Comfyui

ComfyUI

Generate images, video, audio, and 3D content through ComfyUI using the official comfy-cli for setup/lifecycle and direct REST/WebSocket API for workflow execution.

What's in this skill

Reference docs (`references/`):

• official-cli.md — every comfy ... command, with flags
• rest-api.md — REST + WebSocket endpoints (local + cloud), payload schemas
• workflow-format.md — API-format JSON, common node types, param mapping
• template-integrity.md — converting comfyui-workflow-templates from editor format to API format: Reroute bypass, dotted dynamic-input keys (values.a, resize_type.width), Cloud quirks (302 redirect, 1 concurrent free-tier job, 1080p VRAM ceiling), Discord-compatible ffmpeg stitch. Authored by @purzbeats. Load this whenever you're starting from an official template.

Scripts (`scripts/`):

Example workflows (`workflows/`): SD 1.5, SDXL, Flux Dev, SDXL img2img, SDXL inpaint, ESRGAN upscale, AnimateDiff video, Wan T2V. See workflows/README.md.

When to Use

• User asks to generate images with Stable Diffusion, SDXL, Flux, SD3, etc.
• User wants to run a specific ComfyUI workflow file
• User wants to chain generative steps (txt2img → upscale → face restore)
• User needs ControlNet, inpainting, img2img, or other advanced pipelines
• User asks to manage ComfyUI queue, check models, or install custom nodes
• User wants video/audio/3D generation via AnimateDiff, Hunyuan, Wan, AudioCraft, etc.

Architecture: Two Layers

┌─────────────────────────────────────────────────────┐
│ Layer 1: comfy-cli (official lifecycle tool)        │
│   Setup, server lifecycle, custom nodes, models     │
│   → comfy install / launch / stop / node / model    │
└─────────────────────────┬───────────────────────────┘
                          │
┌─────────────────────────▼───────────────────────────┐
│ Layer 2: REST/WebSocket API + skill scripts         │
│   Workflow execution, param injection, monitoring   │
│   POST /api/prompt, GET /api/view, WS /ws           │
│   → run_workflow.py, run_batch.py, ws_monitor.py    │
└─────────────────────────────────────────────────────┘

Why two layers? The official CLI is excellent for installation and server management but has minimal workflow execution support. The REST/WS API fills that gap — the scripts handle param injection, execution monitoring, and output download that the CLI doesn't do.

Quick Start

Detect environment

# What's available?
command -v comfy >/dev/null 2>&1 && echo "comfy-cli: installed"
curl -s http://127.0.0.1:8188/system_stats 2>/dev/null && echo "server: running"

# Can this machine run ComfyUI locally? (GPU/VRAM/disk check)
python scripts/hardware_check.py

If nothing is installed, see Setup & Onboarding below — but always run the hardware check first.

One-line health check

python scripts/health_check.py
# → JSON: comfy_cli on PATH? server reachable? at least one checkpoint? smoke-test passes?

Core Workflow

Step 1: Get a workflow JSON in API format

Workflows must be in API format (each node has class_type). They come from:

• ComfyUI web UI → Workflow → Export (API) (newer UI) or the legacy "Save (API Format)" button (older UI)
• This skill's workflows/ directory (ready-to-run examples)
• Community downloads (civitai, Reddit, Discord) — usually editor format, must be loaded into ComfyUI then re-exported

Editor format (top-level nodes and links arrays) is not directly executable. The scripts detect this and tell you to re-export.

Step 2: See what's controllable

python scripts/extract_schema.py workflow_api.json --summary-only
# → {"parameter_count": 12, "has_negative_prompt": true, "has_seed": true, ...}

python scripts/extract_schema.py workflow_api.json
# → full schema with parameters, model deps, embedding refs

Step 3: Run with parameters

# Local (defaults to http://127.0.0.1:8188)
python scripts/run_workflow.py \
  --workflow workflow_api.json \
  --args '{"prompt": "a beautiful sunset over mountains", "seed": -1, "steps": 30}' \
  --output-dir ./outputs

# Cloud (export API key once; uses correct /api routing automatically)
export COMFY_CLOUD_API_KEY="comfyui-..."
python scripts/run_workflow.py \
  --workflow workflow_api.json \
  --args '{"prompt": "..."}' \
  --host https://cloud.comfy.org \
  --output-dir ./outputs

# Real-time progress via WebSocket (requires `pip install websocket-client`)
python scripts/run_workflow.py \
  --workflow flux_dev.json \
  --args '{"prompt": "..."}' \
  --ws

# img2img / inpaint: pass --input-image to upload + reference automatically
python scripts/run_workflow.py \
  --workflow sdxl_img2img.json \
  --input-image image=./photo.png \
  --args '{"prompt": "make it watercolor", "denoise": 0.6}'

# Batch / sweep: 8 random seeds, parallel up to cloud tier limit
python scripts/run_batch.py \
  --workflow sdxl.json \
  --args '{"prompt": "abstract"}' \
  --count 8 --randomize-seed --parallel 3 \
  --output-dir ./outputs/batch

-1 for seed (or omitting it with --randomize-seed) generates a fresh random seed per run.

Step 4: Present results

The scripts emit JSON to stdout describing every output file:

{
  "status": "success",
  "prompt_id": "abc-123",
  "outputs": [
    {"file": "./outputs/sdxl_00001_.png", "node_id": "9",
     "type": "image", "filename": "sdxl_00001_.png"}
  ]
}

Decision Tree