NilsBriggen
9f42ee2460
Private, offline speech-to-text that runs Whisper on the user's own device — free, no account, no per-minute fees. Replaces Otter.ai / Rev. - Pure, tested engine: chunking, overlap timestamp-stitching, exports (SRT/VTT/TXT/MD/JSON), WAV codec, resampler, job queue, model catalog (142 tests). - Platform-abstracted TranscriptionEngine: transformers.js on web (loaded from CDN at runtime to dodge Metro's onnxruntime-web bundling limits), whisper.rn on native. Shared pipeline orchestrates decode -> chunk -> transcribe -> stitch. - Cross-platform StorageRepo (Dexie web / expo-sqlite native), Zod-validated. - UI: library + search, import, live-progress transcription, synced click-to-seek editor, multi-format export; model picker + privacy in settings. - Web ships as a single-page PWA with COOP/COEP isolation for threaded WASM; Docker (nginx) image + Traefik compose for wisp.briggen.dev. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
61 lines
2.4 KiB
TypeScript
61 lines
2.4 KiB
TypeScript
// The transcription engine interface: the single abstraction that hides the
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// platform-specific Whisper backend (transformers.js on web, whisper.rn on
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// native) behind one stable contract. The pure orchestration pipeline
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// (pipeline.ts) is written entirely against this interface so it can be unit
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// tested with a fake engine and never imports any heavy/native dependency.
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//
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// IMPORTANT contract detail: `transcribeChunk` returns CHUNK-LOCAL times
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// (0-based, relative to the start of the chunk it was handed). The pipeline is
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// responsible for offsetting those into absolute media time and stitching the
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// overlapping windows together (see pipeline.ts + stitch.ts).
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import type {
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Backend,
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ModelId,
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PcmAudio,
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Segment,
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TranscribeOptions,
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} from '../types';
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/**
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* What an engine discovered about the device it is running on. Used by the UI
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* to gate model choices and to decide whether live-mic capture is available.
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*/
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export interface EngineCapabilities {
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/** The compute backend the engine resolved to (e.g. 'webgpu', 'cpu'). */
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backend: Backend;
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/** Whether this engine can transcribe from a live microphone stream. */
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supportsLiveMic: boolean;
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/** Largest model we'd recommend running on this device/backend. */
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maxRecommendedModel: ModelId;
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}
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/**
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* A platform-agnostic Whisper engine. Both `engineImpl.web.ts` and
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* `engineImpl.native.ts` export a singleton `engine` satisfying this.
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*/
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export interface TranscriptionEngine {
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/** Which platform family this engine targets. */
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readonly platform: 'web' | 'native';
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/** Probe the device. May be async (e.g. WebGPU adapter request). */
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capabilities(): Promise<EngineCapabilities>;
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/**
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* Ensure `modelId` is loaded and ready. `onProgress` (if given) receives a
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* fraction in [0, 1] during download/initialization. Implementations should
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* be idempotent: calling again for an already-loaded model is a no-op.
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*/
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loadModel(modelId: ModelId, onProgress?: (p: number) => void): Promise<void>;
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/** Synchronous check: is this model already loaded in memory? */
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isModelLoaded(modelId: ModelId): boolean;
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/**
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* Transcribe a single already-decoded 16 kHz mono chunk.
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* Returns segments with CHUNK-LOCAL times (seconds, 0-based). The caller
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* offsets and stitches; engines must NOT add the chunk's media offset.
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*/
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transcribeChunk(audio: PcmAudio, opts: TranscribeOptions): Promise<Segment[]>;
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}
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