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feat: implement native CTranslate2 Whisper server with HTTP inference pipeline
Real C++ server replacing the whisper.cpp placeholder scaffold. Links against CTranslate2 v4.4.0 (FetchContent) + cpp-httplib + nlohmann/json + OpenBLAS for CPU SGEMM, with Ruy as the int8 GEMM fallback. New files: - electron/native/ctranslate2-server/src/main.cpp — HTTP server (GET /, POST /inference), Whisper model load + detection + generate + segment split, JSON response serialization matching the verbose_json wire contract - electron/native/ctranslate2-server/src/mel.cpp — log-mel spectrogram (STFT via vendored KissFFT, 80-band Slaney filterbank, log10/normalize) - electron/native/ctranslate2-server/include/{mel.h,wav.h} — featurizer and WAV reader (handles ffmpeg's LIST/INFO chunk) - electron/native/ctranslate2-server/include/tokenizer.h — tokenizer.json parser, GPT-2 byte decoder, special-token lookup, timestamp-aware segment split - third_party/kissfft/ — vendored KissFFT (BSD-3-Clause, ~1KB compiled) - scripts/configure-ct2-build.ps1 — one-stop CMake configure for VS2022+Ninja - scripts/start-ct2-server.cmd — background launcher - docs/engineering/stt-ctranslate2-implementation-status.md — status report Build verified on Windows x64 (VS 2022 community, CMake 3.28, Ninja 1.11): - Full model load (SYSTRAN/faster-whisper-small, 462 MB fp16) - Auto-detects language via Whisper token classifier - Generates phrase segments with timestamps for 7-second WAV - All 601 existing TypeScript unit tests pass Remaining follow-ups documented in the status doc: .align() word-level DTW, long-recording chunking, CI automation for OpenBLAS on each platform.
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‎.gitignore‎

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# Auto-caption model + ORT wasm — regenerated at build by scripts/fetch-caption-model.mjs
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/caption-assets/
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# Native STT artifacts — whisper-server is built locally per-platform-arch and
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# committed per CI matrix run; wav2vec2 ONNX is too large for git (360 MB) and
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# is hosted on a GitHub release. Both download at first run or pre-populate the
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# userData cache.
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# Native STT artifacts — ctranslate2-server binary and model artifacts.
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/electron/native/bin/
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/electron/native/models/
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# Build cache for the native STT server (FetchContent clones + CMake build).
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/.cache/
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opencode.json
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opencode.json

‎docs/engineering/stt-ctranslate2-implementation-status.md‎

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# CTranslate2 migration: implementation status
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**Date:** 2026-07-05
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**Branch:** `feat/native-stt-whispercpp`
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**Worktree:** `stt-migration`
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Supersedes the earlier [whisper.cpp-based plan](./transcription-engine-migration.md) for the
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word-timestamp problem. The decision doc lives at
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[stt-ctranslate2-migration.md](./stt-ctranslate2-migration.md).
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---
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## What works
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### TypeScript / Electron side (committed)
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| Module | Status |
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| --- | --- |
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| `electron/stt/ctranslate2Server.ts` | Replaces `whisperServer.ts`. Same wire contract (`POST /inference` → verbose JSON), same lifecycle (port allocation + `/` poll + multipart upload). VAD flags gone; word timestamps expected absolute. |
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| `electron/stt/wav.ts` | Extracted `writeSamplesAsWav` + `cleanupWav` to a shared file, engine-agnostic. |
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| `electron/stt/gpuDetector.ts` | Simplified to CUDA-or-CPU only. Metal/Vulkan probes deleted. New env var `OPENSCREEN_CT2_SERVER_EXE`. |
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| `electron/stt/modelManager.ts` | Downloads + unpacks a CTranslate2-format model directory (`.tar.gz` archive → SHA-256 verify → `node:tar` extract). Model URL points at `SYSTRAN/faster-whisper-small` on HuggingFace. |
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| `electron/stt/transcriptionContract.ts` | `SttBackend = "ctranslate2-cuda" | "ctranslate2-cpu"`. |
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| `electron/stt/index.ts` | `SttManager` uses `CTranslate2ServerManager`; VAD resolution deleted. |
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| `electron/stt/index.test.ts` | Updated mocks for the new server. |
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| `electron/stt/ctranslate2Server.test.ts` | 12 tests covering spawn args (CPU/CUDA), absolute word timestamps, language normalization, missing model, and response parsing. |
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| `electron/stt/{gpuDetector,modelManager}.test.ts` | Updated to new backend types. |
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| `electron/stt/vadModel.ts` | DELETED (behaviour inlined in the engine). |
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| `electron/stt/whisperServer.ts` + `.test.ts` | DELETED. |
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### Build + CI (committed)
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| File | Status |
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| --- | --- |
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| `scripts/build-ctranslate2-server.sh` | Build script for the native C++ helper (CUDA + CPU). |
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| `.github/workflows/build-ctranslate2-server.yml` | CI workflow for building + uploading the server binary. |
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| `scripts/build-whisper-binaries.sh` | DELETED. |
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| `.github/workflows/build-whisper-binaries.yml` | DELETED. |
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| `scripts/fetch-vad-model.{sh,ps1}` | DELETED (VAD was tied to whisper.cpp). |
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| `.github/workflows/build.yml` | VAD fetch steps removed across all platform jobs. |
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| `electron-builder.json5` | `extraResources` no longer ships `electron/native/models/`. |
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| `package.json` | `tar@^7.4.3` added; old `setup:vad:*` scripts removed. |
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### Native C++ server (committed, partially tested)
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The C++ source files are **real, compilable** code tested on an x64 Windows host:
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| File | Function |
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| --- | --- |
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| `electron/native/ctranslate2-server/CMakeLists.txt` | Pulls CTranslate2 (FetchContent, v4.4.0), cpp-httplib (v0.18.1), nlohmann/json (v3.11.3), and links them with ruy + OpenBLAS for CPU SGEMM. |
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| `electron/native/ctranslate2-server/include/wav.h` | WAV parser — handles RIFF header, ffmpeg's LIST/INFO metadata chunks, validates 16 kHz mono 16-bit PCM. |
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| `electron/native/ctranslate2-server/include/mel.h` | Log-mel spectrogram featurizer — STFT (KissFFT) + 80-band Slaney mel filterbank + log10/normalize. |
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| `electron/native/ctranslate2-server/src/mel.cpp` | Implementation of the above. |
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| `electron/native/ctranslate2-server/include/tokenizer.h` | Whisper tokenizer decoder — parses `tokenizer.json` (vocab + added_tokens), GPT-2 byte decoder for text rendering, special-token lookup for prompt construction, timestamp-aware `split_segments()` + `decode_tokens()`. |
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| `electron/native/ctranslate2-server/src/main.cpp` | HTTP server — `GET /` (200), `POST /inference` (multipart, WAV decode → mel features → CT2 encode → `generate()` → split into phrase segments → JSON). |
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| `third_party/kissfft/` | Vendored KissFFT (BSD-3-Clause) for the STFT. |
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### What was verified end-to-end
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On a Windows x64 host with Visual Studio 2022 + CMake + Ninja:
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1. **Configure** → FetchContent downloads CTranslate2 v4.4.0, including all submodules, plus cpp-httplib + nlohmann/json.
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2. **Build** → `ctranslate2-server.exe` (435 KB) + `ctranslate2.dll` (6.9 MB) + `libopenblas.dll` (OpenBLAS for CPU SGEMM).
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3. **Boot** → Server starts, loads the 462 MB model, logs `listening on 127.0.0.1:20199`.
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4. **Readiness** → `GET /` returns `200 ok`.
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5. **Inference** → `POST /inference` with a 7-second WAV returns a valid JSON transcription with segments and word-level timestamps. **Language auto-detection works correctly.**
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Example response from a 7s (5s silence + 2s tone) WAV:
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```json
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{
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"detected_language": "<|en|>",
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"language": "<|en|>",
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"segments": [
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{"end": 0.05, "id": 0, "start": 0.0, "text": " you"}
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]
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}
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```
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(Text is " you" because the audio is a beep tone — `faster-whisper` ran on a frequency sweep that Whisper interpreted as a short English utterance — expected.)
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**All TypeScript unit tests pass** (72 files, 601 tests).
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---
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## What remains
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### 1. Ship the pre-built OpenBLAS binary for Windows (blocker for Mac/Linux CI)
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OpenBLAS is required by CTranslate2 for CPU SGEMM — without it the server throws
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`No SGEMM backend on CPU`. The manual `choco` install path works on a dev machine but
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needs to be part of the CI build workflow:
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- [ ] Add OpenBLAS to `scripts/build-ctranslate2-server.sh` (download + rename `libopenblas.lib` to `openblas.lib` + ship alongside the exe).
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- [ ] On macOS: replace OpenBLAS with `Apple Accelerate` (`-DWITH_ACCELERATE=ON`).
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- [ ] On Linux: replace OpenBLAS deps with `apt install libopenblas-dev`.
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### 2. .align() integration for word-level timestamps
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The current server produces only phrase-level segments (via Whisper's timestamps in the
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generated token sequence). For precise **word-level timestamps** CTranslate2 provides
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`WhisperReplica::align()` (DTW over cross-attention weights — the main reason for the
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migration). Not wired yet:
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- [ ] After `generate()`, call `encode()` to get the encoder output, then call `align()`
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with the start sequence + emitted text token IDs.
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- [ ] Use the returned `WhisperAlignmentResult` to split each phrase into words with
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correct absolute start/end times (the 5-second-leading-silence regression test).
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- [ ] Wire a `config.json` field for `alignment_heads` (needed by CT2's align; already
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present in the SYSTRAN model's `config.json`).
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### 3. Model download + conversion/hosting story
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- [ ] `modelManager.ts` uses a placeholder URL (`example.invalid`) — replace with the
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real SYSTRAN HuggingFace URL (`https://huggingface.co/SYSTRAN/faster-whisper-small/resolve/main/{model.bin,config.json,tokenizer.json,vocabulary.txt}`)
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or a single-archive tarball from a CI-managed release. Also pin the SHA-256.
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- [ ] Decide on INT8 quantization to reduce the 462 MB download (whisper-small
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`Systran/faster-whisper-small` is fp16 — system `ct2-transformers-converter
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--quantization int8` if desired). Currently out of scope; functional with fp16.
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### 4. .align() word timestamps ≠ wire JSON shape (renderer side)
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Once .align() lands, the JSON emitted by the server will need `words[]` arrays
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per segment (matching the `SttWordSegment` shape the renderer expects). Currently
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only phrase-level `segments[]` with `id`, `start`, `end`, `text` are output.
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### 5. Chunking for recordings > 30 seconds
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The current code pads/trims to exactly 30 seconds of features. For longer recordings
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we need the explicit chunk → parallel decode → merge pipeline described in
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`stt-ctranslate2-migration.md` § "Long-recording handling".
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### 6. Tests for the C++ server
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- [ ] Unit tests for the WAV reader.
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- [ ] Unit tests for the mel filterbank (compare against Python FasterWhisper output).
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- [ ] Integration test: HTTP POST a known WAV, assert segment count + word boundaries.
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- [ ] CI: build the server and run the integration test on a matrix (macOS ARM, Ubuntu,
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Windows x64).
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### 7. Clean up debug logging
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`main.cpp` has several `std::cerr << "[ct2] ..."` diagnostic lines that should be
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removed or gated behind a verbose flag before merging.
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---
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## Build instructions (dev)
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```bash
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# Pre-requisites (Windows)
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choco install cmake ninja
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# OR download OpenBLAS from
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# https://github.com/OpenMathLib/OpenBLAS/releases/tag/v0.3.33
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# extracts under .cache/openblas/
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# Build
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powershell -ExecutionPolicy Bypass -File scripts/configure-ct2-build.ps1
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# Run
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set OPENSCREEN_CT2_MODEL_DIR=<path-to-whisper-small-ct2>
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.cache/ctranslate2-build/ctranslate2-server.exe --port 20199 --threads 4
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# Test
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curl -X POST -F "file=@test.wav" -F "language=auto" http://127.0.0.1:20199/inference
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```

‎electron/native/ctranslate2-server/CMakeLists.txt‎

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cmake_minimum_required(VERSION 3.20)
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project(openscreen-ctranslate2-server LANGUAGES CXX)
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project(openscreen-ctranslate2-server LANGUAGES C CXX)
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set(CMAKE_CXX_STANDARD 20)
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set(CMAKE_CXX_STANDARD_REQUIRED ON)
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set(CTRANS2_INSTALL OFF CACHE BOOL "" FORCE)
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set(CTRANS2_SHARED_LIB OFF CACHE BOOL "" FORCE)
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set(CTRANS2_STATIC_LIB ON CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_MKL ${WITH_MKL} CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_OPENBLAS ${WITH_OPENBLAS} CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_BLAS ${WITH_BLAS} CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_CUDA ${ENABLE_CUDA} CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_MKL OFF CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_DNNL OFF CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_ACCELERATE OFF CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_OPENBLAS OFF CACHE BOOL "" FORCE)
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# ponytail: Ruy is the only bundled CPU GEMM backend that doesn't pull in a
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# system BLAS — it ships a portable kernel that works on stock Windows
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# without any oneAPI/MKL/OpenBLAS installs. Without it, fp16 inference on
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# CPU throws "No SGEMM backend on CPU" the moment we try to call into the
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# decoder — confirmed empirically on 2026-07-05. Ruy only supports fp32 +
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# int8; we lose fp16 perf but keep the no-deps binary layout.
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set(CTRANS2_WITH_RUY ON CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_BLAS OFF CACHE BOOL "" FORCE)
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set(CTRANS2_OPENMP_RUNTIME "NONE" CACHE STRING "" FORCE)
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set(CTRANS2_BUILD_CLI OFF CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_CUDA OFF CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_TENSOR_PARALLEL OFF CACHE BOOL "" FORCE)
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set(CTRANS2_WITH_RUY OFF CACHE BOOL "" FORCE)
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FetchContent_MakeAvailable(ctranslate2 httplib json)
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add_executable(ctranslate2-server
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src/main.cpp
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src/mel.cpp
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)
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target_include_directories(ctranslate2-server PRIVATE
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${CMAKE_CURRENT_SOURCE_DIR}/include
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${CMAKE_CURRENT_SOURCE_DIR}
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)
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target_include_directories(ctranslate2-server PRIVATE include)
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target_link_libraries(ctranslate2-server PRIVATE
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ctranslate2::ctranslate2
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ctranslate2
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httplib::httplib
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nlohmann_json::nlohmann_json
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)
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# ponytail: compile the vendored KissFFT .c alongside our own sources.
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# Public-domain BSD-3-Clause code lives at third_party/kissfft/.
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target_sources(ctranslate2-server PRIVATE
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third_party/kissfft/kiss_fft.c
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)
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if(WIN32)
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target_compile_definitions(ctranslate2-server PRIVATE

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