mirror of
https://github.com/openclaw/openclaw.git
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322 lines
11 KiB
TypeScript
322 lines
11 KiB
TypeScript
import fs from "node:fs/promises";
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import os from "node:os";
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import path from "node:path";
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import { afterAll, afterEach, beforeAll, beforeEach, describe, expect, it, vi } from "vitest";
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import { useFastShortTimeouts } from "../../test/helpers/fast-short-timeouts.js";
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import type { OpenClawConfig } from "../config/config.js";
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import { getMemorySearchManager, type MemoryIndexManager } from "./index.js";
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import { createOpenAIEmbeddingProviderMock } from "./test-embeddings-mock.js";
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import "./test-runtime-mocks.js";
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const embedBatch = vi.fn(async (_texts: string[]) => [] as number[][]);
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const embedQuery = vi.fn(async () => [0.5, 0.5, 0.5]);
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vi.mock("./embeddings.js", () => ({
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createEmbeddingProvider: async () =>
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createOpenAIEmbeddingProviderMock({
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embedQuery,
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embedBatch,
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}),
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}));
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describe("memory indexing with OpenAI batches", () => {
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let fixtureRoot: string;
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let workspaceDir: string;
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let memoryDir: string;
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let indexPath: string;
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let manager: MemoryIndexManager | null = null;
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async function readOpenAIBatchUploadRequests(body: FormData) {
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let uploadedRequests: Array<{ custom_id?: string }> = [];
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const entries = body.entries() as IterableIterator<[string, FormDataEntryValue]>;
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for (const [key, value] of entries) {
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if (key !== "file") {
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continue;
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}
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const text = typeof value === "string" ? value : await value.text();
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uploadedRequests = text
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.split("\n")
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.filter(Boolean)
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.map((line: string) => JSON.parse(line) as { custom_id?: string });
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}
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return uploadedRequests;
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}
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function createOpenAIBatchFetchMock(options?: {
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onCreateBatch?: (ctx: { batchCreates: number }) => Response | Promise<Response>;
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}) {
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let uploadedRequests: Array<{ custom_id?: string }> = [];
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const state = { batchCreates: 0 };
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const fetchMock = vi.fn(async (input: RequestInfo | URL, init?: RequestInit) => {
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const url =
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typeof input === "string" ? input : input instanceof URL ? input.toString() : input.url;
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if (url.endsWith("/files")) {
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const body = init?.body;
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if (!(body instanceof FormData)) {
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throw new Error("expected FormData upload");
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}
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uploadedRequests = await readOpenAIBatchUploadRequests(body);
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return new Response(JSON.stringify({ id: "file_1" }), {
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status: 200,
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headers: { "Content-Type": "application/json" },
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});
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}
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if (url.endsWith("/batches")) {
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state.batchCreates += 1;
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if (options?.onCreateBatch) {
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return await options.onCreateBatch({ batchCreates: state.batchCreates });
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}
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return new Response(JSON.stringify({ id: "batch_1", status: "in_progress" }), {
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status: 200,
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headers: { "Content-Type": "application/json" },
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});
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}
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if (url.endsWith("/batches/batch_1")) {
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return new Response(
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JSON.stringify({ id: "batch_1", status: "completed", output_file_id: "file_out" }),
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{ status: 200, headers: { "Content-Type": "application/json" } },
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);
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}
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if (url.endsWith("/files/file_out/content")) {
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const lines = uploadedRequests.map((request, index) =>
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JSON.stringify({
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custom_id: request.custom_id,
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response: {
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status_code: 200,
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body: { data: [{ embedding: [index + 1, 0, 0], index: 0 }] },
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},
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}),
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);
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return new Response(lines.join("\n"), {
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status: 200,
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headers: { "Content-Type": "application/jsonl" },
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});
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}
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throw new Error(`unexpected fetch ${url}`);
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});
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return { fetchMock, state };
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}
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function createBatchCfg(): OpenClawConfig {
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return {
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agents: {
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defaults: {
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workspace: workspaceDir,
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memorySearch: {
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provider: "openai",
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model: "text-embedding-3-small",
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store: { path: indexPath, vector: { enabled: false } },
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sync: { watch: false, onSessionStart: false, onSearch: false },
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query: { minScore: 0, hybrid: { enabled: false } },
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remote: { batch: { enabled: true, wait: true, pollIntervalMs: 1 } },
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},
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},
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list: [{ id: "main", default: true }],
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},
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} as OpenClawConfig;
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}
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beforeAll(async () => {
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fixtureRoot = await fs.mkdtemp(path.join(os.tmpdir(), "openclaw-mem-batch-"));
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workspaceDir = path.join(fixtureRoot, "workspace");
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memoryDir = path.join(workspaceDir, "memory");
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indexPath = path.join(fixtureRoot, "index.sqlite");
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await fs.mkdir(memoryDir, { recursive: true });
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const result = await getMemorySearchManager({ cfg: createBatchCfg(), agentId: "main" });
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expect(result.manager).not.toBeNull();
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if (!result.manager) {
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throw new Error("manager missing");
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}
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manager = result.manager as unknown as MemoryIndexManager;
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});
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afterAll(async () => {
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if (manager) {
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await manager.close();
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manager = null;
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}
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await fs.rm(fixtureRoot, { recursive: true, force: true });
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});
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beforeEach(async () => {
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embedBatch.mockClear();
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embedQuery.mockClear();
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embedBatch.mockImplementation(async (texts: string[]) =>
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texts.map((_text, index) => [index + 1, 0, 0]),
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);
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await fs.rm(memoryDir, { recursive: true, force: true });
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await fs.mkdir(memoryDir, { recursive: true });
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// Reuse one manager instance across tests; keep index state isolated.
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if (!manager) {
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throw new Error("manager missing");
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}
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(manager as unknown as { resetIndex: () => void }).resetIndex();
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(manager as unknown as { dirty: boolean }).dirty = true;
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(manager as unknown as { batchFailureCount: number }).batchFailureCount = 0;
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(manager as unknown as { batchFailureLastError?: string }).batchFailureLastError = undefined;
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(manager as unknown as { batchFailureLastProvider?: string }).batchFailureLastProvider =
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undefined;
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(manager as unknown as { batch: { enabled: boolean } }).batch.enabled = true;
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});
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afterEach(async () => {
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vi.unstubAllGlobals();
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});
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it("uses OpenAI batch uploads when enabled", async () => {
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const restoreTimeouts = useFastShortTimeouts();
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const content = ["hello", "from", "batch"].join("\n\n");
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await fs.writeFile(path.join(memoryDir, "2026-01-07.md"), content);
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const { fetchMock } = createOpenAIBatchFetchMock();
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vi.stubGlobal("fetch", fetchMock);
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try {
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if (!manager) {
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throw new Error("manager missing");
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}
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const labels: string[] = [];
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await manager.sync({
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progress: (update) => {
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if (update.label) {
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labels.push(update.label);
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}
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},
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});
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const status = manager.status();
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expect(status.chunks).toBeGreaterThan(0);
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expect(embedBatch).not.toHaveBeenCalled();
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expect(fetchMock).toHaveBeenCalled();
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expect(labels.some((label) => label.toLowerCase().includes("batch"))).toBe(true);
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} finally {
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restoreTimeouts();
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}
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});
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it("retries OpenAI batch create on transient failures", async () => {
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const restoreTimeouts = useFastShortTimeouts();
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const content = ["retry", "the", "batch"].join("\n\n");
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await fs.writeFile(path.join(memoryDir, "2026-01-08.md"), content);
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const { fetchMock, state } = createOpenAIBatchFetchMock({
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onCreateBatch: ({ batchCreates }) => {
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if (batchCreates === 1) {
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return new Response("upstream connect error", { status: 503 });
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}
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return new Response(JSON.stringify({ id: "batch_1", status: "in_progress" }), {
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status: 200,
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headers: { "Content-Type": "application/json" },
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});
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},
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});
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vi.stubGlobal("fetch", fetchMock);
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try {
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if (!manager) {
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throw new Error("manager missing");
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}
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await manager.sync({ reason: "test" });
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const status = manager.status();
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expect(status.chunks).toBeGreaterThan(0);
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expect(state.batchCreates).toBe(2);
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} finally {
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restoreTimeouts();
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}
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});
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it("tracks batch failures, resets on success, and disables after repeated failures", async () => {
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const restoreTimeouts = useFastShortTimeouts();
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const memoryFile = path.join(memoryDir, "2026-01-09.md");
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await fs.writeFile(memoryFile, ["flaky", "batch"].join("\n\n"));
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let mtimeMs = Date.now();
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const touch = async () => {
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mtimeMs += 1_000;
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const date = new Date(mtimeMs);
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await fs.utimes(memoryFile, date, date);
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};
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await touch();
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let mode: "fail" | "ok" = "fail";
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const { fetchMock } = createOpenAIBatchFetchMock({
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onCreateBatch: () =>
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mode === "fail"
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? new Response("batch failed", { status: 400 })
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: new Response(JSON.stringify({ id: "batch_1", status: "in_progress" }), {
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status: 200,
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headers: { "Content-Type": "application/json" },
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}),
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});
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vi.stubGlobal("fetch", fetchMock);
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try {
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if (!manager) {
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throw new Error("manager missing");
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}
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// First failure: fallback to regular embeddings and increment failure count.
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await manager.sync({ reason: "test" });
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expect(embedBatch).toHaveBeenCalled();
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let status = manager.status();
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expect(status.batch?.enabled).toBe(true);
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expect(status.batch?.failures).toBe(1);
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// Success should reset failure count.
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embedBatch.mockClear();
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mode = "ok";
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await fs.writeFile(memoryFile, ["flaky", "batch", "recovery"].join("\n\n"));
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await touch();
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(manager as unknown as { dirty: boolean }).dirty = true;
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await manager.sync({ reason: "test" });
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status = manager.status();
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expect(status.batch?.enabled).toBe(true);
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expect(status.batch?.failures).toBe(0);
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expect(embedBatch).not.toHaveBeenCalled();
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// Two more failures after reset should disable remote batching.
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await (
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manager as unknown as {
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recordBatchFailure: (params: {
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provider: string;
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message: string;
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attempts?: number;
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forceDisable?: boolean;
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}) => Promise<unknown>;
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}
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).recordBatchFailure({ provider: "openai", message: "batch failed", attempts: 1 });
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await (
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manager as unknown as {
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recordBatchFailure: (params: {
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provider: string;
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message: string;
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attempts?: number;
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forceDisable?: boolean;
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}) => Promise<unknown>;
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}
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).recordBatchFailure({ provider: "openai", message: "batch failed", attempts: 1 });
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status = manager.status();
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expect(status.batch?.enabled).toBe(false);
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expect(status.batch?.failures).toBeGreaterThanOrEqual(2);
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// Once disabled, batch endpoints are skipped and fallback embeddings run directly.
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const fetchCalls = fetchMock.mock.calls.length;
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embedBatch.mockClear();
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await fs.writeFile(memoryFile, ["flaky", "batch", "fallback"].join("\n\n"));
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await touch();
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(manager as unknown as { dirty: boolean }).dirty = true;
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await manager.sync({ reason: "test" });
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expect(fetchMock.mock.calls.length).toBe(fetchCalls);
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expect(embedBatch).toHaveBeenCalled();
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} finally {
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restoreTimeouts();
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}
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});
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});
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