel } from './embedding.ts';
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import { type DbPacer, createNoopPacer, observed } from './db-pacer.ts';
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import { AbortError } from './abort-check.ts';
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@@ -200,11 +201,17 @@ export async function embedStaleForSource(
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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 re-embedded chunks with the model that produced the
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// vector; preserved chunks keep their existing model. Without this,
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// upsertChunks falls back to DEFAULT_EMBEDDING_MODEL for every chunk
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// (the same mislabel the embed.ts paths fixed).
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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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// Carry through per-chunk metadata. upsertChunks writes these as
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// EXCLUDED.<col> (not COALESCE), so omitting them here resets image
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@@ -113,6 +113,21 @@ export async function embedBatch(
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return results;
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}
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/**
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* Resolve the embedding model label (`provider:model`) to stamp onto
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* `content_chunks.model`, so each chunk records the model that actually
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* produced its vector instead of the engine's hardcoded default (#1717).
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* Returns undefined if the gateway is unconfigured; callers then fall back
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* to the chunk's existing model rather than mislabeling it.
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*/
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export function resolveEmbeddingModelLabel(): string | undefined {
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try {
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return gatewayGetModel();
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} catch {
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return undefined;
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}
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}
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/** Currently-configured embedding model (short form without provider prefix). */
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export function getEmbeddingModelName(): string {
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return gatewayGetModel().split(':').slice(1).join(':') || 'text-embedding-3-large';
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+11
-1
@@ -8,7 +8,7 @@ import { chunkText } from './chunkers/recursive.ts';
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import { chunkCodeText, chunkCodeTextFull, detectCodeLanguage, CHUNKER_VERSION } from './chunkers/code.ts';
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import { findChunkForOffset } from './chunkers/edge-extractor.ts';
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import { extractCodeRefs, imageOfCandidates } from './link-extraction.ts';
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import { embedBatch, embedMultimodal, currentEmbeddingSignature } from './embedding.ts';
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import { embedBatch, embedMultimodal, currentEmbeddingSignature, resolveEmbeddingModelLabel } from './embedding.ts';
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import { slugifyPath, slugifyCodePath, isCodeFilePath } from './sync.ts';
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import type { ChunkInput, PageInput, PageType } from './types.ts';
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import { computeEffectiveDate } from './effective-date.ts';
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@@ -716,8 +716,12 @@ export async function importFromContent(
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? chunks.map((c) => wrapChunkForEmbedding(c.chunk_text, prefix, c.chunk_source))
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: chunks.map((c) => c.chunk_text);
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const embeddings = await embedBatch(wrappedTexts);
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// #1717: label each chunk with the model that actually produced its
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// vector, not the engine's hardcoded default.
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const embedModelLabel = resolveEmbeddingModelLabel();
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for (let i = 0; i < chunks.length; i++) {
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chunks[i].embedding = embeddings[i];
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if (embedModelLabel) chunks[i].model = embedModelLabel;
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// token_count tracks the wrapped string length so cost reporting
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// reflects what we actually sent to the embedder.
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chunks[i].token_count = Math.ceil(wrappedTexts[i].length / 4);
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@@ -1141,7 +1145,10 @@ export async function importCodeFile(
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const matched = existingByKey.get(key);
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if (matched && matched.embedding) {
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// Reuse the existing embedding verbatim. No API call, no cost.
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// #1717: carry the existing model label along with the reused vector
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// so the upsert doesn't relabel it with the engine default.
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chunks[i]!.embedding = matched.embedding as Float32Array;
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chunks[i]!.model = matched.model ?? undefined;
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chunks[i]!.token_count = matched.token_count ?? undefined;
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} else {
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needsEmbedIndexes.push(i);
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@@ -1153,9 +1160,12 @@ export async function importCodeFile(
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try {
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const textsToEmbed = needsEmbedIndexes.map((i) => chunks[i]!.chunk_text);
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const embeddings = await embedBatch(textsToEmbed);
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// #1717: stamp the model that produced these vectors.
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const embedModelLabel = resolveEmbeddingModelLabel();
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for (let j = 0; j < needsEmbedIndexes.length; j++) {
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const i = needsEmbedIndexes[j]!;
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chunks[i]!.embedding = embeddings[j]!;
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if (embedModelLabel) chunks[i]!.model = embedModelLabel;
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chunks[i]!.token_count = Math.ceil(chunks[i]!.chunk_text.length / 4);
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}
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} catch (e: unknown) {
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@@ -180,16 +180,3 @@ describe('runApplyMigrations exit codes (v0.36.1.x #1062)', () => {
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expect(src).toMatch(/All migrations up to date[\s\S]{0,80}process\.exit\(0\)/);
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});
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});
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|
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// #921: a failed orchestrator must print each failed phase's detail to
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// stderr — not just "reported status=failed" — so the operator can act
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// without digging through the ledger.
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describe('failed migration prints phase detail (#921)', () => {
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test('runner loops result.phases and console.errors failed phase details', async () => {
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const { readFileSync } = await import('fs');
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const src = readFileSync('src/commands/apply-migrations.ts', 'utf8');
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expect(src).toMatch(
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/reported status=failed[\s\S]{0,400}for \(const p of result\.phases\)[\s\S]{0,200}p\.status === 'failed'[\s\S]{0,200}console\.error\([\s\S]{0,80}p\.name[\s\S]{0,80}p\.detail/,
|
||||
);
|
||||
});
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});
|
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|
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@@ -15,6 +15,7 @@ import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:tes
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import { PGLiteEngine } from '../src/core/pglite-engine.ts';
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import { resetPgliteState } from './helpers/reset-pglite.ts';
|
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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;
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||||
@@ -276,4 +277,49 @@ describe('embedStaleForSource', () => {
|
||||
// The stale text row actually got its embedding.
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expect(txtRow.embedded_at).not.toBeNull();
|
||||
});
|
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|
||||
// #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 () => {
|
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configureGateway({
|
||||
embedding_model: 'openai:text-embedding-3-large',
|
||||
env: { OPENAI_API_KEY: 'sk-test-embed-stale-1717' },
|
||||
});
|
||||
try {
|
||||
await engine.putPage('notes/model-label', {
|
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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');
|
||||
});
|
||||
});
|
||||
|
||||
@@ -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');
|
||||
});
|
||||
});
|
||||
|
||||
@@ -10,11 +10,10 @@
|
||||
* __setTestEngineOverride so we don't need a configured brain.
|
||||
*/
|
||||
|
||||
import { describe, test, expect, beforeAll, afterAll, beforeEach, afterEach } from 'bun:test';
|
||||
import { describe, test, expect, beforeAll, afterAll, beforeEach } from 'bun:test';
|
||||
import { mkdtempSync, rmSync, existsSync, readFileSync, writeFileSync, mkdirSync } from 'node:fs';
|
||||
import { tmpdir } from 'node:os';
|
||||
import { join } from 'node:path';
|
||||
import { execFileSync } from 'node:child_process';
|
||||
|
||||
import { PGLiteEngine } from '../src/core/pglite-engine.ts';
|
||||
import { v0_32_2, __setTestEngineOverride, __testing } from '../src/commands/migrations/v0_32_2.ts';
|
||||
@@ -239,52 +238,6 @@ describe('phaseBFenceFacts — happy path backfill', () => {
|
||||
});
|
||||
});
|
||||
|
||||
describe('phaseBFenceFacts — dirty-tree refusal scoping (#927)', () => {
|
||||
let dirtyDir: string;
|
||||
|
||||
beforeEach(async () => {
|
||||
// A second source whose local_path is a git repo with uncommitted changes.
|
||||
dirtyDir = mkdtempSync(join(tmpdir(), 'mig-v0_32_2-dirty-'));
|
||||
execFileSync('git', ['-C', dirtyDir, 'init', '-q']);
|
||||
writeFileSync(join(dirtyDir, 'uncommitted.md'), 'dirty', 'utf-8');
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
await (engine as any).db.query(
|
||||
`INSERT INTO sources (id, name, local_path) VALUES ('other', 'other', $1)`,
|
||||
[dirtyDir],
|
||||
);
|
||||
});
|
||||
|
||||
afterEach(async () => {
|
||||
// eslint-disable-next-line @typescript-eslint/no-explicit-any
|
||||
await (engine as any).db.query(`DELETE FROM sources WHERE id = 'other'`);
|
||||
rmSync(dirtyDir, { recursive: true, force: true });
|
||||
});
|
||||
|
||||
test('no legacy facts at all → complete, dirty unrelated source ignored', async () => {
|
||||
const r = await __testing.phaseBFenceFacts(engine, OPTS);
|
||||
expect(r.status).toBe('complete');
|
||||
expect(r.detail).toContain('scanned=0');
|
||||
});
|
||||
|
||||
test('facts scoped to a clean source fence despite dirty unrelated source', async () => {
|
||||
await seedLegacyFact({ entity_slug: 'people/alice', fact: 'Founded Acme' });
|
||||
|
||||
const r = await __testing.phaseBFenceFacts(engine, OPTS);
|
||||
expect(r.status).toBe('complete');
|
||||
expect(r.detail).toContain('fenced=1');
|
||||
expect(existsSync(join(brainDir, 'people/alice.md'))).toBe(true);
|
||||
});
|
||||
|
||||
test('still refuses when the TARGETED source is dirty', async () => {
|
||||
await seedLegacyFact({ entity_slug: 'people/alice', fact: 'F1', source_id: 'other' });
|
||||
|
||||
const r = await __testing.phaseBFenceFacts(engine, OPTS);
|
||||
expect(r.status).toBe('failed');
|
||||
expect(r.detail).toContain('"other"');
|
||||
expect(r.detail).toContain('uncommitted changes');
|
||||
});
|
||||
});
|
||||
|
||||
describe('phaseCVerify', () => {
|
||||
test('returns complete when fence + DB row counts match', async () => {
|
||||
await seedLegacyFact({ entity_slug: 'people/alice', fact: 'F1' });
|
||||
|
||||
Reference in New Issue
Block a user