1f2e930d16
Instead of failing on package-lock.json merge conflicts, take the fork's version and continue. Applied to all channel skill merge instructions and CLAUDE.md troubleshooting. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
153 lines
4.7 KiB
Markdown
153 lines
4.7 KiB
Markdown
---
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name: use-local-whisper
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description: Use when the user wants local voice transcription instead of OpenAI Whisper API. Switches to whisper.cpp running on Apple Silicon. WhatsApp only for now. Requires voice-transcription skill to be applied first.
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---
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# Use Local Whisper
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Switches voice transcription from OpenAI's Whisper API to local whisper.cpp. Runs entirely on-device — no API key, no network, no cost.
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**Channel support:** Currently WhatsApp only. The transcription module (`src/transcription.ts`) uses Baileys types for audio download. Other channels (Telegram, Discord, etc.) would need their own audio-download logic before this skill can serve them.
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**Note:** The Homebrew package is `whisper-cpp`, but the CLI binary it installs is `whisper-cli`.
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## Prerequisites
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- `voice-transcription` skill must be applied first (WhatsApp channel)
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- macOS with Apple Silicon (M1+) recommended
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- `whisper-cpp` installed: `brew install whisper-cpp` (provides the `whisper-cli` binary)
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- `ffmpeg` installed: `brew install ffmpeg`
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- A GGML model file downloaded to `data/models/`
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## Phase 1: Pre-flight
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### Check if already applied
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Check if `src/transcription.ts` already uses `whisper-cli`:
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```bash
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grep 'whisper-cli' src/transcription.ts && echo "Already applied" || echo "Not applied"
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```
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If already applied, skip to Phase 3 (Verify).
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### Check dependencies are installed
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```bash
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whisper-cli --help >/dev/null 2>&1 && echo "WHISPER_OK" || echo "WHISPER_MISSING"
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ffmpeg -version >/dev/null 2>&1 && echo "FFMPEG_OK" || echo "FFMPEG_MISSING"
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```
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If missing, install via Homebrew:
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```bash
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brew install whisper-cpp ffmpeg
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```
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### Check for model file
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```bash
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ls data/models/ggml-*.bin 2>/dev/null || echo "NO_MODEL"
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```
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If no model exists, download the base model (148MB, good balance of speed and accuracy):
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```bash
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mkdir -p data/models
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curl -L -o data/models/ggml-base.bin "https://huggingface.co/ggerganov/whisper.cpp/resolve/main/ggml-base.bin"
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```
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For better accuracy at the cost of speed, use `ggml-small.bin` (466MB) or `ggml-medium.bin` (1.5GB).
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## Phase 2: Apply Code Changes
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### Ensure WhatsApp fork remote
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```bash
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git remote -v
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```
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If `whatsapp` is missing, add it:
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```bash
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git remote add whatsapp https://github.com/qwibitai/nanoclaw-whatsapp.git
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```
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### Merge the skill branch
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```bash
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git fetch whatsapp skill/local-whisper
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git merge whatsapp/skill/local-whisper || {
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git checkout --theirs package-lock.json
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git add package-lock.json
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git merge --continue
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}
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```
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This modifies `src/transcription.ts` to use the `whisper-cli` binary instead of the OpenAI API.
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### Validate
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```bash
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npm run build
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```
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## Phase 3: Verify
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### Ensure launchd PATH includes Homebrew
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The NanoClaw launchd service runs with a restricted PATH. `whisper-cli` and `ffmpeg` are in `/opt/homebrew/bin/` (Apple Silicon) or `/usr/local/bin/` (Intel), which may not be in the plist's PATH.
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Check the current PATH:
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```bash
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grep -A1 'PATH' ~/Library/LaunchAgents/com.nanoclaw.plist
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```
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If `/opt/homebrew/bin` is missing, add it to the `<string>` value inside the `PATH` key in the plist. Then reload:
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```bash
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launchctl unload ~/Library/LaunchAgents/com.nanoclaw.plist
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launchctl load ~/Library/LaunchAgents/com.nanoclaw.plist
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```
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### Build and restart
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```bash
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npm run build
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launchctl kickstart -k gui/$(id -u)/com.nanoclaw
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```
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### Test
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Send a voice note in any registered group. The agent should receive it as `[Voice: <transcript>]`.
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### Check logs
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```bash
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tail -f logs/nanoclaw.log | grep -i -E "voice|transcri|whisper"
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```
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Look for:
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- `Transcribed voice message` — successful transcription
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- `whisper.cpp transcription failed` — check model path, ffmpeg, or PATH
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## Configuration
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Environment variables (optional, set in `.env`):
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| Variable | Default | Description |
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|----------|---------|-------------|
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| `WHISPER_BIN` | `whisper-cli` | Path to whisper.cpp binary |
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| `WHISPER_MODEL` | `data/models/ggml-base.bin` | Path to GGML model file |
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## Troubleshooting
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**"whisper.cpp transcription failed"**: Ensure both `whisper-cli` and `ffmpeg` are in PATH. The launchd service uses a restricted PATH — see Phase 3 above. Test manually:
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```bash
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ffmpeg -f lavfi -i anullsrc=r=16000:cl=mono -t 1 -f wav /tmp/test.wav -y
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whisper-cli -m data/models/ggml-base.bin -f /tmp/test.wav --no-timestamps -nt
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```
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**Transcription works in dev but not as service**: The launchd plist PATH likely doesn't include `/opt/homebrew/bin`. See "Ensure launchd PATH includes Homebrew" in Phase 3.
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**Slow transcription**: The base model processes ~30s of audio in <1s on M1+. If slower, check CPU usage — another process may be competing.
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**Wrong language**: whisper.cpp auto-detects language. To force a language, you can set `WHISPER_LANG` and modify `src/transcription.ts` to pass `-l $WHISPER_LANG`.
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