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https://github.com/garrytan/gbrain.git
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Compare commits
3
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
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60fb33c0d9 | ||
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11ed0871c2 | ||
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595eeb7d6f |
+10
-5
@@ -170,10 +170,14 @@ export async function runImport(
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||||
// v0.22.13 (PR #490 Q2): shared parseWorkers helper rejects bad input
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||||
// (--workers 0, -3, "foo") with a loud error instead of silently falling
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||||
// through to 1. Mirrors sync.ts's flag handling.
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const { parseWorkers } = await import('../core/sync-concurrency.ts');
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let workerCount: number;
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const { parseWorkers, autoConcurrency } = await import('../core/sync-concurrency.ts');
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// #1207: undefined (no --workers flag) defers to autoConcurrency below —
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||||
// the shared sync/import policy (PGLite → 1, >100 files → 4) — instead of
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// hardcoding serial. Large Postgres imports stop paying one embedding
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||||
// round-trip per file in sequence.
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let workerCount: number | undefined;
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try {
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workerCount = parseWorkers(workersArg ?? undefined) ?? 1;
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workerCount = parseWorkers(workersArg ?? undefined);
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} catch (e) {
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console.error(e instanceof Error ? e.message : String(e));
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process.exit(1);
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@@ -252,8 +256,9 @@ export async function runImport(
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}
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const files = resumeFilter(allFiles, dir, completed);
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||||
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// Determine actual worker count
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const actualWorkers = workerCount > 1 ? workerCount : 1;
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||||
// Determine actual worker count. Explicit --workers wins; otherwise the
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||||
// shared autoConcurrency policy decides from engine kind + file count.
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||||
const actualWorkers = autoConcurrency(engine, files.length, workerCount);
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||||
if (actualWorkers > 1) {
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console.log(`Using ${actualWorkers} parallel workers`);
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}
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||||
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||||
@@ -197,7 +197,7 @@ export interface SyncResult {
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/** Pages re-embedded during this sync's auto-embed step. 0 if --no-embed or skipped. */
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||||
embedded: number;
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||||
pagesAffected: string[];
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||||
failedFiles?: number; // count of per-file import/sync failures (Bug 9)
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||||
failedFiles?: number; // count of parse failures (Bug 9)
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||||
/**
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* v0.41.13.0 partial-sync fields (only set when status === 'partial').
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||||
*
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||||
@@ -3183,7 +3183,7 @@ async function performSyncInner(engine: BrainEngine, opts: SyncOpts): Promise<Sy
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await clearOpCheckpoint(engine, ckpt.target);
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};
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// issue #1939 adversarial finding #1: a file that failed to import (open ledger
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||||
// issue #1939 adversarial finding #1: a file that failed to parse (open ledger
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// row) and is then deleted/renamed-away never re-enters failedFiles and never
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// imports, so its row would never clear and would age doctor to a permanent
|
||||
// FAIL. Treat removed paths as resolved so the ledger self-heals.
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||||
@@ -3215,9 +3215,9 @@ async function performSyncInner(engine: BrainEngine, opts: SyncOpts): Promise<Sy
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} else {
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const fileFailCount = failedFiles.filter(f => isSkippablePath(f.path)).length;
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serr(
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||||
`\nSync blocked: ${fileFailCount} file(s) failed to import:\n` +
|
||||
`\nSync blocked: ${fileFailCount} file(s) failed to parse:\n` +
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`${codeBreakdown}\n\n` +
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||||
`Fix the listed file errors and re-run, or use 'gbrain sync --skip-failed' to ` +
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||||
`Fix the frontmatter and re-run, or use 'gbrain sync --skip-failed' to ` +
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||||
`acknowledge and move on. A file that keeps failing auto-skips after ` +
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||||
`${resolveAutoSkipThreshold()} consecutive syncs.`,
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||||
);
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@@ -5355,7 +5355,7 @@ function printSyncResult(result: SyncResult, sink: NodeJS.WriteStream = process.
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case 'dry_run':
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break; // already printed in performSync
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||||
case 'blocked_by_failures':
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write(`Sync BLOCKED at ${result.toCommit.slice(0, 8)}: ${result.failedFiles ?? 0} file(s) failed to import.`);
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write(`Sync BLOCKED at ${result.toCommit.slice(0, 8)}: ${result.failedFiles ?? 0} file(s) failed to parse.`);
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write(` See ~/.gbrain/sync-failures.jsonl for details, or run 'gbrain doctor'.`);
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write(` Fix the files then re-run 'gbrain sync', or 'gbrain sync --skip-failed' to move on.`);
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break;
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+24
-6
@@ -1513,12 +1513,21 @@ export async function embed(texts: string[], opts?: EmbedOpts): Promise<Float32A
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const embedding = recipe.touchpoints?.embedding;
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const maxBatchTokens = embedding?.max_batch_tokens;
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||||
const maxBatchCount = embedding?.max_batch_count;
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const charsPerToken = embedding?.chars_per_token ?? DEFAULT_CHARS_PER_TOKEN;
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||||
|
||||
// Pre-split is gated on max_batch_tokens. Recipes without it (e.g. OpenAI)
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||||
// ride the fast path: one embedMany call, no recursion safety net.
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const batches = maxBatchTokens
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||||
? splitByTokenBudget(truncated, Math.floor(maxBatchTokens * effectiveSafetyFactor(recipe)), charsPerToken)
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||||
// Pre-split is gated on max_batch_tokens / max_batch_count. Recipes with
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||||
// neither (e.g. OpenAI) ride the fast path: one embedMany call, no
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||||
// recursion safety net.
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const batches = (maxBatchTokens || maxBatchCount)
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? splitByTokenBudget(
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truncated,
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maxBatchTokens
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||||
? Math.floor(maxBatchTokens * effectiveSafetyFactor(recipe))
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||||
: Number.MAX_SAFE_INTEGER,
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charsPerToken,
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maxBatchCount,
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||||
)
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: [truncated];
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||||
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const allEmbeddings: Float32Array[] = [];
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@@ -1568,6 +1577,9 @@ export async function embed(texts: string[], opts?: EmbedOpts): Promise<Float32A
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* responsible for applying any safety-factor shrink before passing in.
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||||
* @param charsPerToken - Provider-specific character density. Defaults to
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||||
* `DEFAULT_CHARS_PER_TOKEN` (4) when omitted, matching OpenAI tiktoken.
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||||
* @param maxBatchCount - #1199: optional cap on INPUTS per sub-batch, for
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||||
* providers that reject batches by count (DashScope: 10). When omitted,
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||||
* only the token budget governs.
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||||
*
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||||
* @internal exported for tests; not part of the public gateway API.
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||||
*/
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||||
@@ -1575,15 +1587,17 @@ export function splitByTokenBudget(
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texts: string[],
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budgetTokens: number,
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||||
charsPerToken: number = DEFAULT_CHARS_PER_TOKEN,
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||||
maxBatchCount?: number,
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||||
): string[][] {
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const ratio = charsPerToken > 0 ? charsPerToken : DEFAULT_CHARS_PER_TOKEN;
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const maxCount = maxBatchCount !== undefined && maxBatchCount > 0 ? maxBatchCount : Infinity;
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||||
const batches: string[][] = [];
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||||
let current: string[] = [];
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let currentTokens = 0;
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||||
|
||||
for (const text of texts) {
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const estTokens = Math.ceil(text.length / ratio);
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if (current.length > 0 && currentTokens + estTokens > budgetTokens) {
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||||
if (current.length > 0 && (currentTokens + estTokens > budgetTokens || current.length >= maxCount)) {
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batches.push(current);
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current = [];
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currentTokens = 0;
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@@ -1609,7 +1623,11 @@ export function isTokenLimitError(err: unknown): boolean {
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/token.*limit.*exceeded/i.test(msg) ||
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// OpenAI embeddings: "Invalid 'input': maximum request size is 300000 tokens per request."
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||||
/maximum request size.*tokens/i.test(msg) ||
|
||||
/max.*tokens.*per.*request/i.test(msg)
|
||||
/max.*tokens.*per.*request/i.test(msg) ||
|
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// DashScope: "batch size is invalid, it should not be larger than 10." (#1199)
|
||||
// Count-cap error, but recursive halving shrinks count too, so the same
|
||||
// safety net converges.
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||||
/batch size is invalid/i.test(msg)
|
||||
);
|
||||
}
|
||||
|
||||
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||||
@@ -31,6 +31,10 @@ export const dashscope: Recipe = {
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// path. Conservative declaration so the gateway pre-splits before
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// hitting whatever undocumented server-side limit exists.
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max_batch_tokens: 8192,
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||||
// #1199: DashScope hard-caps embeddings at 10 inputs per request
|
||||
// ("batch size is invalid, it should not be larger than 10"). The
|
||||
// token budget alone admits far more than 10 short chunks per batch.
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||||
max_batch_count: 10,
|
||||
// text-embedding-v3 mixes English + CJK heavily; the tokenizer is
|
||||
// closer to Voyage density than OpenAI tiktoken for CJK-dominant
|
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// content. Conservative chars_per_token=2 leaves headroom.
|
||||
|
||||
@@ -16,6 +16,15 @@ export const google: Recipe = {
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||||
dims_options: [768, 1536, 3072],
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cost_per_1m_tokens_usd: 0.15,
|
||||
price_last_verified: '2026-04-20',
|
||||
// #970: Gemini's documented limits are per-INPUT (2048 tokens,
|
||||
// silently truncated beyond) and per-REQUEST count (batchEmbedContents
|
||||
// caps at 100 inputs). There is no separate per-request token cap, so
|
||||
// the token budget is derived: 100 inputs × 2048 tokens. The count cap
|
||||
// binds first for typical chunk sizes. Do NOT copy the 2048 per-input
|
||||
// limit into max_batch_tokens — that would over-split 50×.
|
||||
max_batch_tokens: 204_800,
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||||
chars_per_token: 4,
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||||
max_batch_count: 100,
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||||
},
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expansion: {
|
||||
models: ['gemini-2.0-flash', 'gemini-2.0-flash-lite'],
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||||
|
||||
@@ -58,5 +58,8 @@ export function getRecipe(id: string): Recipe | undefined {
|
||||
}
|
||||
|
||||
export function listRecipes(): Recipe[] {
|
||||
return [...ALL];
|
||||
// Read the map (not ALL) so there is one source of truth — getRecipe,
|
||||
// model-resolver, and listRecipes all see the same registry, and tests
|
||||
// can inject a synthetic recipe via RECIPES to exercise registry walks.
|
||||
return [...RECIPES.values()];
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||||
}
|
||||
|
||||
@@ -46,6 +46,16 @@ export interface EmbeddingTouchpoint {
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||||
* Only consulted when `max_batch_tokens` is also set.
|
||||
*/
|
||||
chars_per_token?: number;
|
||||
/**
|
||||
* #1199: maximum number of INPUTS per embedding request, for providers
|
||||
* that hard-cap batch size by count rather than (or in addition to)
|
||||
* tokens — DashScope text-embedding-v3 rejects batches > 10 with
|
||||
* `InvalidParameter`, Gemini batchEmbedContents caps at 100 requests.
|
||||
* When set, the gateway's pre-split flushes a sub-batch at this count
|
||||
* even if the token budget still has room. Independent of
|
||||
* `max_batch_tokens`; either alone triggers the pre-split.
|
||||
*/
|
||||
max_batch_count?: number;
|
||||
/**
|
||||
* Budget-utilization ceiling in (0, 1]. The gateway pre-splits at
|
||||
* `safety_factor × max_batch_tokens` to leave headroom for tokenizer
|
||||
|
||||
+56
-6
@@ -79,15 +79,34 @@ export interface EmbedBatchOptions {
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||||
* and amplify rate-limit pressure.
|
||||
*/
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||||
maxRetries?: number;
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||||
/**
|
||||
* #1818: bounded parallelism across BATCH_SIZE sub-batches. Defaults to
|
||||
* `GBRAIN_EMBED_BATCH_CONCURRENCY` env, else 4. Results are
|
||||
* index-addressed so output order always matches input order. Set 1 to
|
||||
* force the pre-v0.42 serial dispatch.
|
||||
*/
|
||||
concurrency?: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* Embed a batch of texts via the gateway. Sub-batches of 100 so upstream
|
||||
* progress callbacks fire incrementally on large imports. The gateway owns
|
||||
* adaptive batch splitting and per-recipe token-budget logic; this paginator
|
||||
* is purely about progress-callback granularity.
|
||||
* owns progress-callback granularity and (#1818) bounded parallel dispatch
|
||||
* of the sub-batches — the embed-stale.ts worker-pool pattern, scoped down.
|
||||
*/
|
||||
const BATCH_SIZE = 100;
|
||||
const DEFAULT_EMBED_BATCH_CONCURRENCY = 4;
|
||||
|
||||
function resolveEmbedBatchConcurrency(options: EmbedBatchOptions): number {
|
||||
if (options.concurrency !== undefined) {
|
||||
return Math.max(1, Math.floor(options.concurrency));
|
||||
}
|
||||
const env = Number(process.env.GBRAIN_EMBED_BATCH_CONCURRENCY);
|
||||
if (Number.isFinite(env) && env >= 1) return Math.floor(env);
|
||||
return DEFAULT_EMBED_BATCH_CONCURRENCY;
|
||||
}
|
||||
|
||||
export async function embedBatch(
|
||||
texts: string[],
|
||||
options: EmbedBatchOptions = {},
|
||||
@@ -103,13 +122,44 @@ export async function embedBatch(
|
||||
if (texts.length <= BATCH_SIZE && !options.onBatchComplete) {
|
||||
return gatewayEmbed(texts, gwOpts);
|
||||
}
|
||||
const results: Float32Array[] = [];
|
||||
// #1818: dispatch sub-batches through a bounded worker pool instead of a
|
||||
// serial loop. Results are written into a preallocated index-addressed
|
||||
// array so output order matches input order regardless of completion
|
||||
// order; onBatchComplete reports a monotonic completed-embedding count.
|
||||
const slices: Array<{ start: number; texts: string[] }> = [];
|
||||
for (let i = 0; i < texts.length; i += BATCH_SIZE) {
|
||||
const slice = texts.slice(i, i + BATCH_SIZE);
|
||||
const out = await gatewayEmbed(slice, gwOpts);
|
||||
results.push(...out);
|
||||
options.onBatchComplete?.(results.length, texts.length);
|
||||
slices.push({ start: i, texts: texts.slice(i, i + BATCH_SIZE) });
|
||||
}
|
||||
const results = new Array<Float32Array>(texts.length);
|
||||
let next = 0;
|
||||
let done = 0;
|
||||
const numWorkers = Math.min(resolveEmbedBatchConcurrency(options), slices.length);
|
||||
// Once any sub-batch fails, `failed` stops the surviving workers from
|
||||
// dispatching FURTHER slices — the whole call is rejecting anyway, so
|
||||
// continuing would burn real provider spend in the background and fire
|
||||
// onBatchComplete after the caller already saw the failure (worst with
|
||||
// embedBatchWithBackoff, whose 429 backoff assumes nothing is in flight).
|
||||
// In-flight sibling calls still run to completion (bounded by numWorkers-1).
|
||||
let failed = false;
|
||||
const worker = async (): Promise<void> => {
|
||||
while (!failed && next < slices.length) {
|
||||
// NOTE: no local aborted-check here — an aborted signal makes the next
|
||||
// gatewayEmbed call throw (SDK-side), which rejects the pool. Returning
|
||||
// silently instead would resolve with holes in `results`.
|
||||
const slice = slices[next++];
|
||||
let out: Float32Array[];
|
||||
try {
|
||||
out = await gatewayEmbed(slice.texts, gwOpts);
|
||||
} catch (err) {
|
||||
failed = true;
|
||||
throw err;
|
||||
}
|
||||
for (let j = 0; j < out.length; j++) results[slice.start + j] = out[j];
|
||||
done += out.length;
|
||||
if (!failed) options.onBatchComplete?.(done, texts.length);
|
||||
}
|
||||
};
|
||||
await Promise.all(Array.from({ length: numWorkers }, () => worker()));
|
||||
return results;
|
||||
}
|
||||
|
||||
|
||||
@@ -1058,16 +1058,6 @@ export class PGLiteEngine implements BrainEngine {
|
||||
RETURNING id, source_id, slug, type, title, compiled_truth, timeline, frontmatter, content_hash, created_at, updated_at, effective_date, effective_date_source, import_filename, source_kind, source_uri, ingested_via, ingested_at`,
|
||||
[sourceId, slug, page.type, pageKind, page.title, page.compiled_truth, page.timeline || '', JSON.stringify(frontmatter), hash, effectiveDate, effectiveDateSource, importFilename, chunkerVersion, sourcePath, sourceKind, sourceUri, ingestedVia, ingestedAt]
|
||||
);
|
||||
// #2189: an INSERT … ON CONFLICT DO UPDATE … RETURNING that yields 0 rows
|
||||
// (e.g. a BEFORE trigger suppressing the write) previously crashed in
|
||||
// rowToPage with an opaque "undefined is not an object (row.deleted_at)".
|
||||
// Throw a diagnosable error naming the row instead. Mirrors postgres-engine.ts.
|
||||
if (!rows[0]) {
|
||||
throw new Error(
|
||||
`putPage: INSERT … RETURNING produced no row for slug='${slug}' source_id='${sourceId}'. ` +
|
||||
`A trigger or rule on the pages table may be suppressing the write.`
|
||||
);
|
||||
}
|
||||
return rowToPage(rows[0] as Record<string, unknown>);
|
||||
}
|
||||
|
||||
|
||||
@@ -1119,16 +1119,6 @@ export class PostgresEngine implements BrainEngine {
|
||||
ingested_at = COALESCE(EXCLUDED.ingested_at, pages.ingested_at)
|
||||
RETURNING id, source_id, slug, type, title, compiled_truth, timeline, frontmatter, content_hash, created_at, updated_at, effective_date, effective_date_source, import_filename, source_kind, source_uri, ingested_via, ingested_at
|
||||
`;
|
||||
// #2189: an INSERT … ON CONFLICT DO UPDATE … RETURNING that yields 0 rows
|
||||
// (e.g. a BEFORE trigger suppressing the write) previously crashed in
|
||||
// rowToPage with an opaque "undefined is not an object (row.deleted_at)".
|
||||
// Throw a diagnosable error naming the row instead. Mirrors pglite-engine.ts.
|
||||
if (!rows[0]) {
|
||||
throw new Error(
|
||||
`putPage: INSERT … RETURNING produced no row for slug='${slug}' source_id='${sourceId}'. ` +
|
||||
`A trigger or rule on the pages table may be suppressing the write.`
|
||||
);
|
||||
}
|
||||
return rowToPage(rows[0]);
|
||||
}
|
||||
|
||||
|
||||
@@ -39,6 +39,8 @@ import {
|
||||
__getShrinkStateForTests,
|
||||
} from '../../src/core/ai/gateway.ts';
|
||||
import { AIConfigError, AITransientError } from '../../src/core/ai/errors.ts';
|
||||
import { RECIPES } from '../../src/core/ai/recipes/index.ts';
|
||||
import type { Recipe } from '../../src/core/ai/types.ts';
|
||||
|
||||
// The last test in this file leaves the gateway configured with a remote
|
||||
// provider + fake key and a REAL embed transport. Without a final reset,
|
||||
@@ -93,6 +95,14 @@ function configureGoogle(): void {
|
||||
});
|
||||
}
|
||||
|
||||
function configureDashscope(): void {
|
||||
configureGateway({
|
||||
embedding_model: 'dashscope:text-embedding-v3',
|
||||
embedding_dimensions: 1024,
|
||||
env: { DASHSCOPE_API_KEY: 'sk-fake' },
|
||||
});
|
||||
}
|
||||
|
||||
// --------- 1. Pure helpers ---------
|
||||
|
||||
describe('splitByTokenBudget (pure helper)', () => {
|
||||
@@ -149,6 +159,27 @@ describe('splitByTokenBudget (pure helper)', () => {
|
||||
expect(splitByTokenBudget(texts, 96_000, 0)).toEqual(splitByTokenBudget(texts, 96_000, 4));
|
||||
expect(splitByTokenBudget(texts, 96_000, -1)).toEqual(splitByTokenBudget(texts, 96_000, 4));
|
||||
});
|
||||
|
||||
// #1199: count cap for providers that reject batches by input count.
|
||||
test('max_batch_count flushes even when token budget has room', () => {
|
||||
const texts = Array.from({ length: 25 }, (_, i) => `t${i}`);
|
||||
const result = splitByTokenBudget(texts, 1_000_000, 4, 10);
|
||||
expect(result.map(b => b.length)).toEqual([10, 10, 5]);
|
||||
expect(result.flat()).toEqual(texts);
|
||||
});
|
||||
|
||||
test('token budget still governs alongside max_batch_count', () => {
|
||||
const texts = ['a'.repeat(50_000), 'b'.repeat(50_000), 'c'.repeat(50_000)];
|
||||
const result = splitByTokenBudget(texts, 96_000, 1, 10);
|
||||
expect(result).toHaveLength(3);
|
||||
});
|
||||
|
||||
test('undefined / zero / negative max_batch_count is ignored', () => {
|
||||
const texts = Array.from({ length: 25 }, () => 'x');
|
||||
expect(splitByTokenBudget(texts, 1_000_000, 4, undefined)).toHaveLength(1);
|
||||
expect(splitByTokenBudget(texts, 1_000_000, 4, 0)).toHaveLength(1);
|
||||
expect(splitByTokenBudget(texts, 1_000_000, 4, -5)).toHaveLength(1);
|
||||
});
|
||||
});
|
||||
|
||||
describe('isTokenLimitError (pure helper)', () => {
|
||||
@@ -179,6 +210,12 @@ describe('isTokenLimitError (pure helper)', () => {
|
||||
expect(isTokenLimitError(new Error('Exceeded 300000 max tokens per request'))).toBe(true);
|
||||
});
|
||||
|
||||
test('matches DashScope batch-count error (#1199)', () => {
|
||||
expect(isTokenLimitError(new Error(
|
||||
'InvalidParameter: batch size is invalid, it should not be larger than 10.',
|
||||
))).toBe(true);
|
||||
});
|
||||
|
||||
test('does not match unrelated errors', () => {
|
||||
expect(isTokenLimitError(new Error('Connection refused'))).toBe(false);
|
||||
expect(isTokenLimitError(new Error('Invalid API key'))).toBe(false);
|
||||
@@ -387,26 +424,92 @@ describe('shrink-on-miss adaptive cache', () => {
|
||||
});
|
||||
});
|
||||
|
||||
// --------- 8. Pre-split count cap through public embed() (#1199 / #970) ---------
|
||||
|
||||
describe('embed() pre-split honors max_batch_count', () => {
|
||||
beforeEach(() => resetGateway());
|
||||
afterEach(() => __setEmbedTransportForTests(null));
|
||||
|
||||
test('dashscope never dispatches more than 10 inputs per call (#1199)', async () => {
|
||||
configureDashscope();
|
||||
const stub = mock(async ({ values }: { values: string[] }) => fakeEmbeddings(values, 1024));
|
||||
__setEmbedTransportForTests(stub as any);
|
||||
|
||||
// 25 short texts fit trivially in the 8192-token budget; without the
|
||||
// count cap they'd ship as ONE batch and DashScope would reject it.
|
||||
const texts = Array.from({ length: 25 }, (_, i) => `short-${i}`);
|
||||
const result = await embed(texts);
|
||||
|
||||
expect(result).toHaveLength(25);
|
||||
const callLengths = stub.mock.calls.map(([arg]) => (arg as { values: string[] }).values.length);
|
||||
expect(Math.max(...callLengths)).toBeLessThanOrEqual(10);
|
||||
expect(callLengths.reduce((a, b) => a + b, 0)).toBe(25);
|
||||
// Order preserved across sub-batches.
|
||||
expect((stub.mock.calls[0][0] as { values: string[] }).values[0]).toBe('short-0');
|
||||
});
|
||||
|
||||
test('google pre-splits at 100 inputs per batchEmbedContents call (#970)', async () => {
|
||||
configureGoogle();
|
||||
const stub = mock(async ({ values }: { values: string[] }) => fakeEmbeddings(values, 768));
|
||||
__setEmbedTransportForTests(stub as any);
|
||||
|
||||
const texts = Array.from({ length: 250 }, (_, i) => `g${i}`);
|
||||
const result = await embed(texts);
|
||||
|
||||
expect(result).toHaveLength(250);
|
||||
const callLengths = stub.mock.calls.map(([arg]) => (arg as { values: string[] }).values.length);
|
||||
expect(callLengths).toEqual([100, 100, 50]);
|
||||
});
|
||||
});
|
||||
|
||||
// --------- 7. Startup warning (D9-B) ---------
|
||||
|
||||
describe('startup warning for recipes missing max_batch_tokens', () => {
|
||||
beforeEach(() => resetGateway());
|
||||
|
||||
// #970 closed google's missing cap, so no registered recipe is capless
|
||||
// anymore. Inject a synthetic capless recipe to keep the warning path
|
||||
// covered for the NEXT recipe that forgets the field.
|
||||
const caplessRecipe: Recipe = {
|
||||
id: 'capless-test',
|
||||
name: 'Capless Test Provider',
|
||||
tier: 'openai-compat',
|
||||
implementation: 'openai-compatible',
|
||||
base_url_default: 'https://example.invalid/v1',
|
||||
auth_env: { required: [] },
|
||||
touchpoints: {
|
||||
embedding: { models: ['capless-embed-1'], default_dims: 768 },
|
||||
},
|
||||
};
|
||||
|
||||
function configureCapless(): void {
|
||||
configureGateway({
|
||||
embedding_model: 'capless-test:capless-embed-1',
|
||||
embedding_dimensions: 768,
|
||||
env: {},
|
||||
});
|
||||
}
|
||||
|
||||
test('configured missing-cap recipe warns once; unrelated recipes stay quiet', () => {
|
||||
const warnings: string[] = [];
|
||||
const original = console.warn;
|
||||
console.warn = (msg: string) => warnings.push(String(msg));
|
||||
RECIPES.set(caplessRecipe.id, caplessRecipe);
|
||||
try {
|
||||
configureOpenAI();
|
||||
expect(warnings.length).toBe(0);
|
||||
// #970 regression: google now declares max_batch_tokens → quiet.
|
||||
configureGoogle();
|
||||
expect(warnings.length).toBe(0);
|
||||
configureCapless();
|
||||
const firstCallCount = warnings.length;
|
||||
// Reconfigure: the warning should NOT re-fire for the same recipes
|
||||
// within one process (we already told the operator).
|
||||
configureGoogle();
|
||||
configureCapless();
|
||||
expect(warnings.length).toBe(firstCallCount);
|
||||
} finally {
|
||||
console.warn = original;
|
||||
RECIPES.delete(caplessRecipe.id);
|
||||
}
|
||||
|
||||
// The warning text should match the documented contract.
|
||||
@@ -415,11 +518,12 @@ describe('startup warning for recipes missing max_batch_tokens', () => {
|
||||
);
|
||||
expect(contractMatch.length).toBe(1);
|
||||
|
||||
// Voyage declares max_batch_tokens → suppressed. OpenAI is the
|
||||
// canonical fast-path recipe → also suppressed by id. Both must be
|
||||
// absent from the warnings.
|
||||
// Voyage + google declare max_batch_tokens → suppressed. OpenAI is the
|
||||
// canonical fast-path recipe → also suppressed by id. All must be
|
||||
// absent from the warnings; only the synthetic capless recipe fires.
|
||||
expect(warnings.find(w => w.includes('"voyage"'))).toBeUndefined();
|
||||
expect(warnings.find(w => w.includes('"openai"'))).toBeUndefined();
|
||||
expect(warnings.find(w => w.includes('"google"'))).toBeDefined();
|
||||
expect(warnings.find(w => w.includes('"google"'))).toBeUndefined();
|
||||
expect(warnings.find(w => w.includes('"capless-test"'))).toBeDefined();
|
||||
});
|
||||
});
|
||||
|
||||
@@ -52,16 +52,7 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
|
||||
}
|
||||
});
|
||||
|
||||
test('configureGateway warns for google only when google embedding is configured', () => {
|
||||
warnSpy.mockClear();
|
||||
resetGateway();
|
||||
configureGateway({ env: {} });
|
||||
let messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
|
||||
expect(
|
||||
messages.some(m => m.includes('"google"') && m.includes('without max_batch_tokens')),
|
||||
'google should not warn while OpenAI default is configured',
|
||||
).toBe(false);
|
||||
|
||||
test('configureGateway does NOT warn for google now that it declares batch caps (#970)', () => {
|
||||
warnSpy.mockClear();
|
||||
resetGateway();
|
||||
configureGateway({
|
||||
@@ -69,11 +60,20 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
|
||||
embedding_dimensions: 768,
|
||||
env: { GOOGLE_GENERATIVE_AI_API_KEY: 'fake' },
|
||||
});
|
||||
messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
|
||||
const messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
|
||||
expect(
|
||||
messages.some(m => m.includes('"google"') && m.includes('without max_batch_tokens')),
|
||||
'google should warn when configured because it has fixed-cap models',
|
||||
).toBe(true);
|
||||
'google declares max_batch_tokens/max_batch_count since #970 — no warning',
|
||||
).toBe(false);
|
||||
});
|
||||
|
||||
test('google recipe declares its derived batch caps (#970)', () => {
|
||||
const e = getRecipe('google')!.touchpoints.embedding!;
|
||||
// Count cap is the REAL Gemini limit (batchEmbedContents: 100 inputs);
|
||||
// the token budget is derived (100 × 2048 per-input tokens), NOT the
|
||||
// 2048 per-input limit — copying that verbatim would over-split 50×.
|
||||
expect(e.max_batch_count).toBe(100);
|
||||
expect(e.max_batch_tokens).toBe(204_800);
|
||||
});
|
||||
|
||||
test('every recipe with empty models[] declares user_provided_models OR has openai-fast-path', () => {
|
||||
|
||||
@@ -55,6 +55,11 @@ describe('recipe: dashscope', () => {
|
||||
expect(r.touchpoints.embedding!.chars_per_token).toBeGreaterThan(0);
|
||||
});
|
||||
|
||||
test('declares max_batch_count: 10 — DashScope rejects larger batches (#1199)', () => {
|
||||
const r = getRecipe('dashscope')!;
|
||||
expect(r.touchpoints.embedding!.max_batch_count).toBe(10);
|
||||
});
|
||||
|
||||
test('dimsProviderOptions threads dimensions for text-embedding-v3 (Matryoshka)', async () => {
|
||||
// Codex finding #1: DashScope text-embedding-v3 is Matryoshka 64-1024.
|
||||
// Without `dimensions` on the wire, user-selected non-default dims are
|
||||
|
||||
@@ -0,0 +1,161 @@
|
||||
/**
|
||||
* #1818: embedBatch dispatches its 100-input sub-batches through a bounded
|
||||
* worker pool (the embed-stale.ts concurrency pattern) instead of a serial
|
||||
* `for` loop. This file pins:
|
||||
*
|
||||
* - output order matches input order regardless of completion order
|
||||
* (index-addressed results)
|
||||
* - parallelism actually happens (max in-flight > 1) and stays bounded
|
||||
* (max in-flight <= configured concurrency)
|
||||
* - concurrency: 1 restores the serial pre-#1818 dispatch
|
||||
* - GBRAIN_EMBED_BATCH_CONCURRENCY env is honored when the option is unset
|
||||
* - onBatchComplete reports a monotonic completed count ending at total
|
||||
*
|
||||
* Transport is stubbed via the gateway's __setEmbedTransportForTests seam
|
||||
* (same pattern as test/ai/adaptive-embed-batch.test.ts). OpenAI recipe =
|
||||
* fast path (no pre-split), so each embedBatch sub-batch is exactly one
|
||||
* transport call.
|
||||
*/
|
||||
|
||||
import { afterAll, afterEach, beforeEach, describe, expect, test } from 'bun:test';
|
||||
import {
|
||||
configureGateway,
|
||||
resetGateway,
|
||||
__setEmbedTransportForTests,
|
||||
} from '../src/core/ai/gateway.ts';
|
||||
import { embedBatch } from '../src/core/embedding.ts';
|
||||
import { withEnv } from './helpers/with-env.ts';
|
||||
|
||||
const DIMS = 1536;
|
||||
|
||||
function configureOpenAI(): void {
|
||||
configureGateway({
|
||||
embedding_model: 'openai:text-embedding-3-large',
|
||||
embedding_dimensions: DIMS,
|
||||
env: { OPENAI_API_KEY: 'sk-fake' },
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Install a transport whose returned embedding encodes the GLOBAL input
|
||||
* index in dim 0 (texts are `t<N>`), so order can be asserted end-to-end.
|
||||
* Tracks the max number of concurrently in-flight transport calls.
|
||||
*/
|
||||
function installTrackingTransport(delayMs = 5): { maxInFlight: () => number } {
|
||||
let inFlight = 0;
|
||||
let maxInFlight = 0;
|
||||
__setEmbedTransportForTests((async ({ values }: { values: string[] }) => {
|
||||
inFlight++;
|
||||
maxInFlight = Math.max(maxInFlight, inFlight);
|
||||
await new Promise(r => setTimeout(r, delayMs));
|
||||
inFlight--;
|
||||
return {
|
||||
embeddings: values.map(v => {
|
||||
const idx = Number(v.slice(1));
|
||||
return Array.from({ length: DIMS }, (_, j) => (j === 0 ? idx : 0.1));
|
||||
}),
|
||||
};
|
||||
}) as any);
|
||||
return { maxInFlight: () => maxInFlight };
|
||||
}
|
||||
|
||||
const texts = Array.from({ length: 250 }, (_, i) => `t${i}`);
|
||||
|
||||
afterAll(() => resetGateway());
|
||||
|
||||
describe('embedBatch bounded parallelism (#1818)', () => {
|
||||
beforeEach(() => {
|
||||
resetGateway();
|
||||
configureOpenAI();
|
||||
});
|
||||
afterEach(() => {
|
||||
__setEmbedTransportForTests(null);
|
||||
});
|
||||
|
||||
test('default pool dispatches sub-batches in parallel, order preserved', async () => {
|
||||
const tracker = installTrackingTransport();
|
||||
const result = await embedBatch(texts, { onBatchComplete: () => {} });
|
||||
expect(result).toHaveLength(250);
|
||||
for (let i = 0; i < 250; i++) {
|
||||
expect(result[i][0]).toBe(i);
|
||||
}
|
||||
// 250 texts → 3 sub-batches; default concurrency 4 → all 3 in flight.
|
||||
expect(tracker.maxInFlight()).toBeGreaterThan(1);
|
||||
expect(tracker.maxInFlight()).toBeLessThanOrEqual(4);
|
||||
});
|
||||
|
||||
test('concurrency: 1 keeps the serial dispatch', async () => {
|
||||
const tracker = installTrackingTransport();
|
||||
const result = await embedBatch(texts, { concurrency: 1, onBatchComplete: () => {} });
|
||||
expect(result).toHaveLength(250);
|
||||
expect(tracker.maxInFlight()).toBe(1);
|
||||
});
|
||||
|
||||
test('GBRAIN_EMBED_BATCH_CONCURRENCY env bounds the pool when option unset', async () => {
|
||||
const tracker = installTrackingTransport();
|
||||
await withEnv({ GBRAIN_EMBED_BATCH_CONCURRENCY: '2' }, async () => {
|
||||
await embedBatch(texts, { onBatchComplete: () => {} });
|
||||
});
|
||||
expect(tracker.maxInFlight()).toBeGreaterThan(1);
|
||||
expect(tracker.maxInFlight()).toBeLessThanOrEqual(2);
|
||||
});
|
||||
|
||||
test('onBatchComplete reports a monotonic count ending at total', async () => {
|
||||
installTrackingTransport();
|
||||
const seen: number[] = [];
|
||||
await embedBatch(texts, {
|
||||
onBatchComplete: (done, total) => {
|
||||
expect(total).toBe(250);
|
||||
seen.push(done);
|
||||
},
|
||||
});
|
||||
expect(seen).toHaveLength(3); // 100 + 100 + 50 sub-batches
|
||||
for (let i = 1; i < seen.length; i++) {
|
||||
expect(seen[i]).toBeGreaterThan(seen[i - 1]);
|
||||
}
|
||||
expect(seen[seen.length - 1]).toBe(250);
|
||||
});
|
||||
|
||||
test('a failing sub-batch rejects the whole call', async () => {
|
||||
let call = 0;
|
||||
__setEmbedTransportForTests((async ({ values }: { values: string[] }) => {
|
||||
call++;
|
||||
if (call === 2) throw new Error('boom');
|
||||
await new Promise(r => setTimeout(r, 2));
|
||||
return { embeddings: values.map(() => Array.from({ length: DIMS }, () => 0.1)) };
|
||||
}) as any);
|
||||
await expect(embedBatch(texts, { onBatchComplete: () => {} })).rejects.toThrow();
|
||||
});
|
||||
|
||||
test('after a failure, surviving workers stop dispatching new slices', async () => {
|
||||
// 1000 texts → 10 slices, concurrency 2. First call fails immediately;
|
||||
// without the `failed` flag the second worker would keep draining all
|
||||
// 10 slices in the background AFTER embedBatch already rejected —
|
||||
// burning provider spend and firing onBatchComplete post-rejection.
|
||||
let calls = 0;
|
||||
const completions: number[] = [];
|
||||
__setEmbedTransportForTests((async ({ values }: { values: string[] }) => {
|
||||
calls++;
|
||||
if (calls === 1) throw new Error('boom');
|
||||
await new Promise(r => setTimeout(r, 5));
|
||||
return { embeddings: values.map(() => Array.from({ length: DIMS }, () => 0.1)) };
|
||||
}) as any);
|
||||
const many = Array.from({ length: 1000 }, (_, i) => `t${i}`);
|
||||
await expect(
|
||||
embedBatch(many, { concurrency: 2, onBatchComplete: d => completions.push(d) }),
|
||||
).rejects.toThrow('boom');
|
||||
const callsAtRejection = calls;
|
||||
await new Promise(r => setTimeout(r, 50)); // would-be background drain window
|
||||
expect(calls).toBe(callsAtRejection); // no new dispatch after rejection
|
||||
expect(calls).toBeLessThanOrEqual(2); // only the in-flight sibling ran
|
||||
expect(completions).toHaveLength(0); // no progress reported after failure
|
||||
});
|
||||
|
||||
test('single small batch without callback stays on the one-call fast path', async () => {
|
||||
const tracker = installTrackingTransport(1);
|
||||
const result = await embedBatch(['t0', 't1', 't2']);
|
||||
expect(result).toHaveLength(3);
|
||||
expect(result[1][0]).toBe(1);
|
||||
expect(tracker.maxInFlight()).toBe(1);
|
||||
});
|
||||
});
|
||||
@@ -19,7 +19,7 @@
|
||||
* overwrites this preload.
|
||||
*/
|
||||
import { configureGateway, getEmbeddingDimensions } from '../../src/core/ai/gateway.ts';
|
||||
import { beforeEach } from 'bun:test';
|
||||
import { afterEach, beforeEach } from 'bun:test';
|
||||
|
||||
const LEGACY_CONFIG = {
|
||||
embedding_model: 'openai:text-embedding-3-large',
|
||||
@@ -52,7 +52,7 @@ applyLegacy();
|
||||
// 2. file-local beforeAll → may overwrite to ZE/1280
|
||||
// Since beforeAll runs once per file BEFORE the first beforeEach,
|
||||
// file-local beforeAll wins for that file's tests. ✓
|
||||
beforeEach(() => {
|
||||
function applyLegacyIfEmpty() {
|
||||
try {
|
||||
// Only re-apply if the gateway was reset (or never configured).
|
||||
// Tests that explicitly configured a different model in their
|
||||
@@ -62,4 +62,28 @@ beforeEach(() => {
|
||||
} catch {
|
||||
applyLegacy();
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
beforeEach(applyLegacyIfEmpty);
|
||||
|
||||
// PR #3130 shard-order fix: beforeEach alone leaves ONE window open — a file
|
||||
// whose LAST afterEach calls resetGateway() poisons the NEXT file's
|
||||
// beforeAll, which runs BEFORE any beforeEach fires. A beforeAll there that
|
||||
// does engine.initSchema() then sizes the embedding column from the gateway
|
||||
// DEFAULTS (zembed-1/1280d) instead of the pinned legacy 1536, and every
|
||||
// 1536-d Float32Array fixture in that file dies with
|
||||
// "expected 1280 dimensions, not 1536". Which file pair collides is a
|
||||
// function of shard composition, so adding/removing ANY test file can
|
||||
// surface it (that is exactly how it bit shard 9).
|
||||
//
|
||||
// Preload hooks are registered before any file-local hooks, and bun runs
|
||||
// after-hooks inside-out (file-local afterEach first, then this one), so
|
||||
// this repairs the empty slot immediately after the poisoning reset —
|
||||
// before the next file's beforeAll can observe it.
|
||||
//
|
||||
// Known remaining window: a file whose afterAll() resets the gateway (no
|
||||
// hook runs between its afterAll and the next file's beforeAll). Files
|
||||
// that reset in afterAll and can precede a schema-creating file should
|
||||
// re-apply their own config, or the victim file should configureGateway()
|
||||
// explicitly in its beforeAll.
|
||||
afterEach(applyLegacyIfEmpty);
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
/**
|
||||
* #1207: `gbrain import` without `--workers` used to hardcode workerCount=1,
|
||||
* so a large Postgres import paid one serial embedding round-trip per file.
|
||||
* runImport now routes the default through the shared autoConcurrency policy
|
||||
* (PGLite → 1, >100 files on Postgres → DEFAULT_PARALLEL_WORKERS), while an
|
||||
* explicit `--workers N` still wins.
|
||||
*
|
||||
* The engine here is a minimal postgres-kind stub with no database_url in
|
||||
* config — runImport's parallel branch then falls back to serial processing
|
||||
* (its PR #490 guard) but the WORKER-COUNT DECISION (the thing #1207 fixes)
|
||||
* is still observable via the "Using N parallel workers" log line. Per-file
|
||||
* imports fail against the stub engine and are swallowed by runImport's
|
||||
* per-file catch; that's fine — this test pins the policy, not the import.
|
||||
*/
|
||||
|
||||
import { afterEach, beforeEach, describe, expect, test } from 'bun:test';
|
||||
import { mkdtempSync, writeFileSync, mkdirSync, rmSync, realpathSync } from 'fs';
|
||||
import { tmpdir } from 'os';
|
||||
import { join } from 'path';
|
||||
import { withEnv } from './helpers/with-env.ts';
|
||||
import { runImport } from '../src/commands/import.ts';
|
||||
|
||||
const fakePostgresEngine = {
|
||||
kind: 'postgres',
|
||||
executeRaw: async () => [],
|
||||
logIngest: async () => {},
|
||||
setConfig: async () => {},
|
||||
getConfig: async () => null,
|
||||
} as any;
|
||||
|
||||
let workspace: string;
|
||||
let brainDir: string;
|
||||
let logs: string[];
|
||||
const realLog = console.log;
|
||||
|
||||
beforeEach(() => {
|
||||
workspace = mkdtempSync(join(tmpdir(), 'gbrain-import-workers-home-'));
|
||||
mkdirSync(join(workspace, '.gbrain'), { recursive: true });
|
||||
brainDir = realpathSync(mkdtempSync(join(tmpdir(), 'gbrain-import-workers-brain-')));
|
||||
// 101 files: one past AUTO_CONCURRENCY_FILE_THRESHOLD (100).
|
||||
for (let i = 0; i < 101; i++) {
|
||||
writeFileSync(join(brainDir, `page-${i}.md`), `# Page ${i}\n\nbody ${i}\n`);
|
||||
}
|
||||
logs = [];
|
||||
console.log = (msg?: unknown) => logs.push(String(msg));
|
||||
});
|
||||
|
||||
afterEach(() => {
|
||||
console.log = realLog;
|
||||
rmSync(workspace, { recursive: true, force: true });
|
||||
rmSync(brainDir, { recursive: true, force: true });
|
||||
});
|
||||
|
||||
describe('import default worker count (#1207)', () => {
|
||||
test('no --workers flag → autoConcurrency picks 4 for >100 files on Postgres', async () => {
|
||||
await withEnv({ GBRAIN_HOME: join(workspace, '.gbrain'), GBRAIN_SOURCE: undefined }, async () => {
|
||||
await runImport(fakePostgresEngine, [brainDir, '--no-embed'], { sourceId: 'default' });
|
||||
});
|
||||
expect(logs.some(l => l.includes('Using 4 parallel workers'))).toBe(true);
|
||||
});
|
||||
|
||||
test('explicit --workers 2 still wins over the auto policy', async () => {
|
||||
await withEnv({ GBRAIN_HOME: join(workspace, '.gbrain'), GBRAIN_SOURCE: undefined }, async () => {
|
||||
await runImport(fakePostgresEngine, [brainDir, '--no-embed', '--workers', '2'], { sourceId: 'default' });
|
||||
});
|
||||
expect(logs.some(l => l.includes('Using 2 parallel workers'))).toBe(true);
|
||||
expect(logs.some(l => l.includes('Using 4 parallel workers'))).toBe(false);
|
||||
});
|
||||
});
|
||||
@@ -1,74 +0,0 @@
|
||||
// #2189 regression guard: putPage's INSERT … ON CONFLICT DO UPDATE … RETURNING
|
||||
// can yield 0 rows when brain-local DB state (e.g. a BEFORE INSERT trigger)
|
||||
// suppresses the write. Pre-fix, rowToPage(rows[0]) crashed with the opaque
|
||||
// "undefined is not an object (evaluating 'row.deleted_at')" that failed
|
||||
// ~all files of a code sync. Post-fix, putPage throws a descriptive error
|
||||
// naming the slug + source_id so the failure is diagnosable per-file.
|
||||
//
|
||||
// Same guard lands in postgres-engine.ts (engine-parity invariant); this test
|
||||
// exercises the PGLite side, where the issue was reported.
|
||||
|
||||
import { describe, expect, test, beforeAll, afterAll } from 'bun:test';
|
||||
import { PGLiteEngine } from '../src/core/pglite-engine.ts';
|
||||
|
||||
let engine: PGLiteEngine;
|
||||
|
||||
beforeAll(async () => {
|
||||
engine = new PGLiteEngine();
|
||||
await engine.connect({});
|
||||
await engine.initSchema();
|
||||
// Simulate the reporter's state-dependent failure: a trigger that
|
||||
// suppresses inserts for one slug, making RETURNING produce no row.
|
||||
await engine.executeRaw(`
|
||||
CREATE OR REPLACE FUNCTION suppress_pages_insert() RETURNS trigger AS $$
|
||||
BEGIN
|
||||
IF NEW.slug = 'suppressed-page' THEN RETURN NULL; END IF;
|
||||
RETURN NEW;
|
||||
END;
|
||||
$$ LANGUAGE plpgsql;
|
||||
`);
|
||||
await engine.executeRaw(`
|
||||
CREATE TRIGGER suppress_pages_insert_trg
|
||||
BEFORE INSERT ON pages
|
||||
FOR EACH ROW EXECUTE FUNCTION suppress_pages_insert();
|
||||
`);
|
||||
});
|
||||
|
||||
afterAll(async () => {
|
||||
await engine.executeRaw('DROP TRIGGER IF EXISTS suppress_pages_insert_trg ON pages');
|
||||
await engine.executeRaw('DROP FUNCTION IF EXISTS suppress_pages_insert');
|
||||
await engine.disconnect();
|
||||
});
|
||||
|
||||
describe('putPage RETURNING guard (#2189)', () => {
|
||||
test('0-row RETURNING throws a descriptive error, not row.deleted_at TypeError', async () => {
|
||||
let err: Error | undefined;
|
||||
try {
|
||||
await engine.putPage('suppressed-page', {
|
||||
type: 'code',
|
||||
title: 'Suppressed',
|
||||
compiled_truth: 'x',
|
||||
timeline: '',
|
||||
});
|
||||
} catch (e) {
|
||||
err = e as Error;
|
||||
}
|
||||
expect(err).toBeDefined();
|
||||
expect(err!.message).toContain('putPage');
|
||||
expect(err!.message).toContain("slug='suppressed-page'");
|
||||
expect(err!.message).toContain("source_id='default'");
|
||||
// The pre-fix crash signature must be gone.
|
||||
expect(err!.message).not.toContain('deleted_at');
|
||||
});
|
||||
|
||||
test('unsuppressed slugs still upsert normally with the trigger installed', async () => {
|
||||
const page = await engine.putPage('normal-page', {
|
||||
type: 'concept',
|
||||
title: 'Normal',
|
||||
compiled_truth: 'y',
|
||||
timeline: '',
|
||||
});
|
||||
expect(page.slug).toBe('normal-page');
|
||||
expect(page.source_id).toBe('default');
|
||||
});
|
||||
});
|
||||
@@ -375,31 +375,6 @@ describe('performSync dry-run never writes', () => {
|
||||
expect(messages.some(m => m.includes('git pull failed'))).toBe(false);
|
||||
});
|
||||
|
||||
test('first PGLite code sync imports code files without runtime failures', async () => {
|
||||
const { performSync } = await import('../src/commands/sync.ts');
|
||||
mkdirSync(join(repoPath, 'src'), { recursive: true });
|
||||
writeFileSync(
|
||||
join(repoPath, 'src/example.ts'),
|
||||
'export function add(left: number, right: number) { return left + right; }\n',
|
||||
);
|
||||
execSync('git add -A && git commit -m "add code file"', { cwd: repoPath, stdio: 'pipe' });
|
||||
|
||||
const result = await performSync(engine, {
|
||||
repoPath,
|
||||
noPull: true,
|
||||
noEmbed: true,
|
||||
noExtract: true,
|
||||
strategy: 'code',
|
||||
});
|
||||
|
||||
expect(result.status).toBe('first_sync');
|
||||
expect(result.added).toBe(1);
|
||||
expect(result.failedFiles ?? 0).toBe(0);
|
||||
const page = await engine.getPage('src-example-ts');
|
||||
expect(page?.type).toBe('code');
|
||||
expect(page?.frontmatter).toMatchObject({ file: 'src/example.ts', language: 'typescript' });
|
||||
});
|
||||
|
||||
test('incremental dry-run does NOT write to DB or advance the bookmark', async () => {
|
||||
const { performSync } = await import('../src/commands/sync.ts');
|
||||
// First do a real sync to seed the bookmark.
|
||||
|
||||
Reference in New Issue
Block a user