ComfyUI — Image & Video Generation

Use to generate images (Flux schnell) and videos (Wan2.1 T2V/I2V) on the local RTX 5080 GPU.

Environment

• ComfyUI: ~/ComfyUI (systemd user service: comfyui.service)
• Python venv: ~/comfyui-venv
• API: http://127.0.0.1:8188
• Output: ~/ComfyUI/output/

Script

{baseDir}/scripts/generate.py <mode> [options]

Mode: image — Text-to-Image (Flux schnell)

{baseDir}/scripts/generate.py image \
  --prompt "A cat on the moon" \
  --output /tmp/output.png

Recommended Flux schnell params: steps=4, cfg=1.0, sampler=euler, scheduler=simple

Mode: t2v — Text-to-Video (Wan2.1 T2V-1.3B)

{baseDir}/scripts/generate.py t2v \
  --prompt "A red sports car driving on a mountain road at sunset" \
  --length 49 \
  --output /tmp/video_frames/

Recommended Wan2.1 T2V params: steps=20, cfg=5.0, sampler=uni_pc_bh2, scheduler=simple

Mode: i2v — Image-to-Video (Wan2.1 I2V using T2V-1.3B)

{baseDir}/scripts/generate.py i2v \
  --prompt "gentle wave motion, water flowing" \
  --image /path/to/input.png \
  --output /tmp/video_frames/

Server Management

# Start (systemd user service)
systemctl --user start comfyui.service

# Check status
systemctl --user status comfyui.service

# Check API
curl -s http://127.0.0.1:8188/system_stats | python3 -m json.tool

# Manual start (if systemd not available)
cd ~/ComfyUI && LD_LIBRARY_PATH=~/comfyui-venv/lib/python3.12/site-packages/nvidia/cuda_runtime/lib:$LD_LIBRARY_PATH ~/comfyui-venv/bin/python main.py --listen 127.0.0.1 --port 8188

Installed Models

Image (Flux)

Video (Wan2.1)

Workflow

1. Check ComfyUI status (curl http://127.0.0.1:8188/system_stats).
2. Start if needed (systemctl --user start comfyui.service).
3. Call generate.py with appropriate mode and options.
4. Return output image/frames to user; offer xdg-open to view.
5. For video: frames are individual PNGs; optionally combine into MP4 with imageio.

Troubleshooting

• libcudart.so not found: set LD_LIBRARY_PATH with nvidia/cuda_runtime/lib.
• OOM on 16GB VRAM: reduce resolution or use lower --length for video.
• Video generation slow: T2V-1.3B 49 frames ≈ 2-3 minutes on RTX 5080.
• Server won't start: pkill -f "main.py" for stale processes.
• All models downloaded from ModelScope (domestic) — HuggingFace inaccessible.