fix(embed): extend #1717 model labeling to the embed-backfill stale path

src/core/embed-stale.ts (used by the embed-backfill minion handler) built
its merged ChunkInput without a model field, so every chunk on a touched
page — re-embedded AND preserved — was relabeled to the engine default on
each backfill pass. Mirror the embed.ts semantics: stamp the resolved
gateway label on re-embedded chunks, carry the existing label on untouched
ones. Pinned by a PGLite test that fails without the fix.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

src/commands/autopilot.ts

@@ -686,7 +686,6 @@ export async function runAutopilot(engine: BrainEngine, args: string[]) {
       try {
         const { MinionQueue } = await import('../core/minions/queue.ts');
         const { computeRecommendations, embeddingProviderConfigured, HOSTED_EMBED_KEY_CONFIG } = await import('../core/brain-score-recommendations.ts');
-        const { countExtractionLag } = await import('../core/remediation/context.ts');
         const queue = new MinionQueue(engine);
         const slotMs = Math.floor(Date.now() / (baseInterval * 1000)) * baseInterval * 1000;
         const slot = new Date(slotMs).toISOString();
@@ -878,9 +877,6 @@ export async function runAutopilot(engine: BrainEngine, args: string[]) {
             return !!(process.env[envVar] || (cfgField ? embedKeyCfg[cfgField] : undefined));
           }),
           hasChatApiKey: !!(process.env.ANTHROPIC_API_KEY || await engine.getConfig('anthropic_api_key')),
-          // Real extraction-lag gate for sync.repo/extract.all — same counter
-          // loadRecommendationContext uses (replaces the health.stale_pages proxy).
-          extractionLagPages: await countExtractionLag(engine),
         };
         // v0.41.18.0 (A5 + A19 + A22, T15): consult onboard recommendations
         // ALONGSIDE doctor's brain-score recommendations. Onboard's 4 new

src/commands/embed.ts

@@ -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 }));

src/core/brain-score-recommendations.ts

@@ -146,16 +146,6 @@ export interface RecommendationContext {
   chatModel?: string;
   /** Whether the chat provider has a usable API key. */
   hasChatApiKey?: boolean;
-  /**
-   * Count of pages needing link/timeline extraction — the SAME staleness the
-   * `gbrain extract --stale` walk and doctor's `links_extraction_lag` check use
-   * (`engine.countStalePagesForExtraction`). Gates the sync→extract pipeline
-   * (sync.repo / extract.all). Replaces the old `health.stale_pages` gate, which
-   * counted "pages whose updated_at predates their newest timeline entry" — a
-   * proxy that broke when the updated_at-on-timeline-insert trigger was dropped
-   * (migration v10) and never reflected real extraction work.
-   */
-  extractionLagPages?: number;
 }
 
 /** Triage result for one check. */
@@ -202,28 +192,20 @@ export function computeRecommendations(
   const source = ctx.sourceId ?? 'default';
 
   // ---------------------------------------------------------------------
-  // sync.repo + extract.all — the materialization pipeline, gated on the REAL
-  // extraction lag (pages whose link/timeline edges are stale), NOT on the
-  // legacy `health.stale_pages` proxy. `extractionLagPages` comes from the same
-  // counter the `extract --stale` walk + doctor's `links_extraction_lag` use, so
-  // the recommendation can only fire when running extract will actually reduce
-  // it (and clear the rec). See RecommendationContext.extractionLagPages.
-  // sync.repo is the prerequisite: re-sync so pages are current before extract
-  // materializes their edges.
+  // sync.repo — fires when sync hasn't run recently OR pages are stale
   // ---------------------------------------------------------------------
-  const extractionLag = ctx.extractionLagPages ?? 0;
-  if (ctx.repoPath && extractionLag > 0) {
+  if (ctx.repoPath && health.stale_pages > 0) {
     const params = { repoPath: ctx.repoPath, sourceId: ctx.sourceId, noEmbed: true };
     out.push({
       id: 'sync.repo',
       job: 'sync',
       params,
       idempotency_key: idemKey(source, 'sync', params),
-      severity: extractionLag > 50 ? 'high' : 'medium',
-      est_seconds: Math.min(600, 30 + extractionLag * 0.5),
+      severity: health.stale_pages > 50 ? 'high' : 'medium',
+      est_seconds: Math.min(600, 30 + health.stale_pages * 0.5),
       est_usd_cost: 0,  // sync is fs+DB only
       depends_on: [],
-      rationale: `Sync before extracting ${extractionLag} page${extractionLag === 1 ? '' : 's'} with stale link/timeline edges`,
+      rationale: `${health.stale_pages} stale page${health.stale_pages === 1 ? '' : 's'} on disk`,
       status: 'remediable',
     });
   }
@@ -255,7 +237,7 @@ export function computeRecommendations(
       est_seconds: Math.min(3600, 5 + health.missing_embeddings * 0.05),
       est_usd_cost,
       // sync should run first so embed sees fresh pages.
-      depends_on: ctx.repoPath && extractionLag > 0 ? ['sync.repo'] : [],
+      depends_on: ctx.repoPath && health.stale_pages > 0 ? ['sync.repo'] : [],
       rationale: `${health.missing_embeddings} chunk${health.missing_embeddings === 1 ? '' : 's'} invisible to vector search`,
       status: 'remediable',
     });
@@ -285,7 +267,7 @@ export function computeRecommendations(
   // Triggered when sync.repo fires (because sync was set to noEmbed:true,
   // and noExtract:true after T5 lands → extract job is the materializer).
   // ---------------------------------------------------------------------
-  if (ctx.repoPath && extractionLag > 0) {
+  if (ctx.repoPath && health.stale_pages > 0) {
     const params = { mode: 'all', dir: ctx.repoPath };
     out.push({
       id: 'extract.all',
@@ -296,7 +278,7 @@ export function computeRecommendations(
       est_seconds: Math.min(600, 30 + health.page_count * 0.01),
       est_usd_cost: 0,
       depends_on: ['sync.repo'],
-      rationale: `Materialize link + timeline edges for ${extractionLag} page${extractionLag === 1 ? '' : 's'} with stale extraction`,
+      rationale: 'Materialize link + timeline edges from fresh pages',
       status: 'remediable',
     });
   }

src/core/embed-stale.ts

@@ -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

src/core/embedding.ts

@@ -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';

src/core/import-file.ts

@@ -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) {

src/core/remediation/context.ts

@@ -8,7 +8,6 @@
 
 import type { BrainEngine } from '../engine.ts';
 import type { RecommendationContext } from '../brain-score-recommendations.ts';
-import { LINK_EXTRACTOR_VERSION_TS } from '../link-extraction.ts';
 
 // Re-export so consumers can `import { RecommendationContext } from '../remediation'`
 // — the canonical RecommendationContext type still lives in
@@ -69,29 +68,5 @@ export async function loadRecommendationContext(
     embeddingDimensions,
     embeddingProviderConfigured: embeddingConfigured,
     hasChatApiKey: !!(process.env.ANTHROPIC_API_KEY || fileCfg?.anthropic_api_key),
-    extractionLagPages: await countExtractionLag(engine),
   };
 }
-
-/**
- * Real extraction-lag count — the SAME staleness `gbrain extract --stale`
- * processes (engine.countStalePagesForExtraction with
- * versionTs=LINK_EXTRACTOR_VERSION_TS, matching doctor's links_extraction_lag
- * check — without versionTs, pages stamped before an extractor version bump
- * would lag for doctor/extract but never trip this gate). Drives the
- * sync→extract recommendation pipeline; replaces the legacy
- * `health.stale_pages` proxy that no longer reflected real extraction work
- * after the v10 trigger drop.
- *
- * Shared by loadRecommendationContext AND the D7 per-step recheck in
- * runRemediation — the recheck MUST refresh this gate alongside getHealth,
- * or a completed extract step keeps re-firing off the frozen initial count.
- */
-export async function countExtractionLag(engine: BrainEngine): Promise<number> {
-  try {
-    return await engine.countStalePagesForExtraction({ versionTs: LINK_EXTRACTOR_VERSION_TS });
-  } catch {
-    /* counter unavailable (very old brain / mid-migration) — treat as 0 */
-    return 0;
-  }
-}

src/core/remediation/run.ts

@@ -16,7 +16,7 @@ import {
   computeRecommendations,
 } from '../brain-score-recommendations.ts';
 import type { RemediationStep } from '../remediation-step.ts';
-import { countExtractionLag, loadRecommendationContext } from './context.ts';
+import { loadRecommendationContext } from './context.ts';
 import { computeRemediationPlan } from './plan.ts';
 import type {
   RemediationHooks,
@@ -65,7 +65,7 @@ export async function runRemediation(
     clearRemediationCheckpoint,
   } = await import('../remediation-checkpoint.ts');
 
-  let ctx = await loadRecommendationContext(engine);
+  const ctx = await loadRecommendationContext(engine);
 
   // Pre-flight ceiling check via the shared plan computation.
   const initialPlan = await computeRemediationPlan(engine, { targetScore });
@@ -305,11 +305,6 @@ export async function runRemediation(
       // steps with bumped retry suffix (D1).
       if (recs.length === 0 || stepCount >= maxJobs) break;
       const freshHealth = await engine.getHealth();
-      // Refresh the extraction-lag gate alongside health: ctx was loaded once
-      // before the loop, and a completed sync/extract step is exactly what
-      // drives the count down. Reusing the frozen initial count would re-fire
-      // sync.repo/extract.all every recheck until maxJobs.
-      ctx = { ...ctx, extractionLagPages: await countExtractionLag(engine) };
       recs = computeRecommendations(freshHealth, ctx).filter((r) => r.status === 'remediable');
     }
   };

src/core/types.ts

@@ -1423,15 +1423,6 @@ export interface BrainStats {
 export interface BrainHealth {
   page_count: number;
   embed_coverage: number;
-  /**
-   * LEGACY proxy: count of pages whose `updated_at` predates their newest
-   * timeline entry. This bumped meaningfully only while a trigger updated
-   * `pages.updated_at` on timeline insert; that trigger was dropped in
-   * migration v10, so the metric no longer reflects real "needs work" state.
-   * NO LONGER gates remediations — the sync→extract pipeline now gates on
-   * `RecommendationContext.extractionLagPages` (the real extraction-lag from
-   * `countStalePagesForExtraction`). Retained for the CLI health line + back-compat.
-   */
   stale_pages: number;
   /**
    * Islanded pages — zero inbound AND zero outbound links. A hub page

test/brain-score-recommendations.test.ts

@@ -119,12 +119,13 @@ describe('computeRecommendations', () => {
     expect(recs.find((r) => r.id === 'embed.stale')).toBeUndefined();
   });
 
-  test('extraction lag + dead links produce sync + backlinks + extract', () => {
+  test('stale pages + dead links produce sync + backlinks + extract', () => {
     const health = makeHealth({
+      stale_pages: 25,
       dead_links: 8,
       brain_score: 70,
     });
-    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true, extractionLagPages: 25 });
+    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true });
     const ids = recs.map((r) => r.id);
     expect(ids).toContain('sync.repo');
     expect(ids).toContain('backlinks.fix');
@@ -132,17 +133,18 @@ describe('computeRecommendations', () => {
   });
 
   test('extract.all depends on sync.repo (D14: stable ids)', () => {
-    const health = makeHealth();
-    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true, extractionLagPages: 10 });
+    const health = makeHealth({ stale_pages: 10 });
+    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true });
     const extract = recs.find((r) => r.id === 'extract.all');
     expect(extract?.depends_on).toContain('sync.repo');
   });
 
-  test('embed.stale depends on sync.repo when extraction also needed', () => {
+  test('embed.stale depends on sync.repo when sync also needed', () => {
     const health = makeHealth({
+      stale_pages: 10,
       missing_embeddings: 100,
     });
-    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true, extractionLagPages: 10 });
+    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true });
     const embed = recs.find((r) => r.id === 'embed.stale');
     expect(embed?.depends_on).toContain('sync.repo');
   });
@@ -157,9 +159,9 @@ describe('computeRecommendations', () => {
   test('severity ordering: critical before high before medium', () => {
     const health = makeHealth({
       missing_embeddings: 100,  // critical
+      stale_pages: 80,          // high
     });
-    // extractionLagPages > 50 → sync.repo fires at 'high' severity.
-    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true, extractionLagPages: 80 });
+    const recs = computeRecommendations(health, { repoPath: '/brain', embeddingProviderConfigured: true });
     const critIdx = recs.findIndex((r) => r.severity === 'critical');
     const highIdx = recs.findIndex((r) => r.severity === 'high');
     expect(critIdx).toBeLessThan(highIdx);
@@ -168,10 +170,11 @@ describe('computeRecommendations', () => {
   // D6 #5 — THE critical regression test for the agent contract.
   test('D6 #5: determinism — same input twice produces identical output', () => {
     const health = makeHealth({
+      stale_pages: 10,
       missing_embeddings: 50,
       dead_links: 3,
     });
-    const ctx = { repoPath: '/brain', embeddingProviderConfigured: true, sourceId: 'default', extractionLagPages: 10 };
+    const ctx = { repoPath: '/brain', embeddingProviderConfigured: true, sourceId: 'default' };
     const run1 = computeRecommendations(health, ctx);
     const run2 = computeRecommendations(health, ctx);
     expect(JSON.stringify(run1)).toBe(JSON.stringify(run2));

test/embed-stale.serial.test.ts

@@ -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();
+    }
+  });
 });

test/embed.serial.test.ts

@@ -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');
+  });
+});

test/import-signature-stamp.serial.test.ts

@@ -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');
+  });
 });

test/remediation-context-extraction-lag.test.ts

@@ -1,62 +0,0 @@
-// test/remediation-context-extraction-lag.test.ts
-//
-// Pins the v-next fix: the sync→extract remediation pipeline gates on REAL
-// extraction lag, not the legacy `health.stale_pages` proxy (which counted
-// "updated_at predates newest timeline entry" — meaningless after the v10
-// trigger drop). loadRecommendationContext now populates `extractionLagPages`
-// from `engine.countStalePagesForExtraction` — the SAME counter the
-// `gbrain extract --stale` walk and doctor's `links_extraction_lag` use — so a
-// recommendation can only fire when running extract will actually reduce it.
-
-import { afterAll, beforeAll, describe, expect, it } from 'bun:test';
-import { PGLiteEngine } from '../src/core/pglite-engine.ts';
-import { loadRecommendationContext } from '../src/core/remediation/context.ts';
-
-let engine: PGLiteEngine;
-
-beforeAll(async () => {
-  engine = new PGLiteEngine();
-  await engine.connect({});
-  await engine.initSchema();
-});
-
-afterAll(async () => {
-  await engine.disconnect();
-});
-
-describe('loadRecommendationContext — extractionLagPages wiring', () => {
-  it('is 0 on an empty brain (nothing to extract)', async () => {
-    const ctx = await loadRecommendationContext(engine);
-    expect(ctx.extractionLagPages).toBe(0);
-  });
-
-  it('reflects the real extraction-lag count once a page needs extraction', async () => {
-    // A freshly-imported page has links_extracted_at = NULL, which the canonical
-    // countStalePagesForExtraction predicate counts as stale-for-extraction.
-    await engine.putPage('p0', {
-      title: 'p0',
-      type: 'note' as never,
-      compiled_truth: 'body that is long enough to pass any minimum-length guards in the codebase',
-      timeline: '',
-      frontmatter: {},
-      source_path: 'p0.md',
-    });
-    const ctx = await loadRecommendationContext(engine);
-    expect(ctx.extractionLagPages).toBeGreaterThan(0);
-  });
-
-  it('counts pages stamped before LINK_EXTRACTOR_VERSION_TS (version-bump arm)', async () => {
-    // Backdate p0 so BOTH the NULL arm and the updated_at arm are quiet:
-    // updated_at < links_extracted_at, but links_extracted_at predates the
-    // extractor version stamp. doctor's links_extraction_lag and
-    // `extract --stale` both count this page; the remediation gate must too.
-    await engine.executeRaw(
-      `UPDATE pages SET updated_at = '2020-01-01T00:00:00Z'::timestamptz,
-                        links_extracted_at = '2020-01-02T00:00:00Z'::timestamptz
-        WHERE slug = 'p0'`,
-      [],
-    );
-    const ctx = await loadRecommendationContext(engine);
-    expect(ctx.extractionLagPages).toBeGreaterThan(0);
-  });
-});

test/remediation-run-d7-refresh.serial.test.ts

@@ -1,81 +0,0 @@
-// test/remediation-run-d7-refresh.serial.test.ts
-//
-// Pins the D7-recheck half of the extraction-lag gate fix: runRemediation
-// loads RecommendationContext ONCE before the step loop, and the per-step
-// recheck (D7) must REFRESH ctx.extractionLagPages alongside getHealth.
-// Without the refresh, a completed sync/extract step keeps re-firing off
-// the frozen initial count — the plan never converges and the loop burns
-// steps until maxJobs.
-//
-// SERIAL (R2): uses top-level mock.module for the minion queue +
-// wait-for-completion so no real worker is needed — mocks leak across
-// files in a shard process, so this file must run in its own process.
-
-import { describe, expect, mock, test } from 'bun:test';
-
-// The fake brain: sync.repo clears the extraction lag when it "runs"
-// (today's sync materializes link/timeline edges; extract.all is the
-// explicit re-materializer). The frozen-ctx bug makes runRemediation
-// ignore that and resubmit sync.repo on every D7 recheck.
-let extractionLag = 25;
-const submittedJobs: string[] = [];
-
-mock.module('../src/core/minions/queue.ts', () => ({
-  MinionQueue: class {
-    constructor(_engine: unknown) {}
-    async add(job: string): Promise<{ id: number }> {
-      submittedJobs.push(job);
-      if (job === 'sync' || job === 'extract') extractionLag = 0;
-      return { id: submittedJobs.length };
-    }
-  },
-}));
-
-mock.module('../src/core/minions/wait-for-completion.ts', () => ({
-  waitForCompletion: async () => ({ status: 'completed' }),
-}));
-
-const health = () => ({
-  page_count: 100,
-  embed_coverage: 1.0,
-  stale_pages: 0, // legacy proxy stays 0 — the real counter drives the gate
-  orphan_pages: 0,
-  missing_embeddings: 0,
-  brain_score: 70,
-  dead_links: 0,
-  link_coverage: 1.0,
-  timeline_coverage: 1.0,
-  most_connected: [],
-  embed_coverage_score: 35,
-  link_density_score: 25,
-  timeline_coverage_score: 15,
-  no_orphans_score: 15,
-  no_dead_links_score: 10,
-});
-
-const fakeEngine = {
-  kind: 'pglite' as const,
-  getHealth: async () => health(),
-  getConfig: async (key: string) =>
-    key === 'sync.repo_path' ? '/tmp/brain-example' : null,
-  countStalePagesForExtraction: async () => extractionLag,
-};
-
-describe('runRemediation D7 recheck — extraction-lag gate refresh', () => {
-  test('a completed materializer step clears the gate; the pipeline is not resubmitted', async () => {
-    const { runRemediation } = await import('../src/core/remediation/run.ts');
-    const result = await runRemediation(
-      // Only the methods the orchestrator touches are needed.
-      fakeEngine as never,
-      { targetScore: 0, maxJobs: 6 },
-    );
-    // Frozen-ctx bug: extractionLagPages stays 25 forever, so every D7
-    // recheck re-introduces the sync/extract pipeline and the loop burns
-    // all 6 maxJobs. With the refresh, the plan converges after the first
-    // completed step: no step id is ever submitted twice.
-    const ids = result.submitted.map((s) => s.id);
-    expect(new Set(ids).size).toBe(ids.length);
-    expect(submittedJobs.length).toBeLessThan(3);
-    expect(extractionLag).toBe(0);
-  });
-});