Files
whisper_web/src/worker/protocol.ts
T
Lucas WintherandClaude Fable 5 9f39a82982 WIP: M3 PWA/offline implementation, M4 auth (backend + frontend), D-013 faster-whisper
- M3: hand-rolled service worker (precache + runtime /ort caching), precache
  manifest injection, SW registration/update toast, manifest + generated icons,
  production build script, offline indicator in ModelPicker (D-005/D-007)
- M4 backend: bun:sqlite users/sessions (D-009), Passport local strategy behind
  connect-compat adapter (D-008), /api/auth routes wired into dev+prod serving,
  Bun.password Argon2id, 38 auth tests
- M4 frontend: AuthForms + useAuth + framework-free authClient, session-aware
  header, anonymous-first fail-silent offline handling, 18 client tests
- D-013: server engine (M5) will use faster-whisper via Python sidecar;
  browser side stays Transformers.js (CTranslate2 has no WASM build)
- bun test: 83 pass / tsc --noEmit clean
- Note: M3 doc closeout (WorkBreakdown/Architecture/tests/offline.md) still in
  flight from a background agent; follow-up commit will finish docs

Co-Authored-By: Claude Fable 5 <[email protected]>
2026-07-10 04:02:28 +02:00

263 lines
8.3 KiB
TypeScript

/**
* Typed postMessage protocol between the UI and the inference Web Worker
* (Decisions.md D-003). Shared by `src/worker/inference.worker.ts` and the UI.
*
* Everything in this file must stay free of browser/worker globals so it can
* be unit-tested with `bun test`.
*/
/** Devices the worker can actually run on (D-004). */
export type InferenceDevice = "webgpu" | "wasm";
/**
* What the UI may request. "auto" (the default) lets the worker probe
* `navigator.gpu` and pick WebGPU with automatic WASM fallback (D-004).
*/
export type DevicePreference = InferenceDevice | "auto";
/** Quantization levels used by the curated catalog (D-006). */
export type WhisperDtype = "fp32" | "fp16" | "q8" | "q4";
/**
* Either one dtype for the whole model, or per-part dtypes — the shape
* Transformers.js accepts. Whisper on WebGPU commonly needs a mixed setup
* (e.g. fp16 encoder + q4 merged decoder), so per-part must be expressible.
*/
export type DtypeSpec =
| WhisperDtype
| { encoder_model: WhisperDtype; decoder_model_merged: WhisperDtype };
/** Whisper generation task (multilingual models only). */
export type WhisperTask = "transcribe" | "translate";
// ---------------------------------------------------------------------------
// UI → worker
// ---------------------------------------------------------------------------
export interface LoadMessage {
type: "load";
/** Hugging Face Hub model id, e.g. "onnx-community/whisper-tiny.en". */
modelId: string;
/** Device preference; the worker resolves "auto" and reports the outcome. */
device: DevicePreference;
/**
* Optional dtype override. When omitted the worker resolves the catalog
* default for the device it actually selected (src/lib/models.ts).
*/
dtype?: DtypeSpec;
}
export interface TranscribeMessage {
type: "transcribe";
/**
* Mono PCM at 16 kHz (see src/lib/audio.ts). The underlying ArrayBuffer
* should be passed as a transferable for zero-copy handoff.
*/
audio: Float32Array;
/**
* ISO-ish Whisper language code (e.g. "en", "da"). Omit (or "auto") to let
* Whisper detect the language. Only meaningful for multilingual models.
*/
language?: string;
/** Only meaningful for multilingual models. Defaults to "transcribe". */
task?: WhisperTask;
}
export type UiToWorkerMessage = LoadMessage | TranscribeMessage;
// ---------------------------------------------------------------------------
// Worker → UI
// ---------------------------------------------------------------------------
/**
* Model download / initialization progress. Mirrors the Transformers.js
* `progress_callback` events we care about; `status: "ready"` marks the end
* of a successful load and reports the backend that actually got selected
* (after WebGPU detection / fallback, D-004).
*/
export type LoadProgressMessage =
| { type: "load-progress"; status: "initiate"; file: string }
| { type: "load-progress"; status: "download"; file: string }
| {
type: "load-progress";
status: "progress";
file: string;
/** Bytes downloaded so far. */
loaded: number;
/** Total bytes for this file. */
total: number;
/** Percentage in [0, 100]. */
progress: number;
}
| { type: "load-progress"; status: "done"; file: string }
| { type: "load-progress"; status: "ready"; device: InferenceDevice };
/** Incremental transcript fragment — append to the text streamed so far. */
export interface PartialMessage {
type: "partial";
text: string;
}
/** One timestamped segment of the final transcript. */
export interface TranscriptChunk {
text: string;
/** [start, end] in seconds; end may be null if Whisper never closed the segment. */
timestamp: [number, number | null];
}
export interface ResultMessage {
type: "result";
text: string;
chunks: TranscriptChunk[];
}
export interface ErrorMessage {
type: "error";
stage: "load" | "transcribe";
message: string;
}
export type WorkerToUiMessage =
| LoadProgressMessage
| PartialMessage
| ResultMessage
| ErrorMessage;
// ---------------------------------------------------------------------------
// Runtime guards (postMessage data arrives untyped)
// ---------------------------------------------------------------------------
function isRecord(value: unknown): value is Record<string, unknown> {
return typeof value === "object" && value !== null;
}
const DEVICES: readonly string[] = ["webgpu", "wasm"];
const DTYPES: readonly string[] = ["fp32", "fp16", "q8", "q4"];
export function isInferenceDevice(value: unknown): value is InferenceDevice {
return typeof value === "string" && DEVICES.includes(value);
}
export function isDevicePreference(value: unknown): value is DevicePreference {
return value === "auto" || isInferenceDevice(value);
}
export function isDtypeSpec(value: unknown): value is DtypeSpec {
if (typeof value === "string") return DTYPES.includes(value);
return (
isRecord(value) &&
typeof value.encoder_model === "string" &&
DTYPES.includes(value.encoder_model) &&
typeof value.decoder_model_merged === "string" &&
DTYPES.includes(value.decoder_model_merged)
);
}
export function isUiToWorkerMessage(value: unknown): value is UiToWorkerMessage {
if (!isRecord(value)) return false;
switch (value.type) {
case "load":
return (
typeof value.modelId === "string" &&
isDevicePreference(value.device) &&
(value.dtype === undefined || isDtypeSpec(value.dtype))
);
case "transcribe":
return (
value.audio instanceof Float32Array &&
(value.language === undefined || typeof value.language === "string") &&
(value.task === undefined ||
value.task === "transcribe" ||
value.task === "translate")
);
default:
return false;
}
}
export function isWorkerToUiMessage(value: unknown): value is WorkerToUiMessage {
if (!isRecord(value)) return false;
switch (value.type) {
case "load-progress":
switch (value.status) {
case "initiate":
case "download":
case "done":
return typeof value.file === "string";
case "progress":
return (
typeof value.file === "string" &&
typeof value.loaded === "number" &&
typeof value.total === "number" &&
typeof value.progress === "number"
);
case "ready":
return isInferenceDevice(value.device);
default:
return false;
}
case "partial":
return typeof value.text === "string";
case "result":
return typeof value.text === "string" && Array.isArray(value.chunks);
case "error":
return (
typeof value.message === "string" &&
(value.stage === "load" || value.stage === "transcribe")
);
default:
return false;
}
}
// ---------------------------------------------------------------------------
// Load-progress accumulation (pure; drives the download progress UI)
// ---------------------------------------------------------------------------
export interface FileProgress {
file: string;
loaded: number;
total: number;
done: boolean;
}
export interface LoadProgressState {
/** Per-file progress, keyed by file name, in first-seen order. */
files: Record<string, FileProgress>;
/** True once the pipeline reported ready. */
ready: boolean;
/** Backend the worker actually selected; null until ready (D-004). */
device: InferenceDevice | null;
}
export const initialLoadProgress: LoadProgressState = {
files: {},
ready: false,
device: null,
};
/** Fold one load-progress message into the accumulated state. Pure. */
export function applyLoadProgress(
state: LoadProgressState,
message: LoadProgressMessage,
): LoadProgressState {
if (message.status === "ready") {
return { ...state, ready: true, device: message.device };
}
const previous = state.files[message.file];
const next: FileProgress = {
file: message.file,
loaded: previous?.loaded ?? 0,
total: previous?.total ?? 0,
done: previous?.done ?? false,
};
if (message.status === "progress") {
next.loaded = message.loaded;
next.total = message.total;
} else if (message.status === "done") {
next.done = true;
if (next.total > 0) next.loaded = next.total;
}
return { ...state, files: { ...state.files, [message.file]: next } };
}