Rocky
df1c5ff32c
Replace MLX GPU inference with CoreML bundles so transcription continues while the host app is backgrounded. Adds model download and warm-up, vendored Qwen3Speech, and updates onboarding, settings, and copy for the ~1.6 GB CoreML package (iOS 18+).
43 lines
1.6 KiB
Swift
43 lines
1.6 KiB
Swift
// UtteranceStreamChunkerTests.swift
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// OSGKeyboardTests
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import XCTest
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@testable import OSGKeyboardShared
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final class UtteranceStreamChunkerTests: XCTestCase {
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private let config = FlowUtteranceChunkConfig(
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maxChunkDurationSeconds: 1,
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overlapDurationSeconds: 0.1,
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pauseExtensionMaxSeconds: 0.2,
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pauseRMSThreshold: 0.02,
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sampleRate: 1_000
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)
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func testPauseAwareSplitPrefersSilenceNearWindowEnd() {
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var buffer = [Float](repeating: 0.2, count: 900)
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buffer.append(contentsOf: [Float](repeating: 0.001, count: 50))
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buffer.append(contentsOf: [Float](repeating: 0.2, count: 100))
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let split = UtteranceStreamChunker.pauseAwareSplitIndex(in: buffer, config: config)
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XCTAssertGreaterThanOrEqual(split, config.maxChunkSamples)
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XCTAssertLessThanOrEqual(split, config.maxChunkSamples + config.pauseExtensionSamples)
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}
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func testChunksEmitMultipleSegmentsForLongStream() async {
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let sampleCount = config.maxChunkSamples * 2 + 100
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let samples = [Float](repeating: 0.05, count: sampleCount)
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let (stream, continuation) = AsyncStream<AudioBufferSnapshot>.makeStream()
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continuation.yield(AudioBufferSnapshot(samples: samples, sampleRate: Double(config.sampleRate)))
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continuation.finish()
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var received: [UtteranceAudioChunk] = []
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for await chunk in UtteranceStreamChunker.chunks(from: stream, config: config) {
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received.append(chunk)
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}
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XCTAssertGreaterThanOrEqual(received.count, 2)
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XCTAssertTrue(received.last?.isLast == true)
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}
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}
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