NAS-Only Setup (Docker)

For Synology, QNAP, Unraid, and TrueNAS users running Immich on the same NAS or local network. Docker-only, no LLM, no AI music, CPU encoding.

Who this is for

You have a NAS with Docker support (Synology DSM 7+, Unraid, TrueNAS SCALE, QNAP Container Station). You're already running Immich there. You want memory videos without setting up Python environments or GPU passthrough.

Architecture

┌─────────────────────────────────────────┐
│ NAS (Synology/Unraid/TrueNAS)          │
│                                         │
│  ┌─────────────┐  ┌──────────────────┐ │
│  │   Immich     │  │ Immich Memories  │ │
│  │  (port 2283) │←─│  (port 8080)    │ │
│  │             │  │  CPU encoding    │ │
│  │             │  │  PIL titles      │ │
│  └─────────────┘  └──────────────────┘ │
│                                         │
│  Volumes: config, output, video cache   │
└─────────────────────────────────────────┘

Docker Compose

services:
  immich-memories:
    image: ghcr.io/sam-dumont/immich-video-memory-generator:latest
    container_name: immich-memories
    ports:
      - "8080:8080"
    volumes:
      - immich-memories-config:/home/immich/.immich-memories
      - ./output:/app/output
    environment:
      IMMICH_URL: "${IMMICH_URL}"
      IMMICH_API_KEY: "${IMMICH_API_KEY}"
    restart: unless-stopped
    deploy:
      resources:
        limits:
          memory: 4G
          cpus: "4"

volumes:
  immich-memories-config:

.env file

IMMICH_URL=http://immich-server:2283
IMMICH_API_KEY=your-api-key-here

If Immich runs on the same Docker network, use the container name (immich-server). If it's on a different machine or behind a reverse proxy, use the full URL (https://photos.example.com).

What works

• Clip scoring: motion analysis, face detection (CPU-based), favorites boost, audio signals
• Title screens: PIL-based renderer (works everywhere, no GPU needed)
• Custom music: upload your own MP3/WAV in Step 3
• All memory types: year in review, monthly, person spotlight, trips (if GPS data exists)
• Scheduling: cron-based automated generation via the CLI
• Photo support: Ken Burns animations, face-aware pan, blur backgrounds

What doesn't work

• LLM content analysis: needs a separate LLM server (mlx-vlm, Ollama, vLLM). Without it, scoring uses motion + faces + audio only: still good, just not as context-aware.
• AI music generation: MusicGen and ACE-Step need GPU servers. Use custom music upload instead.
• GPU encoding: NAS CPUs (Celeron, Atom, low-end Xeon) don't have usable GPU encoders. Encoding is CPU-only via libx264.
• Taichi GPU title renderer: falls back to PIL. Title screens still look good, just without particle effects and animated globes.

Performance expectations

On a typical NAS CPU (Intel Celeron J4125, 4 cores, 2.0 GHz):

Clips	Resolution	Time
15	1080p	~8 min
30	1080p	~15 min
30	720p	~10 min
50	1080p	~25 min

Memory usage peaks at about 2-3 GB during encoding. The 4 GB limit in the compose file gives enough headroom. If you're encoding 4K (not recommended on NAS hardware), bump it to 8 GB.

The streaming assembler keeps memory constant regardless of clip count: it processes one clip at a time instead of loading everything into RAM.

Tips for NAS users

• Synology: use Container Manager (formerly Docker). Create the project from the compose file above.
• Unraid: add as a Docker container in the Unraid UI or use Docker Compose Manager plugin.
• TrueNAS SCALE: use the built-in Apps system or deploy via custom Docker compose.
• QNAP: use Container Station with the compose file.
• Keep the video cache enabled (default). It caches downloaded Immich clips locally, so repeat runs skip the download phase. Default cache limit: 10 GB, evicts files older than 7 days.