# Transui design

- Linux is a GTK3 desktop recorder. It supports hosted transcription with an optional local fallback and can type at the cursor or copy to the clipboard.
- macOS is a SwiftUI menu bar recorder targeting macOS 15. It supports the same hosted-first, local-fallback behavior as Linux, a global recording hotkey, launch at login, cursor typing, and clipboard output. When hosted-first is off, use local only. Its compact floating recorder uses teal level bars for recording feedback.
- Android is remote-only. It provides an Android `RecognitionService`, a voice-only input method, and a floating recognition activity. Do not add a local llama.cpp path to Android.
- All clients call OpenAI-compatible `/v1/audio/transcriptions` endpoints and clean only the Qwen3-ASR `language …<astext>` or `language …<asr_text>` prefix.
- Generate the macOS Xcode project from `macos/project.yml` with XcodeGen. Treat the spec as the source of truth and leave `macos/Transui.xcodeproj` untracked.
- The Android voice UI is an opaque, compact system surface. Teal is the recording signal. `PushToTalkButton` draws the Apps and Stop Circle glyphs with Canvas because the target device drops `ImageButton` image layers. Keep the glyphs drawn above the button background.

## llama.cpp local endpoint

The Linux and macOS local fallback uses this multipart request. `response_format=json`
is required; `prompt` is optional and may request transcription or translation.

```sh
curl -s -X POST -F response_format=json http://localhost:8080/v1/audio/transcriptions \
  -F file="@test.mp3" \
  -F 'prompt=Transcribe the following speech segment in English, and translate them into chinese.'
```

llama.cpp may return an event envelope instead of a bare OpenAI response:

```json
{"type":"transcript.text.done","text":"这是个测试。你能听到什么？我希望这很好。","usage":{"type":"tokens","input_tokens":241,"output_tokens":516,"total_tokens":757,"input_tokens_details":{"cached_tokens":0}}}
```

Use `text` as the transcript. Accept `transcript.text.done`; do not require a
bare `{ "text": "…" }` response.