Example Workflows

These are starter API-format workflows for the most common tasks. They're ready to run with scripts/run_workflow.py once you've installed (or have cloud access to) the listed models.

File	Purpose	Required models	Min VRAM
`sd15_txt2img.json`	SD 1.5 text-to-image (512×512)	SD1.5 checkpoint, e.g. `v1-5-pruned-emaonly.safetensors`	4 GB
`sdxl_txt2img.json`	SDXL text-to-image (1024×1024)	`sd_xl_base_1.0.safetensors`	8 GB
`flux_dev_txt2img.json`	Flux Dev text-to-image (1024×1024)	`flux1-dev.safetensors`, `t5xxl_fp16.safetensors`, `clip_l.safetensors`, `ae.safetensors`	24 GB (or use `flux1-dev-fp8`)
`sdxl_img2img.json`	SDXL image-to-image	SDXL checkpoint	8 GB
`sdxl_inpaint.json`	SDXL inpainting (image + mask)	SDXL checkpoint	8 GB
`upscale_4x.json`	Standalone 4× ESRGAN upscale	`4x-UltraSharp.pth` (or any upscaler)	4 GB
`animatediff_video.json`	AnimateDiff text-to-video (16 frames)	SD1.5 checkpoint, `mm_sd_v15_v2.ckpt` motion module	8 GB
`wan_video_t2v.json`	Wan 2.x text-to-video (~33 frames)	`wan2.2_t2v_1.3B_fp16.safetensors`, `umt5_xxl_fp16.safetensors`, `wan_2.1_vae.safetensors`	24 GB

Quick start

bash

# Run a workflow with prompt injection
python3 ../scripts/run_workflow.py \
  --workflow sdxl_txt2img.json \
  --args '{"prompt": "majestic eagle in flight", "seed": 12345, "steps": 35}' \
  --output-dir ./out

# Img2img: upload an input image first via the script's helper
python3 ../scripts/run_workflow.py \
  --workflow sdxl_img2img.json \
  --input-image image=./photo.png \
  --args '{"prompt": "make it watercolor", "denoise": 0.6}' \
  --output-dir ./out

# Cloud (set API key once)
export COMFY_CLOUD_API_KEY="comfyui-..."
python3 ../scripts/run_workflow.py \
  --workflow flux_dev_txt2img.json \
  --args '{"prompt": "a fox in a misty forest"}' \
  --host https://cloud.comfy.org \
  --output-dir ./out

# What can I tweak in this workflow?
python3 ../scripts/extract_schema.py sdxl_txt2img.json --summary-only

# Are all required models / nodes installed?
python3 ../scripts/check_deps.py wan_video_t2v.json

Notes

Inpaint masks: white pixels = "regenerate this region", black = preserve. ComfyUI's LoadImageMask reads the red channel by default; export your mask as a single-channel image or as a normal RGB where red==intensity.
Denoise strength in img2img: 0.0 = output identical to input, 1.0 = ignore input entirely. Sweet spot is usually 0.4–0.7.
Flux Dev needs ~24 GB VRAM in its base form. The flux1-dev-fp8.safetensors variant (already on Comfy Cloud) cuts that roughly in half.
Video workflows can take many minutes. The skill auto-detects video output nodes and bumps the default timeout to 900s. Override with --timeout 1800.
These JSON files are deliberately API format (top-level keys are node IDs with class_type), not editor format. To open them in ComfyUI's web UI for visual editing, use Workflow → Load (API Format) or Workflow → Open and follow the prompt.

Cloud vs local model names

Comfy Cloud's preinstalled checkpoints sometimes have a -fp16 suffix (v1-5-pruned-emaonly-fp16.safetensors) while the canonical local download keeps the original name (v1-5-pruned-emaonly.safetensors). The example workflows use the local-canonical names. When running on cloud, override with:

bash

python3 ../scripts/run_workflow.py \
  --workflow sd15_txt2img.json \
  --args '{"ckpt_name": "v1-5-pruned-emaonly-fp16.safetensors", "prompt": "..."}' \
  --host https://cloud.comfy.org

The ckpt_name, vae_name, lora_name, unet_name, etc. are all exposed as controllable parameters by extract_schema.py — discover what's installed with comfy model list (local) or curl /api/experiment/models/checkpoints (cloud).