comfyui 精选
Generate images, video, and audio via diffusion workflows.
安装方式
cp -r optional-skills/creative/comfyui ~/.claude/skills/comfyui把该 skill 目录放进客户端 skills 目录。不同客户端的目录可能不同,Claude Code 默认是 ~/.claude/skills/
https://raw.githubusercontent.com/NousResearch/hermes-agent/0b89435e7e4f7fab88a34eb69f13bf339eb2fd00/optional-skills/creative/comfyui/SKILL.md下载后另存为 ~/.claude/skills/comfyui/SKILL.md。链接锁定采集时的 commit,内容与本站展示一致。
整仓一次性获取:git clone --depth 1 https://github.com/NousResearch/hermes-agent.git
依赖与权限
- 需要 API Key —— 使用前需配置相应的密钥环境变量
- 需要联网访问外部服务
- 依赖外部命令:
gitnodepythonpipuvxcurlffmpegmake - 以上为按正文与 frontmatter 自动推断的信号,仅供参考;安装前建议先阅读原文。
SKILL.md 正文
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— everycomfy ...command, with flagsrest-api.md— REST + WebSocket endpoints (local + cloud), payload schemasworkflow-format.md— API-format JSON, common node types, param mappingtemplate-integrity.md— convertingcomfyui-workflow-templatesfrom
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/):
| Script | Purpose |
|---|---|
_common.py | Shared HTTP, cloud routing, node catalogs (don't run directly) |
hardware_check.py | Probe GPU/VRAM/disk → recommend local vs Comfy Cloud |
comfyui_setup.sh | Hardware check + comfy-cli + ComfyUI install + launch + verify |
extract_schema.py | Read a workflow → list controllable params + model deps |
check_deps.py | Check workflow against running server → list missing nodes/models |
auto_fix_deps.py | Run check_deps then comfy node install / comfy model download |
run_workflow.py | Inject params, submit, monitor, download outputs (HTTP or WS) |
run_batch.py | Submit a workflow N times with sweeps, parallel up to your tier |
ws_monitor.py | Real-time WebSocket viewer for executing jobs (live progress) |
health_check.py | Verification checklist runner — comfy-cli + server + models + smoke test |
fetch_logs.py | Pull traceback / status messages for a given prompt_id |
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
| User says | Tool | Command |
|---|---|---|
| Lifecycle (use comfy-cli) | ||
| "install ComfyUI" | comfy-cli | bash scripts/comfyui_setup.sh |
| "start ComfyUI" | comfy-cli | comfy launch --background |
| "stop ComfyUI" | comfy-cli | comfy stop |
| "install X node" | comfy-cli | comfy node install <name> |
| "download X model" | comfy-cli | comfy model download --url <url> --relative-path models/checkpoints |
| "list installed models" | comfy-cli | comfy model list |
| "list installed nodes" | comfy-cli | comfy node show installed |
| Execution (use scripts) | ||
| "is everything ready?" | script | health_check.py (optionally with --workflow X --smoke-test) |
| "what can I change in this workflow?" | script | extract_schema.py W.json |
| "check if W's deps are met" | script | check_deps.py W.json |
| "fix missing deps" | script | auto_fix_deps.py W.json |
| "generate an image" | script | run_workflow.py --workflow W --args '{...}' |
| "use this image" (img2img) | script | run_workflow.py --input-image image=./x.png ... |
| "8 variations with random seeds" | script | run_batch.py --count 8 --randomize-seed ... |
| "show me live progress" | script | ws_monitor.py --prompt-id <id> |
| "fetch the error from job X" | script | fetch_logs.py <prompt_id> |
| Direct REST | ||
| "what's in the queue?" | REST | curl http://HOST:8188/queue (local) or --host https://cloud.comfy.org |
| "cancel that" | REST | curl -X POST http://HOST:8188/interrupt |
| "free GPU memory" | REST | curl -X POST http://HOST:8188/free |
Setup & Onboarding
When a user asks to set up ComfyUI, **the FIRST thing to do is ask whether
they want Comfy Cloud (hosted, zero install, API key) or Local (install
ComfyUI on their machine)**. Don't start running install commands or hardware
checks until they've answered.
Official docs: https://docs.comfy.org/installation
CLI docs: https://docs.comfy.org/comfy-cli/getting-started
Cloud docs: https://docs.comfy.org/get_started/cloud
Cloud API: https://docs.comfy.org/development/cloud/overview
Step 0: Ask Local vs Cloud (ALWAYS FIRST)
Suggested script:
"Do you want to run ComfyUI locally on your machine, or use Comfy Cloud?
- Comfy Cloud — hosted on RTX 6000 Pro GPUs, all common models pre-installed,
zero setup. Requires an API key (paid subscription required to actually run
workflows; free tier is read-only). Best if you don't have a capable GPU.
- Local — free, but your machine MUST meet the hardware requirements:
- NVIDIA GPU with ≥6 GB VRAM (≥8 GB for SDXL, ≥12 GB for Flux/video), OR
- AMD GPU with ROCm support (Linux), OR
- Apple Silicon Mac (M1+) with ≥16 GB unified memory (≥32 GB recommended).
- Intel Macs and machines with no GPU will NOT work — use Cloud instead.
Which would you like?"
Routing:
- Cloud → skip to Path A.
- Local → run hardware check first, then pick a path from Paths B–E based on the verdict.
- Unsure → run the hardware check and let the verdict decide.
Step 1: Verify Hardware (ONLY if user chose local)
python scripts/hardware_check.py --json
# Optional: also probe `torch` for actual CUDA/MPS:
python scripts/hardware_check.py --json --check-pytorch
| Verdict | Meaning | Action |
|---|---|---|
ok | ≥8 GB VRAM (discrete) OR ≥32 GB unified (Apple Silicon) | Local install — use comfy_cli_flag from report |
marginal | SD1.5 works; SDXL tight; Flux/video unlikely | Local OK for light workflows, else Path A (Cloud) |
cloud | No usable GPU, <6 GB VRAM, <16 GB Apple unified, Intel Mac, Rosetta Python | Switch to Cloud unless user explicitly forces local |
The script also surfaces wsl: true (WSL2 with NVIDIA passthrough) and
rosetta: true (x86_64 Python on Apple Silicon — must reinstall as ARM64).
If verdict is cloud but the user wants local, do not proceed silently.
Show the notes array verbatim and ask whether they want to (a) switch to
Cloud or (b) force a local install (will OOM or be unusably slow on modern models).
Choosing an Installation Path
Use the hardware check first. The table below is the fallback for when the
user has already told you their hardware:
| Situation | Recommended Path |
|---|---|
verdict: cloud from hardware check | Path A: Comfy Cloud |
| No GPU / want to try without commitment | Path A: Comfy Cloud |
| Windows + NVIDIA + non-technical | Path B: ComfyUI Desktop |
| Windows + NVIDIA + technical | Path C: Portable or Path D: comfy-cli |
| Linux + any GPU | Path D: comfy-cli (easiest) |
| macOS + Apple Silicon | Path B: Desktop or Path D: comfy-cli |
| Headless / server / CI / agents | Path D: comfy-cli |
For the fully automated path (hardware check → install → launch → verify):
bash scripts/comfyui_setup.sh
# Or with overrides:
bash scripts/comfyui_setup.sh --m-series --port=8190 --workspace=/data/comfy
It runs hardware_check.py internally, refuses to install locally when the
verdict is cloud (unless --force-cloud-override), picks the right
comfy-cli flag, and prefers pipx/uvx over global pip to avoid polluting
system Python.
Path A: Comfy Cloud (No Local Install)
For users without a capable GPU or who want zero setup. Hosted on RTX 6000 Pro.
Docs: https://docs.comfy.org/get_started/cloud
- Sign up at https://comfy.org/cloud
- Generate an API key at https://platform.comfy.org/login
- Set the key:
export COMFY_CLOUD_API_KEY="your-comfyui-key"
- Run workflows:
python scripts/run_workflow.py \
--workflow workflows/flux_dev_txt2img.json \
--args '{"prompt": "..."}' \
--host https://cloud.comfy.org \
--output-dir ./outputs
Pricing: https://www.comfy.org/cloud/pricing
Concurrent jobs: Free/Standard 1, Creator 3, Pro 5. Free tier
cannot run workflows via API — only browse models. Paid subscription
required for /api/prompt, /api/upload/*, /api/view, etc.
Path B: ComfyUI Desktop (Windows / macOS)
One-click installer for non-technical users. Currently Beta.
Docs: https://docs.comfy.org/installation/desktop
- Windows (NVIDIA): https://download.comfy.org/windows/nsis/x64
- macOS (Apple Silicon): https://comfy.org
Linux is not supported for Desktop — use Path D.
Path C: ComfyUI Portable (Windows Only)
Docs: https://docs.comfy.org/installation/comfyui_portable_windows
Download from https://github.com/comfyanonymous/ComfyUI/releases, extract,
run run_nvidia_gpu.bat. Update via update/update_comfyui_stable.bat.
Path D: comfy-cli (All Platforms — Recommended for Agents)
The official CLI is the best path for headless/automated setups.
Docs: https://docs.comfy.org/comfy-cli/getting-started
Install comfy-cli
# Recommended:
pipx install comfy-cli
# Or use uvx without installing:
uvx --from comfy-cli comfy --help
# Or (if pipx/uvx unavailable):
pip install --user comfy-cli
Disable analytics non-interactively:
comfy --skip-prompt tracking disable
Install ComfyUI
comfy --skip-prompt install --nvidia # NVIDIA (CUDA)
comfy --skip-prompt install --amd # AMD (ROCm, Linux)
comfy --skip-prompt install --m-series # Apple Silicon (MPS)
comfy --skip-prompt install --cpu # CPU only (slow)
comfy --skip-prompt install --nvidia --fast-deps # uv-based dep resolution
Default location: ~/comfy/ComfyUI (Linux), ~/Documents/comfy/ComfyUI
(macOS/Win). Override with comfy --workspace /custom/path install.
Launch / verify
comfy launch --background # background daemon on :8188
comfy launch -- --listen 0.0.0.0 --port 8190 # LAN-accessible custom port
curl -s http://127.0.0.1:8188/system_stats # health check
Path E: Manual Install (Advanced / Unsupported Hardware)
For Ascend NPU, Cambricon MLU, Intel Arc, or other unsupported hardware.
Docs: https://docs.comfy.org/installation/manual_install
git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI
pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu130
pip install -r requirements.txt
python main.py
Post-Install: Download Models
# SDXL (general purpose, ~6.5 GB)
comfy model download \
--url "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_base_1.0.safetensors" \
--relative-path models/checkpoints
# SD 1.5 (lighter, ~4 GB, good for 6 GB cards)
comfy model download \
--url "https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors" \
--relative-path models/checkpoints
# Flux Dev fp8 (smaller variant, ~12 GB)
comfy model download \
--url "https://huggingface.co/Comfy-Org/flux1-dev/resolve/main/flux1-dev-fp8.safetensors" \
--relative-path models/checkpoints
# CivitAI (set token first):
comfy model download \
--url "https://civitai.com/api/download/models/128713" \
--relative-path models/checkpoints \
--set-civitai-api-token "YOUR_TOKEN"
List installed: comfy model list.
Post-Install: Install Custom Nodes
comfy node install comfyui-impact-pack # popular utility pack
comfy node install comfyui-animatediff-evolved # video generation
comfy node install comfyui-controlnet-aux # ControlNet preprocessors
comfy node install comfyui-essentials # common helpers
comfy node update all
comfy node install-deps --workflow=workflow.json # install everything a workflow needs
Post-Install: Verify
python scripts/health_check.py
# → comfy_cli on PATH? server reachable? checkpoints? smoke test?
python scripts/check_deps.py my_workflow.json
# → are this workflow's nodes/models/embeddings installed?
python scripts/run_workflow.py \
--workflow workflows/sd15_txt2img.json \
--args '{"prompt": "test", "steps": 4}' \
--output-dir ./test-outputs
Image Upload (img2img / Inpainting)
The simplest way is to use --input-image with run_workflow.py:
python scripts/run_workflow.py \
--workflow workflows/sdxl_img2img.json \
--input-image image=./photo.png \
--args '{"prompt": "make it cyberpunk", "denoise": 0.6}'
The flag uploads photo.png, then injects its server-side filename into
whatever schema parameter is named image. For inpainting, pass both:
python scripts/run_workflow.py \
--workflow workflows/sdxl_inpaint.json \
--input-image image=./photo.png \
--input-image mask_image=./mask.png \
--args '{"prompt": "fill with flowers"}'
Manual upload via REST:
curl -X POST "http://127.0.0.1:8188/upload/image" \
-F "[email protected]" -F "type=input" -F "overwrite=true"
# Returns: {"name": "photo.png", "subfolder": "", "type": "input"}
# Cloud equivalent:
curl -X POST "https://cloud.comfy.org/api/upload/image" \
-H "X-API-Key: $COMFY_CLOUD_API_KEY" \
-F "[email protected]" -F "type=input" -F "overwrite=true"
Cloud Specifics
- Base URL:
https://cloud.comfy.org - Auth:
X-API-Keyheader (or?token=KEYfor WebSocket) - API key: set
$COMFY_CLOUD_API_KEYonce and the scripts pick it up automatically - Output download:
/api/viewreturns a 302 to a signed URL; the scripts
follow it and strip X-API-Key before fetching from the storage backend
(don't leak the API key to S3/CloudFront).
- Endpoint differences from local ComfyUI:
/api/object_info,/api/queue,/api/userdata— 403 on free tier;
paid only.
/historyis renamed to/history_v2on cloud (the scripts route
automatically).
/models/<folder>is renamed to/experiment/models/<folder>on cloud
(the scripts route automatically).
clientIdin WebSocket is currently ignored — all connections for a
user receive the same broadcast. Filter by prompt_id client-side.
subfolderis accepted on uploads but ignored — cloud has a flat namespace.- Concurrent jobs: Free/Standard: 1, Creator: 3, Pro: 5. Extras queue
automatically. Use run_batch.py --parallel N to saturate your tier.
Queue & System Management
# Local
curl -s http://127.0.0.1:8188/queue | python -m json.tool
curl -X POST http://127.0.0.1:8188/queue -d '{"clear": true}' # cancel pending
curl -X POST http://127.0.0.1:8188/interrupt # cancel running
curl -X POST http://127.0.0.1:8188/free \
-H "Content-Type: application/json" \
-d '{"unload_models": true, "free_memory": true}'
# Cloud — same paths under /api/, plus:
python scripts/fetch_logs.py --tail-queue --host https://cloud.comfy.org
Pitfalls
- API format required — every script and the
/api/promptendpoint expect
API-format workflow JSON. The scripts detect editor format (top-level
nodes and links arrays) and tell you to re-export via
"Workflow → Export (API)" (newer UI) or "Save (API Format)" (older UI).
- Server must be running — all execution requires a live server.
comfy launch --background starts one. Verify with
curl http://127.0.0.1:8188/system_stats.
- Model names are exact — case-sensitive, includes file extension.
check_deps.py does fuzzy matching (with/without extension and folder
prefix), but the workflow itself must use the canonical name. Use
comfy model list to discover what's installed.
- Missing custom nodes — "class_type not found" means a required node
isn't installed. check_deps.py reports which package to install;
auto_fix_deps.py runs the install for you.
- Working directory —
comfy-cliauto-detects the ComfyUI workspace.
If commands fail with "no workspace found", use
comfy --workspace /path/to/ComfyUI <command> or
comfy set-default /path/to/ComfyUI.
- Cloud free-tier API limits —
/api/prompt,/api/view,/api/upload/*,
/api/object_info all return 403 on free accounts. health_check.py and
check_deps.py handle this gracefully and surface a clear message.
- Timeout for video/audio workflows — auto-detected when an output node
is VHS_VideoCombine, SaveVideo, etc.; the default jumps from 300 s to
900 s. Override explicitly with --timeout 1800.
- Path traversal in output filenames — server-supplied filenames are
passed through safe_path_join to refuse anything escaping --output-dir.
Keep this protection on — workflows with custom save nodes can produce
arbitrary paths.
- Workflow JSON is arbitrary code — custom nodes run Python, so
submitting an unknown workflow has the same trust profile as eval.
Inspect workflows from untrusted sources before running.
- Auto-randomized seed — pass
seed: -1in--args(or use
--randomize-seed and omit the seed) to get a fresh seed per run.
The actual seed is logged to stderr.
trackingprompt — first run ofcomfymay prompt for analytics.
Use comfy --skip-prompt tracking disable to skip non-interactively.
comfyui_setup.sh does this for you.
Verification Checklist
Use python scripts/health_check.py to run the whole list at once. Manual:
- [ ]
hardware_check.pyverdict isokOR the user explicitly chose Comfy Cloud - [ ]
comfy --versionworks (oruvx --from comfy-cli comfy --help) - [ ]
curl http://HOST:PORT/system_statsreturns JSON - [ ]
comfy model listshows at least one checkpoint (local) OR
/api/experiment/models/checkpoints returns models (cloud)
- [ ] Workflow JSON is in API format
- [ ]
check_deps.pyreportsis_ready: true(or onlynode_check_skipped
on cloud free tier)
- [ ] Test run with a small workflow completes; outputs land in
--output-dir
质量与来源
- 所属仓库
- NousResearch/hermes-agent
- 仓库星标
- 25 万
- 最近更新
- 今天
- 采集时间
- 今天
- commit
- 0b89435e7e4f
- 内容指纹
- sha256:1013a06bf6accc0
- 文件路径
- optional-skills/creative/comfyui/SKILL.md