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openclaw-workspace/memory/2026-02-11.md
2026-04-11 09:45:12 -05:00

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# 2026-02-11
## Frigate NVR Setup
**Status:** ✅ Running with TensorRT
**Location:** `frigate/config.yml`
**Hardware:** RTX 3050 Laptop GPU
**Cameras Configured (8 total):**
- ✅ Kitchen - working
- ✅ Livingroom - working
- ✅ Front_DUO2 - working
- ✅ Back - working
- 🔄 Driveway - connecting
- 🔄 Garage - connecting
- 🔄 Back_Porch - connecting
- 🔄 Front - connecting
**Features:**
- TensorRT object detection (yolov7-320)
- MQTT publishing to HA at 192.168.0.39:1883
- Recording disabled (detection only)
- Zones and masks configured per camera
**Access:**
- Web UI: http://localhost:5000
- RTSP restream: rtsp://localhost:8554/{camera_name}
**First startup:** TensorRT model compilation took ~6 minutes (normal)
---
## Nextcloud + Talk Setup
**Status:** ✅ Main services running
**Location:** `nextcloud/docker-compose.yml`
**Services:**
- ✅ Nextcloud app (port 8080)
- ✅ MariaDB 10.6
- ✅ Redis (caching)
- ⚠️ Coturn (TURN server) - needs config fix
**Access:** http://localhost:8080
**Next Steps:**
1. Complete admin account setup via web UI
2. Install "Talk" app from App Store
3. Configure TURN server in Talk settings
4. Test video calls
---
## Project Ideas Discussed
**Daily Briefings Dashboard (XAMPP based)**
- RSS feed aggregation
- YouTube video transcription (Whisper)
- Frigate event integration via MQTT
- Weather display
- Nextcloud calendar integration
- Single web UI at http://localhost
**Storage Location:** XAMPP htdocs ready for development
---
## Files Created/Modified
- `frigate/config.yml` - TensorRT NVR config
- `frigate/docker-compose.yml` - Frigate container setup
- `frigate/README.md` - Documentation
- `nextcloud/docker-compose.yml` - NC + Talk stack
- `nextcloud/README.md` - Setup guide
---
## Technical Notes
**Frigate TensorRT:** First boot requires model compilation (5-10 min). Subsequent boots are instant.
**Nextcloud Talk:** Requires TURN server for calls behind NAT. Coturn included but may need manual start.
**Both services:** Docker Compose on WSL2 with GPU support enabled.