fix(embed): support hosted Perplexity embeddings (pplx-embed-v1-*) (#1046)

Adds a `perplexity` embedding recipe (OpenAI-compatible at
https://api.perplexity.ai/v1, auth via PERPLEXITY_API_KEY only — never an
OPENAI_API_KEY fallback) covering pplx-embed-v1-0.6b and pplx-embed-v1-4b.

Perplexity's /embeddings endpoint diverges from OpenAI's wire shape in two
places that break the AI SDK adapter, handled by a new perplexityCompatFetch
shim (mirrors the Voyage/ZeroEntropy pattern incl. the two-layer OOM caps):
- encoding_format only accepts base64_int8/base64_binary; the SDK's 'float'
  default is forced to 'base64_int8' outbound.
- The response embedding is base64-encoded signed int8 components (natively
  quantized); decoded to number[] inbound so the SDK's Zod schema validates.
  Cosine similarity is scale-invariant, so raw int8 components rank correctly.

Flexible dims (Matryoshka-style 128..native max: 1024 for 0.6b, 2560 for 4b)
validate fail-loud in dims.ts + the init preflight; `dimensions` is
Perplexity's native field so no wire translation is needed. default_dims is
1024 (works on a plain vector column for both models); the 4b model's full
2560 width rides the existing halfvec (>2000 dims) storage/ANN path. Pricing
entries land in embedding-pricing.ts.

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

src/cli.ts

@@ -935,10 +935,7 @@ export function formatResult(opName: string, result: unknown): string {
         lines.push(`Link coverage (entities): ${(h.link_coverage * 100).toFixed(1)}%`);
       }
       if (h.timeline_coverage !== undefined) {
-        lines.push(`Timeline coverage (entity pages): ${(h.timeline_coverage * 100).toFixed(1)}%`);
-      }
-      if (h.timeline_coverage_score !== undefined) {
-        lines.push(`Timeline density (all pages): ${h.timeline_coverage_score}/15 (whole-brain brain-score component)`);
+        lines.push(`Timeline coverage (entities): ${(h.timeline_coverage * 100).toFixed(1)}%`);
       }
       if (Array.isArray(h.most_connected) && h.most_connected.length > 0) {
         lines.push('Most connected entities:');

src/commands/doctor.ts

@@ -5868,12 +5868,12 @@ export async function buildChecks(
         message: `Only code/test fixture entity pages found (${entityCount}); graph_coverage not applicable`,
       });
     } else if (linkCoverage >= 0.5 && timelineCoverage >= 0.5) {
-      checks.push({ name: 'graph_coverage', status: 'ok', message: `Entity link coverage ${linkPct}%, entity timeline coverage ${timelinePct}%` });
+      checks.push({ name: 'graph_coverage', status: 'ok', message: `Entity link coverage ${linkPct}%, timeline ${timelinePct}%` });
     } else {
       checks.push({
         name: 'graph_coverage',
         status: 'warn',
-        message: `Entity link coverage ${linkPct}%, entity timeline coverage ${timelinePct}% (${eligibleEntityCount} entity pages). Run: gbrain extract all`,
+        message: `Entity link coverage ${linkPct}%, timeline ${timelinePct}% (${eligibleEntityCount} entity pages). Run: gbrain extract all`,
       });
     }
 
@@ -5885,7 +5885,7 @@ export async function buildChecks(
       const parts = [
         `embed ${health.embed_coverage_score}/35`,
         `links ${health.link_density_score}/25`,
-        `timeline density (all pages) ${health.timeline_coverage_score}/15`,
+        `timeline ${health.timeline_coverage_score}/15`,
         `orphans ${health.no_orphans_score}/15`,
         `dead-links ${health.no_dead_links_score}/10`,
       ];

src/core/ai/dims.ts

@@ -90,6 +90,30 @@ export function isValidOpenAITextEmbedding3Dim(modelId: string, dims: number): b
   return Number.isInteger(dims) && dims >= 1 && dims <= max;
 }
 
+// Perplexity hosted embeddings (#1046): Matryoshka-style flexible dims,
+// any integer from 128 up to the model's native size. `dimensions` is the
+// native wire field (no translation needed); output encoding divergence
+// (base64 int8) is handled by perplexityCompatFetch in gateway.ts.
+const PERPLEXITY_EMBEDDING_MAX_DIMS: Record<string, number> = {
+  'pplx-embed-v1-0.6b': 1024,
+  'pplx-embed-v1-4b': 2560,
+};
+export const PERPLEXITY_MIN_DIMS = 128;
+
+export function isPerplexityEmbeddingModel(modelId: string): boolean {
+  return modelId in PERPLEXITY_EMBEDDING_MAX_DIMS;
+}
+
+export function maxPerplexityEmbeddingDim(modelId: string): number | undefined {
+  return PERPLEXITY_EMBEDDING_MAX_DIMS[modelId];
+}
+
+export function isValidPerplexityDim(modelId: string, dims: number): boolean {
+  const max = PERPLEXITY_EMBEDDING_MAX_DIMS[modelId];
+  if (max === undefined) return false;
+  return Number.isInteger(dims) && dims >= PERPLEXITY_MIN_DIMS && dims <= max;
+}
+
 // NVIDIA NIM hosted embedding models use asymmetric input_type values. Most
 // emit fixed natural dimensions, but llama-nemotron-embed-1b-v2 accepts
 // Matryoshka-style dimension overrides (e.g. matching an existing 1280d
@@ -226,6 +250,23 @@ export function dimsProviderOptions(
           },
         };
       }
+      // Perplexity pplx-embed-v1-* — flexible dims via the native
+      // `dimensions` field. Fail-loud when the configured dim is outside
+      // the model's range (same rationale as the Voyage/ZE guards: the
+      // upstream HTTP 400 misroutes as a transient network error).
+      // Symmetric retrieval — inputType is never emitted.
+      if (isPerplexityEmbeddingModel(modelId)) {
+        if (!isValidPerplexityDim(modelId, dims)) {
+          const max = maxPerplexityEmbeddingDim(modelId)!;
+          throw new AIConfigError(
+            `Perplexity model "${modelId}" supports embedding_dimensions in ` +
+            `${PERPLEXITY_MIN_DIMS}..${max}, got ${dims}.`,
+            `Set \`embedding_dimensions\` to a value between ${PERPLEXITY_MIN_DIMS} and ${max} ` +
+            `in your gbrain config.`,
+          );
+        }
+        return { openaiCompatible: { dimensions: dims } };
+      }
       // NVIDIA NIM hosted embeddings are OpenAI-compatible but require
       // asymmetric input_type. Use passage for indexing/document-side vectors
       // and query for search-side vectors. Only llama-nemotron-embed-1b-v2

src/core/ai/gateway.ts

@@ -263,6 +263,18 @@ export class ZeroEntropyResponseTooLargeError extends Error {
   }
 }
 
+/** Perplexity twin of the Voyage/ZE OOM caps (#1046). Int8 components are
+ * 1 byte each, so a real response (512 texts × 2560 dims) is ~1.3 MB —
+ * anything near this cap is unambiguously not legitimate. */
+const MAX_PERPLEXITY_RESPONSE_BYTES = 256 * 1024 * 1024;
+
+export class PerplexityResponseTooLargeError extends Error {
+  constructor(message: string) {
+    super(message);
+    this.name = 'PerplexityResponseTooLargeError';
+  }
+}
+
 // ---- Unified auth resolution (D12=A) ----
 //
 // Pre-v0.32, openai-compatible auth was duplicated across instantiateEmbedding,
@@ -1292,6 +1304,103 @@ const openAICompatAsymmetricFetch = (async (input: RequestInfo | URL, init?: Req
   return fetch(typeof input === 'string' ? input : input.toString(), baseInit);
 }) as unknown as typeof fetch;
 
+/**
+ * Perplexity compatibility shim (#1046). Perplexity's `/v1/embeddings`
+ * endpoint is OpenAI-shaped but diverges on two points that break the AI
+ * SDK's openai-compatible adapter:
+ *   - `encoding_format` only accepts 'base64_int8' (default) or
+ *     'base64_binary'; the SDK sends 'float', which Perplexity rejects.
+ *     Force 'base64_int8' on the wire.
+ *   - The response `embedding` is a base64 string encoding SIGNED INT8
+ *     components (natively quantized output). The SDK schema expects
+ *     `number[]` — decode Int8Array → number[] here. Cosine similarity is
+ *     scale-invariant, so the raw int8 components rank correctly.
+ * `dimensions` is Perplexity's native field name — no translation needed
+ * (dims.ts emits it directly). Layer 1/Layer 2 OOM caps mirror the Voyage
+ * pattern.
+ *
+ * Exported for tests (behavioral coverage of the int8 decode); not part of
+ * the public gateway API.
+ */
+export const perplexityCompatFetch = (async (input: RequestInfo | URL, init?: RequestInit) => {
+  // OUTBOUND: force the encoding Perplexity actually accepts.
+  if (init?.body && typeof init.body === 'string') {
+    try {
+      const parsed = JSON.parse(init.body);
+      if (parsed && typeof parsed === 'object' && parsed.encoding_format !== 'base64_int8') {
+        parsed.encoding_format = 'base64_int8';
+        // Drop Content-Length so fetch recomputes from the new body.
+        const headers = new Headers(init.headers ?? {});
+        headers.delete('content-length');
+        init = { ...init, body: JSON.stringify(parsed), headers };
+      }
+    } catch {
+      // Body wasn't JSON — pass through untouched.
+    }
+  }
+
+  const resp = await fetch(input as any, init);
+  if (!resp.ok) return resp;
+  const ct = resp.headers.get('content-type') ?? '';
+  if (!ct.toLowerCase().includes('application/json')) return resp;
+
+  // Layer 1: Content-Length pre-check BEFORE the body is parsed.
+  const contentLengthHeader = resp.headers.get('content-length');
+  if (contentLengthHeader) {
+    const len = parseInt(contentLengthHeader, 10);
+    if (Number.isFinite(len) && len > MAX_PERPLEXITY_RESPONSE_BYTES) {
+      throw new PerplexityResponseTooLargeError(
+        `Perplexity response Content-Length=${len} exceeds ${MAX_PERPLEXITY_RESPONSE_BYTES} bytes — ` +
+        `likely compromised endpoint or misconfiguration`,
+      );
+    }
+  }
+
+  // INBOUND: decode base64 int8 embeddings to number[] so the SDK's Zod
+  // schema validates.
+  try {
+    const json: any = await resp.clone().json();
+    if (!json || typeof json !== 'object') return resp;
+    let modified = false;
+    if (Array.isArray(json.data)) {
+      for (const item of json.data) {
+        if (item && typeof item.embedding === 'string') {
+          // Layer 2: per-embedding cap for chunked responses that skipped
+          // Layer 1. base64 → bytes is the canonical 0.75 ratio.
+          const estDecoded = Math.ceil(item.embedding.length * 0.75);
+          if (estDecoded > MAX_PERPLEXITY_RESPONSE_BYTES) {
+            throw new PerplexityResponseTooLargeError(
+              `Perplexity embedding base64 exceeds ${MAX_PERPLEXITY_RESPONSE_BYTES} bytes ` +
+              `(estimated ${estDecoded} bytes from ${item.embedding.length} base64 chars)`,
+            );
+          }
+          // base64_int8: one signed int8 per component.
+          const bytes = Buffer.from(item.embedding, 'base64');
+          item.embedding = Array.from(new Int8Array(bytes.buffer, bytes.byteOffset, bytes.byteLength));
+          modified = true;
+        }
+      }
+    }
+    if (json.usage && typeof json.usage === 'object' && json.usage.prompt_tokens === undefined) {
+      json.usage.prompt_tokens = typeof json.usage.total_tokens === 'number'
+        ? json.usage.total_tokens
+        : 0;
+      modified = true;
+    }
+    if (!modified) return resp;
+    return new Response(JSON.stringify(json), {
+      status: resp.status,
+      statusText: resp.statusText,
+      headers: resp.headers,
+    });
+  } catch (err) {
+    // OOM-cap throws MUST propagate; anything else falls back to the
+    // original response (same contract as voyageCompatFetch).
+    if (err instanceof PerplexityResponseTooLargeError) throw err;
+    return resp;
+  }
+}) as unknown as typeof fetch;
+
 async function resolveEmbeddingProvider(modelStr: string): Promise<{ model: any; recipe: Recipe; modelId: string }> {
   const { parsed, recipe } = resolveRecipe(modelStr);
   assertTouchpoint(recipe, 'embedding', parsed.modelId, getExtendedModelsForProvider(parsed.providerId));
@@ -1360,6 +1469,8 @@ function instantiateEmbedding(recipe: Recipe, modelId: string, cfg: AIGatewayCon
           ? zeroEntropyCompatFetch
           : recipe.id === 'nvidia'
           ? nvidiaCompatFetch
+          : recipe.id === 'perplexity'
+          ? perplexityCompatFetch
           : openAICompatAsymmetricFetch);
       const client = createOpenAICompatible({
         name: recipe.id,

src/core/ai/recipes/index.ts

@@ -26,6 +26,7 @@ import { llamaServerReranker } from './llama-server-reranker.ts';
 import { moonshot } from './moonshot.ts';
 import { mistral } from './mistral.ts';
 import { nvidia } from './nvidia.ts';
+import { perplexity } from './perplexity.ts';
 
 const ALL: Recipe[] = [
   openai,
@@ -48,6 +49,7 @@ const ALL: Recipe[] = [
   moonshot,
   mistral,
   nvidia,
+  perplexity,
 ];
 
 /** Map from `provider:id` key to recipe. */

src/core/ai/recipes/perplexity.ts

@@ -0,0 +1,54 @@
+import type { Recipe } from '../types.ts';
+
+/**
+ * Perplexity's hosted embeddings API (#1046). OpenAI-shaped at
+ * `POST {base}/embeddings` but diverges on the wire:
+ *   - `encoding_format` only accepts 'base64_int8' (default) or
+ *     'base64_binary' — the AI SDK's 'float' default is rejected.
+ *   - The response `embedding` is a base64 string encoding SIGNED INT8
+ *     components (natively quantized output), not a float array.
+ * Both divergences are handled by perplexityCompatFetch in gateway.ts
+ * (force 'base64_int8' outbound; decode Int8Array → number[] inbound).
+ * Cosine similarity is scale-invariant, so the raw int8 components store
+ * and rank correctly as floats.
+ *
+ * Models (per docs.perplexity.ai/api-reference/embeddings-post, 2026-07):
+ *   - pplx-embed-v1-0.6b: dims 128..1024 (default 1024)
+ *   - pplx-embed-v1-4b:   dims 128..2560 (default 2560)
+ * The flexible-dim range validation lives in src/core/ai/dims.ts
+ * (PERPLEXITY_EMBEDDING_MAX_DIMS). default_dims is pinned at 1024 so both
+ * models work out of the box on a plain vector(N) column; users who want
+ * the 4b model's full 2560 width set `embedding_dimensions: 2560` and the
+ * existing halfvec path (dims > 2000) covers storage + ANN.
+ *
+ * Auth is PERPLEXITY_API_KEY only — deliberately NO OPENAI_API_KEY
+ * fallback (a Perplexity brain must never silently bill/route through
+ * OpenAI). If your key lives in PPLX_API_KEY, re-export it.
+ */
+export const perplexity: Recipe = {
+  id: 'perplexity',
+  name: 'Perplexity',
+  tier: 'openai-compat',
+  implementation: 'openai-compatible',
+  base_url_default: 'https://api.perplexity.ai/v1',
+  auth_env: {
+    required: ['PERPLEXITY_API_KEY'],
+    setup_url: 'https://www.perplexity.ai/settings/api',
+  },
+  touchpoints: {
+    embedding: {
+      models: ['pplx-embed-v1-0.6b', 'pplx-embed-v1-4b'],
+      default_dims: 1024,
+      cost_per_1m_tokens_usd: 0.03, // pplx-embed-v1-4b; 0.6b is $0.004/M
+      price_last_verified: '2026-07-21',
+      // Perplexity enforces 120K combined tokens (and 512 texts) per
+      // request. Same pre-split posture as Voyage: assume a dense
+      // tokenizer (1 char ≈ 1 token) at 0.5 utilization; the gateway's
+      // recursive halving is the runtime safety net.
+      max_batch_tokens: 120_000,
+      chars_per_token: 1,
+      safety_factor: 0.5,
+    },
+  },
+  setup_hint: 'Get an API key at https://www.perplexity.ai/settings/api, then `export PERPLEXITY_API_KEY=...` (re-export PPLX_API_KEY if that is where your key lives).',
+};

src/core/embedding-dim-check.ts

@@ -32,6 +32,10 @@ import {
   nvidiaEmbeddingDim,
   nvidiaEmbeddingDimOptions,
   supportsNvidiaEmbeddingDimension,
+  isPerplexityEmbeddingModel,
+  isValidPerplexityDim,
+  maxPerplexityEmbeddingDim,
+  PERPLEXITY_MIN_DIMS,
 } from './ai/dims.ts';
 
 /**
@@ -462,6 +466,15 @@ function isCustomDimValidForProvider(
         `(allowed: ${ZEROENTROPY_VALID_DIMS.join(', ')}).`,
     };
   }
+  if (recipe.id === 'perplexity' && isPerplexityEmbeddingModel(modelId)) {
+    if (isValidPerplexityDim(modelId, requestedDims)) return { valid: true, error: '' };
+    return {
+      valid: false,
+      error:
+        `Perplexity ${modelId} accepts dimensions ${PERPLEXITY_MIN_DIMS}..${maxPerplexityEmbeddingDim(modelId)}, ` +
+        `got ${requestedDims}.`,
+    };
+  }
   if (recipe.id === 'openai' && isOpenAITextEmbedding3Model(modelId)) {
     if (isValidOpenAITextEmbedding3Dim(modelId, requestedDims)) return { valid: true, error: '' };
     const maxDim = maxOpenAITextEmbedding3Dim(modelId);

src/core/embedding-pricing.ts

@@ -40,6 +40,9 @@ export const EMBEDDING_PRICING: Record<string, EmbeddingPricing> = {
   // Mistral (https://mistral.ai/pricing/api/, verified 2026-07-19)
   'mistral:mistral-embed':         { pricePerMTok: 0.10 },
   'mistral:mistral-embed-2312':    { pricePerMTok: 0.10 },
+  // Perplexity (https://docs.perplexity.ai/getting-started/pricing, verified 2026-07-21)
+  'perplexity:pplx-embed-v1-0.6b': { pricePerMTok: 0.004 },
+  'perplexity:pplx-embed-v1-4b':   { pricePerMTok: 0.03 },
 };
 
 export type PriceLookupResult =

test/ai/recipe-perplexity.test.ts

@@ -0,0 +1,142 @@
+/**
+ * #1046 — Perplexity hosted embeddings (pplx-embed-v1-*).
+ *
+ * Covers the three seams the recipe touches:
+ *  - recipe registration + auth (PERPLEXITY_API_KEY only, never OPENAI_API_KEY)
+ *  - flexible-dim validation (128..native max) in dims.ts + the init
+ *    preflight (resolveSchemaEmbeddingDim), incl. the >2000-dim 4b case
+ *  - perplexityCompatFetch: forces encoding_format=base64_int8 outbound and
+ *    decodes the base64 int8 embedding payload to number[] inbound
+ */
+import { afterEach, describe, expect, test } from 'bun:test';
+import {
+  dimsProviderOptions,
+  isPerplexityEmbeddingModel,
+  isValidPerplexityDim,
+  maxPerplexityEmbeddingDim,
+} from '../../src/core/ai/dims.ts';
+import { getRecipe, RECIPES } from '../../src/core/ai/recipes/index.ts';
+import { perplexity } from '../../src/core/ai/recipes/perplexity.ts';
+import { defaultResolveAuth, perplexityCompatFetch } from '../../src/core/ai/gateway.ts';
+import { AIConfigError } from '../../src/core/ai/errors.ts';
+import { resolveSchemaEmbeddingDim } from '../../src/core/embedding-dim-check.ts';
+import { lookupEmbeddingPrice } from '../../src/core/embedding-pricing.ts';
+
+describe('recipe: perplexity', () => {
+  test('registered as an OpenAI-compatible embedding provider', () => {
+    expect(RECIPES.has('perplexity')).toBe(true);
+    expect(getRecipe('perplexity')).toBe(perplexity);
+    expect(perplexity.tier).toBe('openai-compat');
+    expect(perplexity.implementation).toBe('openai-compatible');
+    expect(perplexity.base_url_default).toBe('https://api.perplexity.ai/v1');
+    const e = perplexity.touchpoints.embedding!;
+    expect(e.models).toEqual(['pplx-embed-v1-0.6b', 'pplx-embed-v1-4b']);
+    expect(e.default_dims).toBe(1024);
+    expect(e.max_batch_tokens).toBe(120_000);
+  });
+
+  test('auth is PERPLEXITY_API_KEY bearer — no OPENAI_API_KEY fallback', () => {
+    expect(perplexity.resolveAuth).toBeUndefined();
+    expect(perplexity.auth_env?.required).toEqual(['PERPLEXITY_API_KEY']);
+    expect(defaultResolveAuth(perplexity, { PERPLEXITY_API_KEY: 'fake-pplx' }, 'embedding')).toEqual({
+      headerName: 'Authorization',
+      token: 'Bearer fake-pplx',
+    });
+    // An OPENAI_API_KEY in the env must NOT satisfy Perplexity auth.
+    expect(() => defaultResolveAuth(perplexity, { OPENAI_API_KEY: 'sk-test' }, 'embedding')).toThrow(AIConfigError);
+  });
+
+  test('dims: 128..native-max range per model', () => {
+    expect(isPerplexityEmbeddingModel('pplx-embed-v1-4b')).toBe(true);
+    expect(maxPerplexityEmbeddingDim('pplx-embed-v1-4b')).toBe(2560);
+    expect(maxPerplexityEmbeddingDim('pplx-embed-v1-0.6b')).toBe(1024);
+    expect(isValidPerplexityDim('pplx-embed-v1-4b', 2560)).toBe(true);
+    expect(isValidPerplexityDim('pplx-embed-v1-4b', 128)).toBe(true);
+    expect(isValidPerplexityDim('pplx-embed-v1-4b', 64)).toBe(false);
+    expect(isValidPerplexityDim('pplx-embed-v1-0.6b', 2560)).toBe(false);
+  });
+
+  test('dimsProviderOptions emits native `dimensions`, fails loud out of range', () => {
+    expect(dimsProviderOptions('openai-compatible', 'pplx-embed-v1-4b', 2560)).toEqual({
+      openaiCompatible: { dimensions: 2560 },
+    });
+    // Symmetric provider — inputType never emitted.
+    expect(dimsProviderOptions('openai-compatible', 'pplx-embed-v1-4b', 1024, 'query')).toEqual({
+      openaiCompatible: { dimensions: 1024 },
+    });
+    expect(() => dimsProviderOptions('openai-compatible', 'pplx-embed-v1-0.6b', 2560)).toThrow(AIConfigError);
+  });
+
+  test('init preflight accepts the 4b model at its native 2560 dims (halfvec territory)', () => {
+    const res = resolveSchemaEmbeddingDim({
+      embedding_model: 'perplexity:pplx-embed-v1-4b',
+      embedding_dimensions: 2560,
+    });
+    expect(res).toEqual({
+      ok: true,
+      dim: 2560,
+      model: 'perplexity:pplx-embed-v1-4b',
+      provider: 'perplexity',
+      recipeDefault: 1024,
+    });
+    const bad = resolveSchemaEmbeddingDim({
+      embedding_model: 'perplexity:pplx-embed-v1-4b',
+      embedding_dimensions: 4096,
+    });
+    expect(bad.ok).toBe(false);
+  });
+
+  test('embedding pricing table knows both models', () => {
+    expect(lookupEmbeddingPrice('perplexity:pplx-embed-v1-4b')).toMatchObject({ kind: 'known', pricePerMTok: 0.03 });
+    expect(lookupEmbeddingPrice('perplexity:pplx-embed-v1-0.6b')).toMatchObject({ kind: 'known', pricePerMTok: 0.004 });
+  });
+});
+
+describe('perplexityCompatFetch — int8 wire shim', () => {
+  const realFetch = globalThis.fetch;
+  afterEach(() => {
+    globalThis.fetch = realFetch;
+  });
+
+  test('forces encoding_format=base64_int8 outbound and decodes int8 base64 inbound', async () => {
+    const int8 = new Int8Array([3, -7, 127, -128]);
+    const b64 = Buffer.from(int8.buffer).toString('base64');
+    let sentBody: any;
+    globalThis.fetch = (async (_input: any, init?: RequestInit) => {
+      sentBody = JSON.parse(init!.body as string);
+      return new Response(
+        JSON.stringify({
+          object: 'list',
+          model: 'pplx-embed-v1-4b',
+          data: [{ object: 'embedding', index: 0, embedding: b64 }],
+          usage: { prompt_tokens: 4, total_tokens: 4 },
+        }),
+        { status: 200, headers: { 'content-type': 'application/json' } },
+      );
+    }) as any;
+
+    const resp = await (perplexityCompatFetch as any)('https://api.perplexity.ai/v1/embeddings', {
+      method: 'POST',
+      headers: { 'content-type': 'application/json' },
+      // The AI SDK sends encoding_format:'float' — Perplexity rejects it.
+      body: JSON.stringify({ model: 'pplx-embed-v1-4b', input: ['hi'], encoding_format: 'float', dimensions: 4 }),
+    });
+
+    expect(sentBody.encoding_format).toBe('base64_int8');
+    expect(sentBody.dimensions).toBe(4); // native field, untouched
+    const json = await resp.json();
+    expect(json.data[0].embedding).toEqual([3, -7, 127, -128]);
+    expect(json.usage.prompt_tokens).toBe(4);
+  });
+
+  test('non-JSON and error responses pass through untouched', async () => {
+    globalThis.fetch = (async () =>
+      new Response('nope', { status: 401, headers: { 'content-type': 'text/plain' } })) as any;
+    const resp = await (perplexityCompatFetch as any)('https://api.perplexity.ai/v1/embeddings', {
+      method: 'POST',
+      body: JSON.stringify({ model: 'pplx-embed-v1-4b', input: ['hi'] }),
+    });
+    expect(resp.status).toBe(401);
+    expect(await resp.text()).toBe('nope');
+  });
+});

test/doctor-timeline-metric-labels-2298.test.ts

@@ -1,155 +0,0 @@
-/**
- * Issue #2298 — timeline metric presentation contract.
- *
- * Authoritative upstream semantics (src/core/types.ts):
- *   - Metric A `timeline_coverage` (entity-scoped, fraction 0–1):
- *       eligible entity pages WITH a timeline entry / eligible entity pages
- *     -> surfaced by `graph_coverage` check AND `get_health` CLI entity line.
- *   - Metric B `timeline_coverage_score` (whole-brain, 0–15 brain-score component):
- *       all pages WITH a timeline entry / all pages
- *     -> surfaced by `brain_score` component breakdown AND (separately) CLI.
- *
- * The two have DIFFERENT numerators/denominators. This PR labels each
- * explicitly and keeps BOTH the entity CLI line and the whole-brain line.
- *
- * Tests (no private EriadorMu data, no production/home DB, no network):
- *   - numeric denominator assertions (Metric A = 50%, Metric B = 4/15)
- *   - doctor rendered-message assertions (exact labels, no ambiguous old label)
- *   - CLI rendered-output assertions (exact lines, guard matrix)
- *   - red/green: same assertions FAIL on origin/master, PASS on this branch
- *
- * Scoring formula UNCHANGED. Canonical PGLite fixture via resetPgliteState.
- */
-
-import { describe, expect, test, beforeAll, afterAll, beforeEach } from 'bun:test';
-import { PGLiteEngine } from '../src/core/pglite-engine.ts';
-import { sqlQueryForEngine } from '../src/core/sql-query.ts';
-import { resetPgliteState } from './helpers/reset-pglite.ts';
-import { buildChecks } from '../src/commands/doctor.ts';
-import { formatResult } from '../src/cli.ts';
-
-let engine: PGLiteEngine;
-
-async function seedFourPages(eng: PGLiteEngine): Promise<void> {
-  const sql = sqlQueryForEngine(eng);
-  // 2 eligible entity pages, 2 technical/non-entity pages.
-  // Only ONE entity page has a timeline entry; only ONE total page does.
-  await sql`
-    INSERT INTO pages (slug, source_id, type, title, compiled_truth, frontmatter, content_hash, created_at, updated_at)
-    VALUES
-      ('acme-example', 'default', 'company', 'Acme', '', '{}', 'h1', now(), now()),
-      ('alice-example', 'default', 'person', 'Alice', '', '{}', 'h2', now(), now()),
-      ('technical-a', 'default', 'note', 'Tech A', '', '{}', 'h3', now(), now()),
-      ('technical-b', 'default', 'note', 'Tech B', '', '{}', 'h4', now(), now())
-  `;
-  const companyId = (await sql`SELECT id FROM pages WHERE slug='acme-example'`)[0].id as number;
-  await sql`INSERT INTO timeline_entries (page_id, date, source, summary, detail)
-    VALUES (${companyId}, CURRENT_DATE, 'test', 'milestone', '{}')`;
-}
-
-beforeAll(async () => {
-  engine = new PGLiteEngine();
-  await engine.connect({});
-  await engine.initSchema();
-});
-
-afterAll(async () => {
-  await engine.disconnect();
-});
-
-beforeEach(async () => {
-  await resetPgliteState(engine);
-});
-
-describe('issue #2298 — numeric denominator semantics', () => {
-  test('entity timeline coverage = 1/2 = 50% (2 eligible entities, 1 with timeline)', async () => {
-    await seedFourPages(engine);
-    const health = await engine.getHealth();
-    expect(health.timeline_coverage).toBeDefined();
-    expect(Math.round((health.timeline_coverage ?? 0) * 100)).toBe(50);
-  });
-
-  test('whole-brain timeline density = 1/4 -> score 4/15 (4 total pages, 1 with timeline)', async () => {
-    await seedFourPages(engine);
-    const health = await engine.getHealth();
-    expect(health.timeline_coverage_score).toBeDefined();
-    expect(health.timeline_coverage_score).toBe(4);
-  });
-
-  test('the two metrics use independent denominators', async () => {
-    await seedFourPages(engine);
-    const health = await engine.getHealth();
-    expect(Math.round((health.timeline_coverage ?? 0) * 100)).toBe(50);
-    expect(health.timeline_coverage_score ?? 0).toBe(4);
-    // 50% (entity, /2) != 26.7% (whole-brain, /4). Provably distinct.
-    expect(Math.round(((health.timeline_coverage_score ?? 0) / 15) * 100)).not.toBe(50);
-  });
-});
-
-describe('issue #2298 — doctor rendered-message contract', () => {
-  test('graph_coverage renders entity-scoped label with 50%', async () => {
-    await seedFourPages(engine);
-    const checks = await buildChecks(engine, [], null);
-    const graph = checks.find((c) => c.name === 'graph_coverage');
-    expect(graph, 'graph_coverage check must be present').toBeDefined();
-    expect(graph!.message).toContain('entity timeline coverage 50%');
-    // ambiguous old label must NOT be present
-    expect(graph!.message).not.toMatch(/timeline 50%/);
-    expect(graph!.message).not.toMatch(/timeline \(entity, brain score\)/);
-  });
-
-  test('brain_score renders whole-brain density label 4/15', async () => {
-    await seedFourPages(engine);
-    const checks = await buildChecks(engine, [], null);
-    const brain = checks.find((c) => c.name === 'brain_score');
-    expect(brain, 'brain_score check must be present').toBeDefined();
-    expect(brain!.message).toContain('timeline density (all pages) 4/15');
-    // wrong labels must NOT be present
-    expect(brain!.message).not.toMatch(/timeline 4\/15/);
-    expect(brain!.message).not.toMatch(/timeline \(entity, brain score\)/);
-    // brain-score component must NOT carry the word "entity" (it is whole-brain)
-    const timelinePart = brain!.message.split('timeline density (all pages) 4/15')[0] + 'timeline density (all pages) 4/15';
-    expect(timelinePart).not.toMatch(/entity/);
-  });
-});
-
-describe('issue #2298 — CLI get_health rendered-output contract', () => {
-  function fakeHealth(overrides: Record<string, unknown>): any {
-    return {
-      embed_coverage: 1, missing_embeddings: 0, stale_pages: 0, orphan_pages: 0,
-      link_coverage: 1, timeline_coverage: 0.5, timeline_coverage_score: 4,
-      most_connected: [], ...overrides,
-    };
-  }
-
-  test('both entity and whole-brain lines render, no undefined/15', () => {
-    const out = formatResult('get_health', fakeHealth({}));
-    expect(out).toContain('Timeline coverage (entity pages): 50.0%');
-    expect(out).toContain('Timeline density (all pages): 4/15');
-    expect(out).not.toContain('undefined/15');
-    expect(out).not.toContain('Timeline coverage (entities)');
-    expect(out).not.toMatch(/timeline \(entity, brain score\)/);
-    expect(out).not.toMatch(/bare "timeline 4\/15"/);
-  });
-
-  test('guard matrix: entity present, whole-brain absent -> only entity line', () => {
-    const out = formatResult('get_health', fakeHealth({ timeline_coverage_score: undefined }));
-    expect(out).toContain('Timeline coverage (entity pages): 50.0%');
-    expect(out).not.toContain('Timeline density (all pages)');
-    expect(out).not.toContain('undefined/15');
-  });
-
-  test('guard matrix: whole-brain present, entity absent -> only whole-brain line', () => {
-    const out = formatResult('get_health', fakeHealth({ timeline_coverage: undefined }));
-    expect(out).toContain('Timeline density (all pages): 4/15');
-    expect(out).not.toContain('Timeline coverage (entity pages)');
-    expect(out).not.toContain('undefined/15');
-  });
-
-  test('guard matrix: both absent -> neither timeline line, never undefined/15', () => {
-    const out = formatResult('get_health', fakeHealth({ timeline_coverage: undefined, timeline_coverage_score: undefined }));
-    expect(out).not.toContain('Timeline coverage (entity pages)');
-    expect(out).not.toContain('Timeline density (all pages)');
-    expect(out).not.toContain('undefined/15');
-  });
-});