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docs overhaul: agent-facing doc bundle, read-only docs mount in containers

- Strip ~55 stale upstream docs (dev docs never meant for the agents)
- Write new slim index.md as an agent-facing guide to the app's features
- Add new plugin docs: comfyui, elevenlabs, kokoro_tts, orpheus_tts_3b,
  remote_connectivity, whisper_local (replacing old names)
- Add docs_host to UserFs: docs/… and ~/docs/… resolve to {WD}/docs,
  mounted read-only at /root/docs in every user's container
- Instruct assistant/kid/project-coordinator agents to read docs/index.md
  when users ask how the software works

2026-07-22 10:20:21 +01:00

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Whisper Local

Plugin id: whisper_local
Category: Speech-to-text, local
Runs: on this machine, in-process (via whisper.cpp, Metal-accelerated on Apple Silicon) — no cloud, no API key

What it does

Transcribes voice messages entirely on-device using whisper.cpp. Nothing leaves the machine — the right choice when privacy matters more than raw speed, or when there's no budget for a cloud transcription API.

The model (roughly 1–3 GB depending on size) is loaded into memory only when first needed ("lazy" loading) and unloaded again after a configurable idle period to free RAM — unless eager loading is turned on.

Requirements

A GGML .bin Whisper model file, downloaded manually onto the host filesystem — this plugin does not fetch it automatically. Example:
```
curl -L -o models/ggml-large-v3.bin \
  https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3.bin
```
Smaller/faster models (e.g. ggml-medium.bin, ggml-small.bin) trade accuracy for speed and size — point at any of them.
ffmpeg installed on the host (used to convert incoming audio to the 16 kHz mono format Whisper needs).

Enabling & configuring (admin)

Download a model file first (see above) and note its path.
Plugin catalog → Whisper Local → enable, then Configure.
Fields:
- model (required) — path to the .bin file, e.g. models/ggml-large-v3.bin.
- language — a BCP-47 code (it, en, …) or auto for automatic detection (default auto).
- load_at_startup — load the model into memory as soon as the plugin starts, instead of on first use (default off).
- idle_timeout_secs — unload the model from memory after this many seconds of inactivity, 0 = never unload (default 1200, 20 minutes).

Notes

The model occupies roughly 1–3 GB of RAM while loaded.
The very first transcription after an idle unload is slower, since the model has to reload.
No external service and no per-use cost — the trade-off is local CPU/GPU time and disk space for the model file.

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