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The generic per-user #plugins page is gone: a plugin with per-user settings hosts them in its own web_pages() sidebar page instead (Telegram's pairing page is new; Honcho's opt-in page already existed). The admin catalog moves from #plugin-catalog to #plugins (old hash redirected), and user_config_schema is removed from the Plugin trait, the API DTOs and both plugins — the my-config endpoint, the plugin_user_configs store and the update_user_config hook stay, now driven by each plugin's own page fragment.
38 lines
2.1 KiB
Markdown
38 lines
2.1 KiB
Markdown
# Whisper Local
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- **Plugin id:** `whisper_local`
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- **Category:** Speech-to-text, local
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- **Runs:** on this machine, in-process (via `whisper.cpp`, Metal-accelerated on Apple Silicon) — no cloud, no API key
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## What it does
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Transcribes voice messages entirely on-device using [whisper.cpp](https://github.com/ggerganov/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.
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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.
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## Requirements
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- A GGML `.bin` Whisper model file, downloaded manually onto the host filesystem — this plugin does not fetch it automatically. Example:
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```
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curl -L -o models/ggml-large-v3.bin \
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https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-large-v3.bin
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```
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Smaller/faster models (e.g. `ggml-medium.bin`, `ggml-small.bin`) trade accuracy for speed and size — point at any of them.
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- `ffmpeg` installed on the host (used to convert incoming audio to the 16 kHz mono format Whisper needs).
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## Enabling & configuring (admin)
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1. Download a model file first (see above) and note its path.
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2. Plugins page → **Whisper Local** → enable, then **Configure**.
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3. Fields:
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- **`model`** (required) — path to the `.bin` file, e.g. `models/ggml-large-v3.bin`.
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- **`language`** — a BCP-47 code (`it`, `en`, …) or `auto` for automatic detection (default `auto`).
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- **`load_at_startup`** — load the model into memory as soon as the plugin starts, instead of on first use (default off).
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- **`idle_timeout_secs`** — unload the model from memory after this many seconds of inactivity, `0` = never unload (default `1200`, 20 minutes).
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## Notes
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- The model occupies roughly 1–3 GB of RAM while loaded.
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- The very first transcription after an idle unload is slower, since the model has to reload.
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- 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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