claude-home/docker/examples/tdarr-node-local/docker-compose-gpu.yml
Cal Corum 10c9e0d854 CLAUDE: Migrate to technology-first documentation architecture
Complete restructure from patterns/examples/reference to technology-focused directories:

• Created technology-specific directories with comprehensive documentation:
  - /tdarr/ - Transcoding automation with gaming-aware scheduling
  - /docker/ - Container management with GPU acceleration patterns
  - /vm-management/ - Virtual machine automation and cloud-init
  - /networking/ - SSH infrastructure, reverse proxy, and security
  - /monitoring/ - System health checks and Discord notifications
  - /databases/ - Database patterns and troubleshooting
  - /development/ - Programming language patterns (bash, nodejs, python, vuejs)

• Enhanced CLAUDE.md with intelligent context loading:
  - Technology-first loading rules for automatic context provision
  - Troubleshooting keyword triggers for emergency scenarios
  - Documentation maintenance protocols with automated reminders
  - Context window management for optimal documentation updates

• Preserved valuable content from .claude/tmp/:
  - SSH security improvements and server inventory
  - Tdarr CIFS troubleshooting and Docker iptables solutions
  - Operational scripts with proper technology classification

• Benefits achieved:
  - Self-contained technology directories with complete context
  - Automatic loading of relevant documentation based on keywords
  - Emergency-ready troubleshooting with comprehensive guides
  - Scalable structure for future technology additions
  - Eliminated context bloat through targeted loading

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-08-12 23:20:15 -05:00

45 lines
1.2 KiB
YAML

version: "3.4"
services:
tdarr-node:
container_name: tdarr-node-local-gpu
image: ghcr.io/haveagitgat/tdarr_node:latest
restart: unless-stopped
environment:
- TZ=America/Chicago
- UMASK_SET=002
- nodeName=local-workstation-gpu
- serverIP=192.168.1.100 # Replace with your Tdarr server IP
- serverPort=8266
- inContainer=true
- ffmpegVersion=6
# NVIDIA environment variables
- NVIDIA_DRIVER_CAPABILITIES=all
- NVIDIA_VISIBLE_DEVICES=all
volumes:
# Media access (same as server)
- /mnt/media:/media # Replace with your media path
# Local transcoding cache
- ./temp:/temp
devices:
- /dev/dri:/dev/dri # Intel/AMD GPU fallback
# GPU configuration - choose ONE method:
# Method 1: Deploy syntax (recommended)
deploy:
resources:
limits:
memory: 16G # GPU transcoding uses less RAM
reservations:
memory: 8G
devices:
- driver: nvidia
count: all
capabilities: [gpu]
# Method 2: Runtime (alternative)
# runtime: nvidia
# Method 3: CDI (future)
# devices:
# - nvidia.com/gpu=all