# aman
> Local amanuensis

Python X11 STT daemon that records audio, runs Whisper, applies local AI cleanup, and injects text.

## Requirements

- X11
- `sounddevice` (PortAudio)
- `faster-whisper`
- `llama-cpp-python`
- Tray icon deps: `gtk3`, `libayatana-appindicator3`
- Python deps (core): `numpy`, `pillow`, `faster-whisper`, `llama-cpp-python`, `sounddevice`
- X11 extras: `PyGObject`, `python-xlib`

System packages (example names): `portaudio`/`libportaudio2`.

<details>
<summary>Ubuntu/Debian</summary>

```bash
sudo apt install -y portaudio19-dev libportaudio2 python3-gi gir1.2-gtk-3.0 libayatana-appindicator3-1
```

</details>

<details>
<summary>Arch Linux</summary>

```bash
sudo pacman -S --needed portaudio gtk3 libayatana-appindicator
```

</details>

<details>
<summary>Fedora</summary>

```bash
sudo dnf install -y portaudio portaudio-devel gtk3 libayatana-appindicator-gtk3
```

</details>

<details>
<summary>openSUSE</summary>

```bash
sudo zypper install -y portaudio portaudio-devel gtk3 libayatana-appindicator3-1
```

</details>

## Python Daemon

Install Python deps:

X11 (supported):

```bash
uv sync --extra x11
```

## Config

Create `~/.config/aman/config.json` (or let `aman` create it automatically on first start if missing):

```json
{
  "daemon": { "hotkey": "Cmd+m" },
  "recording": { "input": "0" },
  "stt": { "model": "base", "device": "cpu" },
  "injection": {
    "backend": "clipboard",
    "remove_transcription_from_clipboard": false
  },
  "vocabulary": {
    "replacements": [
      { "from": "Martha", "to": "Marta" },
      { "from": "docker", "to": "Docker" }
    ],
    "terms": ["Systemd", "Kubernetes"]
  }
}
```

Recording input can be a device index (preferred) or a substring of the device
name.

Hotkey notes:

- Use one key plus optional modifiers (for example `Cmd+m`, `Super+m`, `Ctrl+space`).
- `Super` and `Cmd` are equivalent aliases for the same modifier.
- Invalid hotkey syntax in config prevents startup/reload.
- When `~/.config/aman/pipelines.py` exists, hotkeys come from `HOTKEY_PIPELINES`.
- `daemon.hotkey` is used as the fallback/default hotkey only when no pipelines file is present.

AI cleanup is always enabled and uses the locked local Llama-3.2-3B GGUF model
downloaded to `~/.cache/aman/models/` during daemon initialization.

Use `-v/--verbose` to enable DEBUG logs, including recognized/processed
transcript text and llama.cpp logs (`llama::` prefix). Without `-v`, logs are
INFO level.

Vocabulary correction:

- `vocabulary.replacements` is deterministic correction (`from -> to`).
- `vocabulary.terms` is a preferred spelling list used as hinting context.
- Wildcards are intentionally rejected (`*`, `?`, `[`, `]`, `{`, `}`) to avoid ambiguous rules.
- Rules are deduplicated case-insensitively; conflicting replacements are rejected.

STT hinting:

- Vocabulary is passed to Whisper as `hotwords`/`initial_prompt` only when those
  arguments are supported by the installed `faster-whisper` runtime.

## systemd user service

```bash
mkdir -p ~/.local/share/aman/src/assets
cp src/*.py ~/.local/share/aman/src/
cp src/assets/*.png ~/.local/share/aman/src/assets/
cp systemd/aman.service ~/.config/systemd/user/aman.service
systemctl --user daemon-reload
systemctl --user enable --now aman
```

## Usage

- Press the hotkey once to start recording.
- Press it again to stop and run STT.
- Press `Esc` while recording to cancel without processing.
- Transcript contents are logged only when `-v/--verbose` is used.
- Config changes are hot-reloaded automatically (polled every 1 second).
- `~/.config/aman/pipelines.py` changes are hot-reloaded automatically (polled every 1 second).
- Send `SIGHUP` to force an immediate reload of config and pipelines:
  `systemctl --user kill -s HUP aman` (or send `HUP` to the process directly).
- Reloads are applied when the daemon is idle; invalid updates are rejected and the last valid config stays active.
- Reload success/failure is logged, and desktop notifications are shown when available.

Wayland note:

- Running under Wayland currently exits with a message explaining that it is not supported yet.

Injection backends:

- `clipboard`: copy to clipboard and inject via Ctrl+Shift+V (GTK clipboard + XTest)
- `injection`: type the text with simulated keypresses (XTest)
- `injection.remove_transcription_from_clipboard`: when `true` and backend is `clipboard`, restores/clears the clipboard after paste so the transcript is not kept there

AI processing:

- Local llama.cpp model only (no remote provider configuration).

## Pipelines API

`aman` is split into:

- shell daemon: hotkeys, recording/cancel, and desktop injection
- pipeline engine: `lib.transcribe(...)` and `lib.llm(...)`
- pipeline implementation: Python callables mapped per hotkey

Pipeline file path:

- `~/.config/aman/pipelines.py`
- You can start from [`pipelines.example.py`](./pipelines.example.py).
- If `pipelines.py` is missing, `aman` uses a built-in reference pipeline bound to `daemon.hotkey`.
- If `pipelines.py` exists but is invalid, startup fails fast.
- Pipelines are hot-reloaded automatically when the module file changes.
- Send `SIGHUP` to force an immediate reload of both config and pipelines.

Expected module exports:

```python
HOTKEY_PIPELINES = {
  "Super+m": my_pipeline,
  "Super+Shift+m": caps_pipeline,
}

PIPELINE_OPTIONS = {
  "Super+Shift+m": {"failure_policy": "strict"},  # optional
}
```

Pipeline callable signature:

```python
def my_pipeline(audio, lib) -> str:
  text = lib.transcribe(audio)
  context = lib.llm(
    system_prompt="context system prompt",
    user_prompt=f"Transcript: {text}",
  )
  out = lib.llm(
    system_prompt="amanuensis prompt",
    user_prompt=f"context={context}\ntext={text}",
  )
  return out
```

`lib` API:

- `lib.transcribe(audio, hints=None, whisper_opts=None) -> str`
- `lib.llm(system_prompt=..., user_prompt=..., llm_opts=None) -> str`

Failure policy options:

- `best_effort` (default): pipeline errors return empty output
- `strict`: pipeline errors abort the current run

Validation:

- `HOTKEY_PIPELINES` must be a non-empty dictionary.
- Every hotkey key must be a non-empty string.
- Every pipeline value must be callable.
- `PIPELINE_OPTIONS` must be a dictionary when provided.

Reference behavior:

- The built-in fallback pipeline (used when `pipelines.py` is missing) uses `lib.llm(...)` twice:
  - first to infer context
  - second to run the amanuensis rewrite
- The second pass requests JSON output and expects `{"cleaned_text": "..."}`.
- Deterministic dictionary replacements are then applied as part of that reference implementation.

Control:

```bash
make run
make check
```