- OAuth authentication via Authentik - WebSocket connection to OpenClaw gateway - Configurable gateway URL with first-run setup - User preferences sync across devices - Multi-user support with custom assistant names - ElevenLabs TTS integration (local + remote) - FCM push notifications for alarms - Voice input via Google Speech API - No hardcoded secrets or internal IPs in tracked files
1.6 KiB
1.6 KiB
Vosk Model Setup Instructions
Step 1: Download the Model
Download the small English model from Vosk:
Direct Link: https://alphacephei.com/vosk/models/vosk-model-small-en-us-0.15.zip
Size: ~40 MB
Step 2: Extract the Model
- Extract
vosk-model-small-en-us-0.15.zip - You should have a folder named
vosk-model-small-en-us-0.15
Step 3: Add to Android Project
-
Create the assets folder if it doesn't exist:
mkdir -p ~/.openclaw/workspace/alfred-mobile/app/src/main/assets -
Move the extracted model folder:
mv ~/Downloads/vosk-model-small-en-us-0.15 ~/.openclaw/workspace/alfred-mobile/app/src/main/assets/ -
Verify the structure:
app/src/main/assets/ └── vosk-model-small-en-us-0.15/ ├── am/ ├── conf/ ├── graph/ ├── ivector/ └── README
Step 4: Rebuild the App
The model will be bundled with the APK. This increases the app size by ~40 MB but allows completely offline wake word detection.
Alternative: Smaller Model
If 40 MB is too large, you can use an even smaller model:
vosk-model-small-en-us-0.4 (~10 MB)
- Link: https://alphacephei.com/vosk/models/vosk-model-small-en-us-0.4.zip
- Less accurate but much smaller
- Update the folder name in
WakeWordManager.ktto match
Verification
Once the model is in place, the app will:
- Automatically unpack it to internal storage on first run
- Load it into memory
- Start listening for "alfred", "hey alfred", or "ok alfred"
Ready to download the model? Let me know when it's in place and we'll continue with the UI integration!