Install
openclaw skills install comfyui-videoAutomate AI video generation with ComfyUI and LTX-2.3. Supports text-to-video (T2V), image-to-video (I2V), batch scene rendering for music videos, and multi-scene workflows. Includes progress monitoring, fault recovery, and performance tuning. Use when generating AI videos with ComfyUI, creating MV scenes in batch, troubleshooting video rendering, or optimizing generation speed.
openclaw skills install comfyui-videoAutomate AI video generation using ComfyUI + LTX-2.3 model. Ideal for music video (MV) production, multi-scene batch rendering, and AI video content creation.
| Item | Spec |
|---|---|
| GPU | ≥24GB VRAM (Turing/Ampere/Ada) |
| ComfyUI | 0.17+ |
| PyTorch | 2.6+cu124 |
| Access | SSH tunnel forwarding port 18188 |
| Model | Size | Path |
|---|---|---|
| LTX-2.3 dev (bf16) | 43GB | models/checkpoints/ltx-2.3-22b-dev.safetensors |
| Gemma 3 12B | 23GB | models/text_encoders/comfy_gemma_3_12B_it.safetensors |
| Distilled LoRA | 7.1GB | models/loras/ltxv/ltx2/ltx-2.3-22b-distilled-lora-384.safetensors |
| Video VAE (bf16) | - | models/vae/LTX23_video_vae_bf16.safetensors |
Turing GPUs (e.g., Quadro RTX 8000) do NOT support fp8_e4m3fn. Use bf16/fp16 models only.
Per-step time: ~221s (constant, regardless of frame count!)
15 steps: ~57 min
25 steps: ~1h45m
Frames: 72=3s, 121=5s, 480=20s (24fps)
Key insight: Frame count does NOT affect total time. Bottleneck is model forward pass.
| Node | ID | Purpose |
|---|---|---|
| LoadImage | 2004 | I2V reference input |
| CLIPTextEncode (positive) | 2483 | Positive prompt |
| CLIPTextEncode (negative) | 2612 | Negative prompt |
| EmptyLTXVLatentVideo | 3059 | Empty latent |
| LTXVScheduler | 4966 | Steps/length params |
| LoraLoaderModelOnly | 4922+ | LoRA loader |
| SaveVideo | 4823/4852 | Output mp4 |
/workspace/ComfyUI/custom_nodes/ComfyUI-LTXVideo/example_workflows/2.3/LTX-2.3_T2V_I2V_Single_Stage_Distilled_Full.jsonscripts/batch_scenes.js/workspace/ComfyUI/output/Use scripts/batch_scenes.js for automation:
// Load script first, then configure each scene:
await comfyui_batch.configureScene({
name: "scene_01",
prompt: "A lonely girl running through rain at night, neon reflections",
image: "unified_ref.png",
steps: 15,
frames: 72
});
// Click Run, repeat for next scene
| Steps | Quality | Time/Scene | Use Case |
|---|---|---|---|
| 8 | Rough | ~30min | Quick preview |
| 15 | Good | ~57min | Recommended sweet spot |
| 25 | Best | ~1h45m | Final quality output |
I2V + LoRA at 15 steps achieves ~90% of 25-step quality with 40% less time.
Error: Exception when validating node: 'VAEDecode'
Cause: VAE load timing or insufficient VRAM
Fix: Reload the entire workflow (fetch + loadGraphData), wait for models to fully load, then run. Never reload during execution.
Cause: SSH tunnel disconnected Fix:
ssh -f -N -L 18188:localhost:18188 user@host -p portCause: Different reference images per scene Fix: Use the SAME reference image for all scenes. Extract a clear frame from an existing video if needed. The I2V input image dictates the visual baseline.
Check: ssh -p PORT root@HOST "ls -lht /workspace/ComfyUI/output/*.mp4"
Fix: Check for VAEDecode errors in log, then re-run.
# Current sampling progress
ssh -p PORT root@HOST "grep 'it/s' /tmp/comfy.log | tail -1"
# Completion check
ssh -p PORT root@HOST "grep 'Prompt executed' /tmp/comfy.log | tail -1"
# Output files
ssh -p PORT root@HOST "ls -lht /workspace/ComfyUI/output/*.mp4"
| Mode | Steps | Quality | Notes |
|---|---|---|---|
| T2V (no LoRA) | 15 | ❌ Very blurry | Not recommended |
| I2V + LoRA | 25 | ✅ Excellent | Major quality improvement |
| I2V + LoRA | 15 | ✅ Very good | Best time/quality ratio |
Conclusion: I2V + LoRA is the recommended combination.
scripts/batch_scenes.js — Batch scene automationreferences/workflow_nodes.md — Full node ID mappingreferences/tips.md — Prompt tips, VRAM management, optimization