feat: add managed Granite embedding models
GoodBuddy previously required an external OpenAI-compatible endpoint for vector retrieval. It can now install, verify, import, remove, and run the built-in Granite multilingual embedding model in an isolated local inference process, while retaining custom embedding connections and migrating existing settings. The model connection UI now manages built-in and custom vector connections consistently, reports the actual retrieval path, preserves credentials across failed saves, and renders the vector tab synchronously. Related settings copy, switch styling, metadata typography, and renderer bundle guardrails are aligned with the resulting workflow. Release note: 新增可管理的内置 Granite 多语言向量模型，支持本地下载、离线导入、连接切换与诊断；同时优化向量设置及相关界面的文案、开关和状态显示。
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mesalogo
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import { describe, expect, it, vi } from 'vitest'
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import {
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EMBEDDING_INFERENCE_PROTOCOL,
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EMBEDDING_INFERENCE_PROTOCOL_VERSION,
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type EmbeddingInferenceRequest
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} from './embedding-inference-contracts'
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import {
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EmbeddingInferenceBroker,
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type EmbeddingInferenceTransport
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} from './embedding-inference-broker'
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class TestTransport implements EmbeddingInferenceTransport {
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readonly sent: EmbeddingInferenceRequest[] = []
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readonly close = vi.fn()
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private readonly messageListeners = new Set<(message: unknown) => void>()
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private readonly closeListeners = new Set<() => void>()
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postMessage(message: EmbeddingInferenceRequest): void {
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this.sent.push(message)
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}
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onMessage(listener: (message: unknown) => void): () => void {
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this.messageListeners.add(listener)
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return () => this.messageListeners.delete(listener)
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}
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onClose(listener: () => void): () => void {
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this.closeListeners.add(listener)
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return () => this.closeListeners.delete(listener)
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}
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receive(message: unknown): void {
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for (const listener of this.messageListeners) {
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listener(message)
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}
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}
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crash(): void {
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for (const listener of this.closeListeners) {
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listener()
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}
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}
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}
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function response(message: Record<string, unknown>): Record<string, unknown> {
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return {
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protocol: EMBEDDING_INFERENCE_PROTOCOL,
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version: EMBEDDING_INFERENCE_PROTOCOL_VERSION,
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...message
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}
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}
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function embedRequest(transport: TestTransport): Extract<
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EmbeddingInferenceRequest,
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{ type: 'embed' }
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> {
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const request = transport.sent.find((item) => item.type === 'embed')
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if (!request || request.type !== 'embed') {
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throw new Error('No embed request was sent')
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}
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return request
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}
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describe('EmbeddingInferenceBroker', () => {
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it('uses UUID requests with roles and validates bounded results', async () => {
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const transport = new TestTransport()
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const broker = new EmbeddingInferenceBroker({
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createTransport: () => transport
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})
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const pending = broker.embed(['first', 'second'], 'query')
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await vi.waitFor(() => expect(transport.sent).toHaveLength(1))
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const request = embedRequest(transport)
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expect(request).toMatchObject({
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type: 'embed',
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role: 'query',
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texts: ['first', 'second']
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})
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expect(request.requestId).toMatch(
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/^[0-9a-f]{8}-[0-9a-f]{4}-[1-8][0-9a-f]{3}-[89ab][0-9a-f]{3}-[0-9a-f]{12}$/i
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)
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expect(request).not.toHaveProperty('modelDirectory')
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expect(request).not.toHaveProperty('env')
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transport.receive(
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response({
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type: 'result',
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requestId: request.requestId,
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vectors: [
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[1, 2],
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[3, 4]
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]
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})
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)
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await expect(pending).resolves.toEqual([
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[1, 2],
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[3, 4]
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])
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const shuttingDown = broker.shutdown()
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transport.receive(response({ type: 'shutdown-complete' }))
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await shuttingDown
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})
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it('rejects malformed input and untrusted vector responses', async () => {
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const transport = new TestTransport()
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const broker = new EmbeddingInferenceBroker({
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createTransport: () => transport
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})
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await expect(broker.embed([], 'document')).rejects.toThrow(
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'texts must contain'
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)
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const pending = broker.embed(['safe input'], 'document')
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await vi.waitFor(() => expect(transport.sent).toHaveLength(1))
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const request = embedRequest(transport)
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transport.receive(
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response({
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type: 'result',
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requestId: request.requestId,
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vectors: [[0, 0]]
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})
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)
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await expect(pending).rejects.toMatchObject({
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code: 'PROTOCOL_VIOLATION'
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})
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expect(transport.close).toHaveBeenCalledOnce()
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})
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it('propagates cancellation and timeout without accepting late results', async () => {
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vi.useFakeTimers()
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try {
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const transport = new TestTransport()
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const broker = new EmbeddingInferenceBroker({
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createTransport: () => transport,
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timeoutMs: 100
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})
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const controller = new AbortController()
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const cancelled = broker.embed(
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['cancel this'],
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'query',
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controller.signal
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)
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await vi.advanceTimersByTimeAsync(0)
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const cancelledRequest = embedRequest(transport)
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controller.abort()
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await expect(cancelled).rejects.toMatchObject({ name: 'AbortError' })
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expect(transport.sent.at(-1)).toMatchObject({
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type: 'cancel',
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requestId: cancelledRequest.requestId
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})
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transport.receive(
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response({
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type: 'error',
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requestId: cancelledRequest.requestId,
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code: 'CANCELLED',
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message: 'Embedding inference was cancelled'
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})
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)
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expect(transport.close).not.toHaveBeenCalled()
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const timedOut = broker.embed(['time this'], 'document')
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await vi.advanceTimersByTimeAsync(0)
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const timedRequest = transport.sent.find(
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(item) =>
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item.type === 'embed' &&
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item.requestId !== cancelledRequest.requestId
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)
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if (!timedRequest || timedRequest.type !== 'embed') {
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throw new Error('No second embed request was sent')
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}
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const timedOutExpectation = expect(timedOut).rejects.toMatchObject({
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name: 'TimeoutError'
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})
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await vi.advanceTimersByTimeAsync(100)
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await timedOutExpectation
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expect(transport.sent.at(-1)).toMatchObject({
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type: 'cancel',
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requestId: timedRequest.requestId
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})
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const shuttingDown = broker.shutdown()
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transport.receive(response({ type: 'shutdown-complete' }))
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await shuttingDown
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} finally {
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vi.useRealTimers()
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}
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})
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it('rejects on process close and enforces its lifetime restart bound', async () => {
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const transports = [
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new TestTransport(),
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new TestTransport(),
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new TestTransport()
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]
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const factory = vi.fn(() => {
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const transport = transports[factory.mock.calls.length - 1]
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if (!transport) {
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throw new Error('unexpected restart')
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}
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return transport
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})
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const broker = new EmbeddingInferenceBroker({
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createTransport: factory,
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maxRestarts: 1
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})
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const first = broker.embed(['first'], 'query')
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await vi.waitFor(() => expect(transports[0]?.sent).toHaveLength(1))
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transports[0]?.crash()
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await expect(first).rejects.toMatchObject({ code: 'PROCESS_CLOSED' })
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const second = broker.embed(['second'], 'document')
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await vi.waitFor(() => expect(transports[1]?.sent).toHaveLength(1))
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transports[1]?.crash()
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await expect(second).rejects.toMatchObject({ code: 'PROCESS_CLOSED' })
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await expect(broker.embed(['third'], 'query')).rejects.toMatchObject({
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code: 'RESTART_LIMIT'
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})
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expect(factory).toHaveBeenCalledTimes(2)
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})
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it('performs graceful shutdown and rejects future work', async () => {
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const transport = new TestTransport()
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const broker = new EmbeddingInferenceBroker({
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createTransport: () => transport
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})
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const pending = broker.embed(['active'], 'query')
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await vi.waitFor(() => expect(transport.sent).toHaveLength(1))
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const shuttingDown = broker.shutdown()
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await expect(pending).rejects.toMatchObject({ code: 'CLOSED' })
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expect(transport.sent.at(-1)).toMatchObject({ type: 'shutdown' })
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transport.receive(response({ type: 'shutdown-complete' }))
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await expect(shuttingDown).resolves.toBeUndefined()
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expect(transport.close).toHaveBeenCalledOnce()
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await expect(broker.embed(['late'], 'query')).rejects.toMatchObject({
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code: 'CLOSED'
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})
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})
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})
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