hy
9bd424cd1c
- Deleted the `missing-llm-notification-startup.e2e.test.ts` file as it is no longer needed. - Enhanced `send-guard-mode-switch-and-preferences.e2e.test.ts` to include checks for missing model notifications. - Removed `browser-use-deepseek-financing-search.e2e.test.ts` due to redundancy. - Cleaned up `chat-run-service-contract.test.ts` by removing performance tests that are no longer relevant. - Updated `aiLiveTestData.ts` to remove unused constants and types related to risk reports. - Removed `aiToolHarness.ts` function for writing sample documents as it is no longer utilized. - Updated `llmConfig.ts` to infer LLM provider kind from environment variables. - Cleaned up `cache-summary.ts` by removing unused JSON conversion functions. - Deleted `browserLlmConfig.ts` as it was redundant. - Enhanced `settings.ts` to support new application settings and improved HTTP server response handling. - Removed unused functions from `workbench.ts` related to waiting for assistant answers.
58 lines
2.0 KiB
TypeScript
58 lines
2.0 KiB
TypeScript
import { describe, expect, it } from 'vitest'
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import { createEmbeddingRuntimeDispatcher } from '../../../../src/main/services/vector/runtime/embeddingRuntimeProcess'
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import type {
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EmbeddingExecutor,
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EmbeddingRuntimeRequest,
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EmbeddingRuntimeResponse
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} from '../../../../src/main/services/vector/runtime/types'
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describe('embedding runtime contract', () => {
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it('serializes every inference request through one executor', async () => {
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let activeCalls = 0
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let maxActiveCalls = 0
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const callOrder: string[] = []
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const responses: EmbeddingRuntimeResponse[] = []
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let initialized = false
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const executor: EmbeddingExecutor = {
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initialize: async () => {
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initialized = true
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callOrder.push('initialize')
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},
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embed: async (texts) => {
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if (!initialized) throw new Error('not initialized')
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activeCalls += 1
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maxActiveCalls = Math.max(maxActiveCalls, activeCalls)
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callOrder.push(`start:${texts[0]}`)
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await new Promise<void>((resolve) => setTimeout(resolve, 20))
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callOrder.push(`end:${texts[0]}`)
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activeCalls -= 1
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return {
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data: Float32Array.from([texts[0].length]),
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dims: [1, 1]
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}
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}
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}
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const dispatcher = createEmbeddingRuntimeDispatcher({
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executor,
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postMessage: (response) => responses.push(response)
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})
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const requests: EmbeddingRuntimeRequest[] = [
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{ requestId: 'initialize', action: 'initialize', payload: null },
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{ requestId: 'first', action: 'embed', payload: { texts: ['alpha'] } },
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{ requestId: 'second', action: 'embed', payload: { texts: ['beta'] } }
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]
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requests.forEach((request) => dispatcher.dispatch(request))
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await dispatcher.whenIdle()
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expect(maxActiveCalls).toBe(1)
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expect(callOrder).toEqual(['initialize', 'start:alpha', 'end:alpha', 'start:beta', 'end:beta'])
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expect(responses.map((response) => response.requestId)).toEqual([
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'initialize',
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'first',
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'second'
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])
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expect(responses.every((response) => response.ok)).toBe(true)
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})
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})
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