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https://github.com/garrytan/gbrain.git
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Compare commits
2
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
55290e9088 | ||
|
|
04a2a1f7bf |
@@ -223,14 +223,16 @@ export GBRAIN_REMOTE_CLIENT_ID=<Alice's client_id>
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export GBRAIN_REMOTE_CLIENT_SECRET=<Alice's client_secret>
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export GBRAIN_REMOTE_MCP_URL=https://brain.acme-co.com/mcp
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gbrain search "performance review" --remote
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gbrain search "performance review"
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```
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(On a thin-client install every shared op routes through the remote MCP server automatically — no flag needed. The env vars select whose credentials the call uses.)
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Alice should see results only from `customers` and `shared`. The performance-review notes live in `internal`, which she's not scoped to read. She shouldn't see them.
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```bash
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# Terminal 2, as Bob (export his credentials similarly)
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gbrain search "performance review" --remote
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gbrain search "performance review"
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```
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Bob should see the performance-review notes from `internal`, plus anything related from `shared`. He shouldn't see anything that lives only in `customers`.
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@@ -514,7 +516,7 @@ The first sync embeds every page, which takes time. Check `gbrain sources status
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### "I see a page I shouldn't see"
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This shouldn't happen, but if you suspect it, run `gbrain search <query> --remote --json` as the constrained client and inspect the `source_id` field on every returned result. Every row should be in the client's `--federated-read` set. If one isn't, file an issue with the exact slug and source IDs.
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This shouldn't happen, but if you suspect it, run `gbrain search <query> --json` as the constrained client (thin-client install, with the client's `GBRAIN_REMOTE_*` env exported) and inspect the `source_id` field on every returned result. Every row should be in the client's `--federated-read` set. If one isn't, file an issue with the exact slug and source IDs.
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### "The synthesized answer is wrong"
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+84
-5
@@ -464,7 +464,11 @@ async function main() {
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// routed path. Date → ISO string; bigint → string (postgres.js shape);
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// Buffer → object. Microsecond-cost; eliminates a whole drift bug class.
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const result = JSON.parse(JSON.stringify(rawResult, bigintToStringReplacer));
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const output = formatResult(op.name, result);
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// #380 pass-through: `--json` (undeclared on most ops, promised by docs)
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// emits the raw op result instead of the human formatter.
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const output = params.json === true
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? JSON.stringify(result, null, 2) + '\n'
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: formatResult(op.name, result);
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if (output) process.stdout.write(output);
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} catch (e: unknown) {
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// v0.42.20.0 (codex D4): on error, set exitCode + return so the `finally`
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@@ -547,7 +551,10 @@ async function runThinClientRouted(
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signal: sigintController.signal,
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});
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const result = unpackToolResult(raw);
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const output = formatResult(op.name, result);
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// #380: same --json seam as the local-engine path (renderer parity).
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const output = params.json === true
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? JSON.stringify(result, null, 2) + '\n'
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: formatResult(op.name, result);
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if (output) process.stdout.write(output);
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} catch (e: unknown) {
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if (e instanceof RemoteMcpError) {
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@@ -757,10 +764,28 @@ export function resolveQueryImage(
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return { path: imagePath, base64, mime };
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}
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/**
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* #380: undeclared flags that are honored DOWNSTREAM of parseOpArgs and must
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* keep passing through when unknown flags become hard errors:
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* - source → makeContext's resolveSourceId (the --source axis)
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* - brain → the mount/brain routing axis (docs promise the flag)
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* - dry_run → makeContext's ctx.dryRun (ops without a declared dry_run)
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* - json → raw-JSON output seam (local + thin-client paths)
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*/
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const PASSTHROUGH_VALUE_FLAGS = new Set(['source', 'brain']);
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const PASSTHROUGH_BOOL_FLAGS = new Set(['dry_run', 'json']);
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export function parseOpArgs(op: Operation, args: string[]): Record<string, unknown> {
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const params: Record<string, unknown> = {};
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const positional = op.cliHints?.positional || [];
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let posIdx = 0;
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const cliName = op.cliHints?.name || op.name;
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const MAX_STDIN = 5_000_000; // 5MB cap, shared by stdin and --file
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// #380: `--file <path>` fills the op's declared stdin param (put's `content`)
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// from a file. Driven by cliHints.stdin — no per-op hard-coding — and
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// disabled when the op declares a real `file` param of its own.
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const fileParam = op.cliHints?.stdin && !op.params.file ? op.cliHints.stdin : undefined;
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let filePath: string | undefined;
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for (let i = 0; i < args.length; i++) {
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const arg = args[i];
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@@ -774,12 +799,42 @@ export function parseOpArgs(op: Operation, args: string[]): Record<string, unkno
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}
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}
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const key = arg.slice(2).replace(/-/g, '_');
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if (fileParam && key === 'file') {
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if (i + 1 >= args.length) {
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console.error(`Error: ${arg} requires a value.`);
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process.exit(1);
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}
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filePath = args[++i];
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continue;
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}
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const paramDef = op.params[key];
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if (paramDef?.type === 'boolean') {
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if (!paramDef) {
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if (PASSTHROUGH_BOOL_FLAGS.has(key)) {
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params[key] = true;
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continue;
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}
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if (PASSTHROUGH_VALUE_FLAGS.has(key)) {
|
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if (i + 1 >= args.length) {
|
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console.error(`Error: ${arg} requires a value.`);
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process.exit(1);
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}
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params[key] = args[++i];
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continue;
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}
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// #380: unknown flags were silently swallowed into params, so typos
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||||
// like `put --file` created empty pages instead of erroring.
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console.error(`Unknown option for gbrain ${cliName}: ${arg}`);
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console.error(`Run 'gbrain ${cliName} --help' for valid flags.`);
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process.exit(1);
|
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}
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if (paramDef.type === 'boolean') {
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params[key] = true;
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} else if (i + 1 < args.length) {
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params[key] = args[++i];
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if (paramDef?.type === 'number') params[key] = Number(params[key]);
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if (paramDef.type === 'number') params[key] = Number(params[key]);
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} else {
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console.error(`Error: ${arg} requires a value.`);
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process.exit(1);
|
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}
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} else if (posIdx < positional.length) {
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const key = positional[posIdx++];
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@@ -788,10 +843,30 @@ export function parseOpArgs(op: Operation, args: string[]): Record<string, unkno
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}
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}
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// #380: resolve --file AFTER the loop so --file/--content conflicts are
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// caught in either order.
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if (filePath !== undefined && fileParam) {
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if (params[fileParam] !== undefined) {
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console.error(`Error: use only one of --file, --${fileParam}, or stdin for gbrain ${cliName}.`);
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process.exit(1);
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}
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let fileContent: string;
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try {
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fileContent = readFileSync(filePath, 'utf-8');
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||||
} catch (e) {
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console.error(`Error: cannot read --file ${filePath}: ${e instanceof Error ? e.message : String(e)}`);
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process.exit(1);
|
||||
}
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if (Buffer.byteLength(fileContent, 'utf-8') > MAX_STDIN) {
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console.error(`Error: file content exceeds ${MAX_STDIN} bytes. Split into smaller inputs.`);
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process.exit(1);
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}
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params[fileParam] = fileContent;
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}
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// Read stdin for content params
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if (op.cliHints?.stdin && !params[op.cliHints.stdin] && !process.stdin.isTTY) {
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const stdinContent = readFileSync(0, 'utf-8');
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const MAX_STDIN = 5_000_000; // 5MB
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if (Buffer.byteLength(stdinContent, 'utf-8') > MAX_STDIN) {
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console.error(`Error: stdin content exceeds ${MAX_STDIN} bytes. Split into smaller inputs.`);
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process.exit(1);
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@@ -2253,6 +2328,10 @@ export function printOpHelp(op: Operation, invokedName?: string) {
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const prefix = isPos ? ` <${key}>` : ` --${key.replace(/_/g, '-')}`;
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console.log(`${prefix.padEnd(28)} ${def.description || ''}${req}`);
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||||
}
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||||
// #380: ops that read stdin also accept --file <path> (parseOpArgs).
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if (op.cliHints?.stdin && !op.params.file) {
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console.log(`${' --file <path>'.padEnd(28)} Read ${op.cliHints.stdin} from a file (alternative to --${op.cliHints.stdin} or stdin)`);
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}
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||||
}
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}
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||||
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+5
-10
@@ -170,14 +170,10 @@ 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, 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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const { parseWorkers } = await import('../core/sync-concurrency.ts');
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let workerCount: number;
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||||
try {
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workerCount = parseWorkers(workersArg ?? undefined);
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workerCount = parseWorkers(workersArg ?? undefined) ?? 1;
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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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@@ -256,9 +252,8 @@ export async function runImport(
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||||
}
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||||
const files = resumeFilter(allFiles, dir, completed);
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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);
|
||||
// Determine actual worker count
|
||||
const actualWorkers = workerCount > 1 ? workerCount : 1;
|
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if (actualWorkers > 1) {
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console.log(`Using ${actualWorkers} parallel workers`);
|
||||
}
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||||
|
||||
+6
-24
@@ -1513,21 +1513,12 @@ 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;
|
||||
|
||||
// Pre-split is gated on max_batch_tokens / max_batch_count. Recipes with
|
||||
// neither (e.g. OpenAI) ride the fast path: one embedMany call, no
|
||||
// recursion safety net.
|
||||
const batches = (maxBatchTokens || maxBatchCount)
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||||
? splitByTokenBudget(
|
||||
truncated,
|
||||
maxBatchTokens
|
||||
? Math.floor(maxBatchTokens * effectiveSafetyFactor(recipe))
|
||||
: Number.MAX_SAFE_INTEGER,
|
||||
charsPerToken,
|
||||
maxBatchCount,
|
||||
)
|
||||
// Pre-split is gated on max_batch_tokens. Recipes without it (e.g. OpenAI)
|
||||
// ride the fast path: one embedMany call, no recursion safety net.
|
||||
const batches = maxBatchTokens
|
||||
? splitByTokenBudget(truncated, Math.floor(maxBatchTokens * effectiveSafetyFactor(recipe)), charsPerToken)
|
||||
: [truncated];
|
||||
|
||||
const allEmbeddings: Float32Array[] = [];
|
||||
@@ -1577,9 +1568,6 @@ export async function embed(texts: string[], opts?: EmbedOpts): Promise<Float32A
|
||||
* responsible for applying any safety-factor shrink before passing in.
|
||||
* @param charsPerToken - Provider-specific character density. Defaults to
|
||||
* `DEFAULT_CHARS_PER_TOKEN` (4) when omitted, matching OpenAI tiktoken.
|
||||
* @param maxBatchCount - #1199: optional cap on INPUTS per sub-batch, for
|
||||
* providers that reject batches by count (DashScope: 10). When omitted,
|
||||
* only the token budget governs.
|
||||
*
|
||||
* @internal exported for tests; not part of the public gateway API.
|
||||
*/
|
||||
@@ -1587,17 +1575,15 @@ export function splitByTokenBudget(
|
||||
texts: string[],
|
||||
budgetTokens: number,
|
||||
charsPerToken: number = DEFAULT_CHARS_PER_TOKEN,
|
||||
maxBatchCount?: number,
|
||||
): string[][] {
|
||||
const ratio = charsPerToken > 0 ? charsPerToken : DEFAULT_CHARS_PER_TOKEN;
|
||||
const maxCount = maxBatchCount !== undefined && maxBatchCount > 0 ? maxBatchCount : Infinity;
|
||||
const batches: string[][] = [];
|
||||
let current: string[] = [];
|
||||
let currentTokens = 0;
|
||||
|
||||
for (const text of texts) {
|
||||
const estTokens = Math.ceil(text.length / ratio);
|
||||
if (current.length > 0 && (currentTokens + estTokens > budgetTokens || current.length >= maxCount)) {
|
||||
if (current.length > 0 && currentTokens + estTokens > budgetTokens) {
|
||||
batches.push(current);
|
||||
current = [];
|
||||
currentTokens = 0;
|
||||
@@ -1623,11 +1609,7 @@ export function isTokenLimitError(err: unknown): boolean {
|
||||
/token.*limit.*exceeded/i.test(msg) ||
|
||||
// OpenAI embeddings: "Invalid 'input': maximum request size is 300000 tokens per request."
|
||||
/maximum request size.*tokens/i.test(msg) ||
|
||||
/max.*tokens.*per.*request/i.test(msg) ||
|
||||
// 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.
|
||||
/batch size is invalid/i.test(msg)
|
||||
/max.*tokens.*per.*request/i.test(msg)
|
||||
);
|
||||
}
|
||||
|
||||
|
||||
@@ -31,10 +31,6 @@ export const dashscope: Recipe = {
|
||||
// path. Conservative declaration so the gateway pre-splits before
|
||||
// hitting whatever undocumented server-side limit exists.
|
||||
max_batch_tokens: 8192,
|
||||
// #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.
|
||||
max_batch_count: 10,
|
||||
// text-embedding-v3 mixes English + CJK heavily; the tokenizer is
|
||||
// closer to Voyage density than OpenAI tiktoken for CJK-dominant
|
||||
// content. Conservative chars_per_token=2 leaves headroom.
|
||||
|
||||
@@ -16,15 +16,6 @@ export const google: Recipe = {
|
||||
dims_options: [768, 1536, 3072],
|
||||
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,
|
||||
chars_per_token: 4,
|
||||
max_batch_count: 100,
|
||||
},
|
||||
expansion: {
|
||||
models: ['gemini-2.0-flash', 'gemini-2.0-flash-lite'],
|
||||
|
||||
@@ -58,8 +58,5 @@ export function getRecipe(id: string): Recipe | undefined {
|
||||
}
|
||||
|
||||
export function listRecipes(): Recipe[] {
|
||||
// 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()];
|
||||
return [...ALL];
|
||||
}
|
||||
|
||||
@@ -46,16 +46,6 @@ export interface EmbeddingTouchpoint {
|
||||
* 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
|
||||
|
||||
+6
-56
@@ -79,34 +79,15 @@ export interface EmbedBatchOptions {
|
||||
* and amplify rate-limit pressure.
|
||||
*/
|
||||
maxRetries?: number;
|
||||
/**
|
||||
* #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
|
||||
* owns progress-callback granularity and (#1818) bounded parallel dispatch
|
||||
* of the sub-batches — the embed-stale.ts worker-pool pattern, scoped down.
|
||||
* is purely about progress-callback granularity.
|
||||
*/
|
||||
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 = {},
|
||||
@@ -122,44 +103,13 @@ export async function embedBatch(
|
||||
if (texts.length <= BATCH_SIZE && !options.onBatchComplete) {
|
||||
return gatewayEmbed(texts, gwOpts);
|
||||
}
|
||||
// #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[] }> = [];
|
||||
const results: Float32Array[] = [];
|
||||
for (let i = 0; i < texts.length; i += BATCH_SIZE) {
|
||||
slices.push({ start: i, texts: texts.slice(i, 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);
|
||||
}
|
||||
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;
|
||||
}
|
||||
|
||||
|
||||
@@ -769,7 +769,7 @@ const get_page: Operation = {
|
||||
|
||||
const put_page: Operation = {
|
||||
name: 'put_page',
|
||||
description: 'Write/update a page (markdown with frontmatter). Chunks, embeds, reconciles tags, and (when auto_link/auto_timeline are enabled) extracts + reconciles graph links and timeline entries. For large content on Windows (pipe-buffer limit ~45KB) or any file-as-input workflow, use `gbrain capture --file PATH --slug SLUG` — capture reads the file as a Buffer with a binary-NUL guard and adds provenance write-through (v0.39.3.0).',
|
||||
description: 'Write/update a page (markdown with frontmatter). Chunks, embeds, reconciles tags, and (when auto_link/auto_timeline are enabled) extracts + reconciles graph links and timeline entries. On the CLI, `gbrain put SLUG --file PATH` reads content from a file (also `--content` or stdin). For provenance write-through and a binary-NUL guard, prefer `gbrain capture --file PATH --slug SLUG` (v0.39.3.0).',
|
||||
params: {
|
||||
slug: { type: 'string', required: true, description: 'Page slug' },
|
||||
content: { type: 'string', required: true, description: 'Full markdown content with YAML frontmatter' },
|
||||
@@ -1384,7 +1384,10 @@ const list_pages: Operation = {
|
||||
params: {
|
||||
type: { type: 'string', description: 'Filter by page type' },
|
||||
tag: { type: 'string', description: 'Filter by tag' },
|
||||
limit: { type: 'number', description: 'Max results (default 50)' },
|
||||
limit: { type: 'number', description: 'Max results (default 50, capped at 100 — use offset to paginate beyond)' },
|
||||
// #2876: the 100-row cap was silent and there was no way past it even
|
||||
// though both engines already support OFFSET on listPages.
|
||||
offset: { type: 'number', description: 'Skip first N results (pagination; pair with limit)' },
|
||||
// v0.29 — surface filter that already exists on PageFilters.
|
||||
updated_after: {
|
||||
type: 'string',
|
||||
@@ -1415,6 +1418,10 @@ const list_pages: Operation = {
|
||||
type: p.type as any,
|
||||
tag: p.tag as string,
|
||||
limit: clampSearchLimit(p.limit as number | undefined, 50, 100),
|
||||
// #2876: thread pagination through (engines already honor offset).
|
||||
offset: Number.isFinite(p.offset as number) && (p.offset as number) > 0
|
||||
? Math.floor(p.offset as number)
|
||||
: undefined,
|
||||
includeDeleted: (p.include_deleted as boolean) === true,
|
||||
updated_after: typeof p.updated_after === 'string' ? p.updated_after : undefined,
|
||||
sort,
|
||||
|
||||
@@ -39,8 +39,6 @@ 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,
|
||||
@@ -95,14 +93,6 @@ 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)', () => {
|
||||
@@ -159,27 +149,6 @@ 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)', () => {
|
||||
@@ -210,12 +179,6 @@ 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);
|
||||
@@ -424,92 +387,26 @@ 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).
|
||||
configureCapless();
|
||||
configureGoogle();
|
||||
expect(warnings.length).toBe(firstCallCount);
|
||||
} finally {
|
||||
console.warn = original;
|
||||
RECIPES.delete(caplessRecipe.id);
|
||||
}
|
||||
|
||||
// The warning text should match the documented contract.
|
||||
@@ -518,12 +415,11 @@ describe('startup warning for recipes missing max_batch_tokens', () => {
|
||||
);
|
||||
expect(contractMatch.length).toBe(1);
|
||||
|
||||
// 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.
|
||||
// Voyage declares max_batch_tokens → suppressed. OpenAI is the
|
||||
// canonical fast-path recipe → also suppressed by id. Both must be
|
||||
// absent from the warnings.
|
||||
expect(warnings.find(w => w.includes('"voyage"'))).toBeUndefined();
|
||||
expect(warnings.find(w => w.includes('"openai"'))).toBeUndefined();
|
||||
expect(warnings.find(w => w.includes('"google"'))).toBeUndefined();
|
||||
expect(warnings.find(w => w.includes('"capless-test"'))).toBeDefined();
|
||||
expect(warnings.find(w => w.includes('"google"'))).toBeDefined();
|
||||
});
|
||||
});
|
||||
|
||||
@@ -52,7 +52,16 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
|
||||
}
|
||||
});
|
||||
|
||||
test('configureGateway does NOT warn for google now that it declares batch caps (#970)', () => {
|
||||
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);
|
||||
|
||||
warnSpy.mockClear();
|
||||
resetGateway();
|
||||
configureGateway({
|
||||
@@ -60,20 +69,11 @@ describe('v0.32 #779: no_batch_cap suppresses the missing-max_batch_tokens warni
|
||||
embedding_dimensions: 768,
|
||||
env: { GOOGLE_GENERATIVE_AI_API_KEY: 'fake' },
|
||||
});
|
||||
const messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
|
||||
messages = warnSpy.mock.calls.map(c => String(c[0] ?? ''));
|
||||
expect(
|
||||
messages.some(m => m.includes('"google"') && m.includes('without max_batch_tokens')),
|
||||
'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);
|
||||
'google should warn when configured because it has fixed-cap models',
|
||||
).toBe(true);
|
||||
});
|
||||
|
||||
test('every recipe with empty models[] declares user_provided_models OR has openai-fast-path', () => {
|
||||
|
||||
@@ -55,11 +55,6 @@ 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
|
||||
|
||||
@@ -1,8 +1,41 @@
|
||||
import { describe, expect, test } from 'bun:test';
|
||||
import { mkdtempSync, rmSync, writeFileSync } from 'fs';
|
||||
import { tmpdir } from 'os';
|
||||
import { join } from 'path';
|
||||
import { parseOpArgs } from '../src/cli.ts';
|
||||
import { operationsByName } from '../src/core/operations.ts';
|
||||
|
||||
describe('parseOpArgs', () => {
|
||||
// #380: `gbrain put SLUG --file PATH` reads content from the file instead
|
||||
// of silently swallowing the flag and creating an empty page.
|
||||
test('put --file reads the stdin param (content) from a file', () => {
|
||||
const dir = mkdtempSync(join(tmpdir(), 'gbrain-put-file-'));
|
||||
try {
|
||||
const pagePath = join(dir, 'page.md');
|
||||
writeFileSync(pagePath, '# From file\n\nBody loaded from --file.\n');
|
||||
const params = parseOpArgs(operationsByName.put_page, ['concepts/from-file', '--file', pagePath]);
|
||||
expect(params.slug).toBe('concepts/from-file');
|
||||
expect(params.content).toBe('# From file\n\nBody loaded from --file.\n');
|
||||
} finally {
|
||||
rmSync(dir, { recursive: true, force: true });
|
||||
}
|
||||
});
|
||||
|
||||
// #380 regression guard: undeclared-but-honored flags must keep passing
|
||||
// through when unknown flags become hard errors (--source is read by
|
||||
// makeContext; --json by the output seam; --dry-run by ctx.dryRun).
|
||||
test('pass-through allowlist flags survive on ops that do not declare them', () => {
|
||||
const params = parseOpArgs(operationsByName.get_page, [
|
||||
'people/alice-example', '--source', 'wiki', '--json', '--dry-run',
|
||||
]);
|
||||
expect(params).toEqual({
|
||||
slug: 'people/alice-example',
|
||||
source: 'wiki',
|
||||
json: true,
|
||||
dry_run: true,
|
||||
});
|
||||
});
|
||||
|
||||
test('--no-<boolean> maps to false without consuming the next flag', () => {
|
||||
const params = parseOpArgs(operationsByName.query, [
|
||||
'freshEmbedSourceScope code source',
|
||||
|
||||
+71
-1
@@ -1,5 +1,5 @@
|
||||
import { describe, test, expect } from 'bun:test';
|
||||
import { existsSync, mkdtempSync, readFileSync, rmSync } from 'fs';
|
||||
import { existsSync, mkdtempSync, readFileSync, rmSync, writeFileSync } from 'fs';
|
||||
import { tmpdir } from 'os';
|
||||
import { join } from 'path';
|
||||
|
||||
@@ -120,6 +120,76 @@ describe('CLI dispatch integration', () => {
|
||||
expect(exitCode).toBe(0);
|
||||
});
|
||||
|
||||
// #380 / PR #856: put --help documents the --file input path.
|
||||
test('put --help documents --file input', async () => {
|
||||
const proc = Bun.spawn(['bun', 'run', 'src/cli.ts', 'put', '--help'], {
|
||||
cwd: repoRoot,
|
||||
stdout: 'pipe',
|
||||
stderr: 'pipe',
|
||||
});
|
||||
const stdout = await new Response(proc.stdout).text();
|
||||
const exitCode = await proc.exited;
|
||||
expect(stdout).toContain('Usage: gbrain put');
|
||||
expect(stdout).toContain('--file <path>');
|
||||
expect(exitCode).toBe(0);
|
||||
});
|
||||
|
||||
// #380: unknown flags on shared ops are a hard error (previously silently
|
||||
// swallowed into params — `put --file` created empty pages). parseOpArgs
|
||||
// runs BEFORE engine connect, so the error must fire without a brain.
|
||||
test('unknown shared-op flags fail before DB connection', async () => {
|
||||
const home = mkdtempSync(join(tmpdir(), 'gbrain-cli-unknown-flag-'));
|
||||
try {
|
||||
const proc = Bun.spawn(['bun', 'run', 'src/cli.ts', 'get', 'people/alice', '--bogus'], {
|
||||
cwd: repoRoot,
|
||||
stdout: 'pipe',
|
||||
stderr: 'pipe',
|
||||
env: isolatedEnv(home),
|
||||
});
|
||||
const stderr = await new Response(proc.stderr).text();
|
||||
const exitCode = await proc.exited;
|
||||
expect(stderr).toContain('Unknown option for gbrain get: --bogus');
|
||||
expect(stderr).not.toContain('No brain configured');
|
||||
expect(exitCode).toBe(1);
|
||||
} finally {
|
||||
rmSync(home, { recursive: true, force: true });
|
||||
}
|
||||
});
|
||||
|
||||
test('put rejects combining --file and --content', async () => {
|
||||
const home = mkdtempSync(join(tmpdir(), 'gbrain-cli-put-conflict-'));
|
||||
try {
|
||||
const pagePath = join(home, 'page.md');
|
||||
writeFileSync(pagePath, 'file body\n');
|
||||
const proc = Bun.spawn(
|
||||
['bun', 'run', 'src/cli.ts', 'put', 'a/b', '--content', 'inline', '--file', pagePath],
|
||||
{ cwd: repoRoot, stdout: 'pipe', stderr: 'pipe', env: isolatedEnv(home) },
|
||||
);
|
||||
const stderr = await new Response(proc.stderr).text();
|
||||
const exitCode = await proc.exited;
|
||||
expect(stderr).toContain('use only one of --file, --content, or stdin');
|
||||
expect(exitCode).toBe(1);
|
||||
} finally {
|
||||
rmSync(home, { recursive: true, force: true });
|
||||
}
|
||||
});
|
||||
|
||||
test('put --file with a missing path errors instead of writing an empty page', async () => {
|
||||
const home = mkdtempSync(join(tmpdir(), 'gbrain-cli-put-missing-file-'));
|
||||
try {
|
||||
const proc = Bun.spawn(
|
||||
['bun', 'run', 'src/cli.ts', 'put', 'a/b', '--file', join(home, 'nope.md')],
|
||||
{ cwd: repoRoot, stdout: 'pipe', stderr: 'pipe', env: isolatedEnv(home) },
|
||||
);
|
||||
const stderr = await new Response(proc.stderr).text();
|
||||
const exitCode = await proc.exited;
|
||||
expect(stderr).toContain('cannot read --file');
|
||||
expect(exitCode).toBe(1);
|
||||
} finally {
|
||||
rmSync(home, { recursive: true, force: true });
|
||||
}
|
||||
});
|
||||
|
||||
test('upgrade --help prints usage without running upgrade', async () => {
|
||||
const proc = Bun.spawn(['bun', 'run', 'src/cli.ts', 'upgrade', '--help'], {
|
||||
cwd: repoRoot,
|
||||
|
||||
@@ -1,161 +0,0 @@
|
||||
/**
|
||||
* #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 { afterEach, beforeEach } from 'bun:test';
|
||||
import { 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. ✓
|
||||
function applyLegacyIfEmpty() {
|
||||
beforeEach(() => {
|
||||
try {
|
||||
// Only re-apply if the gateway was reset (or never configured).
|
||||
// Tests that explicitly configured a different model in their
|
||||
@@ -62,28 +62,4 @@ function applyLegacyIfEmpty() {
|
||||
} 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);
|
||||
});
|
||||
|
||||
@@ -1,69 +0,0 @@
|
||||
/**
|
||||
* #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);
|
||||
});
|
||||
});
|
||||
@@ -0,0 +1,55 @@
|
||||
import { describe, test, expect } from 'bun:test';
|
||||
import { operationsByName } from '../src/core/operations.ts';
|
||||
|
||||
/**
|
||||
* #2876: `gbrain list --limit` silently clamped at 100 with no pagination.
|
||||
* list_pages now declares `offset` (both engines already supported it on
|
||||
* PageFilters) and the limit description discloses the 100-row cap.
|
||||
*/
|
||||
describe('list_pages pagination (#2876)', () => {
|
||||
const listPagesOp = operationsByName.list_pages;
|
||||
|
||||
function makeCtx(captured: unknown[]) {
|
||||
return {
|
||||
engine: {
|
||||
listPages: async (filters: unknown) => {
|
||||
captured.push(filters);
|
||||
return [];
|
||||
},
|
||||
},
|
||||
config: { engine: 'pglite' },
|
||||
logger: { info() {}, warn() {}, error() {} },
|
||||
dryRun: false,
|
||||
remote: false,
|
||||
sourceId: 'default',
|
||||
} as any;
|
||||
}
|
||||
|
||||
test('declares offset param and discloses the 100-row cap on limit', () => {
|
||||
expect(listPagesOp.params.offset).toBeDefined();
|
||||
expect(listPagesOp.params.offset.type).toBe('number');
|
||||
expect(listPagesOp.params.limit.description).toContain('100');
|
||||
});
|
||||
|
||||
test('threads offset through to engine.listPages', async () => {
|
||||
const captured: any[] = [];
|
||||
await listPagesOp.handler(makeCtx(captured), { limit: 10, offset: 30 });
|
||||
expect(captured[0].offset).toBe(30);
|
||||
expect(captured[0].limit).toBe(10);
|
||||
});
|
||||
|
||||
test('drops negative, non-finite, and zero offsets', async () => {
|
||||
const captured: any[] = [];
|
||||
const ctx = makeCtx(captured);
|
||||
await listPagesOp.handler(ctx, { offset: -5 });
|
||||
await listPagesOp.handler(ctx, { offset: Infinity });
|
||||
await listPagesOp.handler(ctx, { offset: 0 });
|
||||
for (const f of captured) expect(f.offset).toBeUndefined();
|
||||
});
|
||||
|
||||
test('floors fractional offsets', async () => {
|
||||
const captured: any[] = [];
|
||||
await listPagesOp.handler(makeCtx(captured), { offset: 7.9 });
|
||||
expect(captured[0].offset).toBe(7);
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user